Search Results for author: Rui Zhang

Found 296 papers, 95 papers with code

Grouped-Attention for Content-Selection and Content-Plan Generation

no code implementations Findings (EMNLP) 2021 Bayu Distiawan Trisedya, Xiaojie Wang, Jianzhong Qi, Rui Zhang, Qingjun Cui

A key component of the GSC-attention is grouped-attention, which is token-level attention constrained within each input attribute that enables our proposed model captures both local and global context.

Data-to-Text Generation

Contrastive Data and Learning for Natural Language Processing

no code implementations NAACL (ACL) 2022 Rui Zhang, Yangfeng Ji, Yue Zhang, Rebecca J. Passonneau

We then survey the benefits and the best practices of contrastive learning for various downstream NLP applications including Text Classification, Question Answering, Summarization, Text Generation, Interpretability and Explainability, Commonsense Knowledge and Reasoning, Vision-and-Language. This tutorial intends to help researchers in the NLP and computational linguistics community to understand this emerging topic and promote future research directions of using contrastive learning for NLP applications.

Contrastive Learning Question Answering +4

Multi-Passive/Active-IRS Enhanced Wireless Coverage: Deployment Optimization and Cost-Performance Trade-off

no code implementations21 Sep 2023 Min Fu, Weidong Mei, Rui Zhang

To reconcile these trade-offs, we formulate a joint multi-PIRS/AIRS deployment problem to select an optimal subset of all candidate locations for deploying IRS and also optimize the number of passive/active reflecting elements deployed at each selected location to satisfy a given SNR target over all cells, such that the total deployment cost is minimized.

Combinatorial Optimization

An Anchor Learning Approach for Citation Field Learning

no code implementations7 Sep 2023 Zilin Yuan, Borun Chen, Yimeng Dai, Yinghui Li, Hai-Tao Zheng, Rui Zhang

CIFAL leverages the anchor learning, which is model-agnostic for any Pre-trained Language Model, to help capture citation patterns from the data of different citation styles.

Language Modelling

UMMAFormer: A Universal Multimodal-adaptive Transformer Framework for Temporal Forgery Localization

1 code implementation28 Aug 2023 Rui Zhang, Hongxia Wang, Mingshan Du, Hanqing Liu, Yang Zhou, Qiang Zeng

Our approach introduces a Temporal Feature Abnormal Attention (TFAA) module based on temporal feature reconstruction to enhance the detection of temporal differences.

Binary Classification Temporal Forgery Localization +1

MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendation

no code implementations22 Aug 2023 Jinpeng Wang, Ziyun Zeng, Yunxiao Wang, Yuting Wang, Xingyu Lu, Tianxiang Li, Jun Yuan, Rui Zhang, Hai-Tao Zheng, Shu-Tao Xia

We propose MISSRec, a multi-modal pre-training and transfer learning framework for SR. On the user side, we design a Transformer-based encoder-decoder model, where the contextual encoder learns to capture the sequence-level multi-modal synergy while a novel interest-aware decoder is developed to grasp item-modality-interest relations for better sequence representation.

Contrastive Learning Sequential Recommendation +1

Multi-domain Recommendation with Embedding Disentangling and Domain Alignment

1 code implementation10 Aug 2023 Wentao Ning, Xiao Yan, Weiwen Liu, Reynold Cheng, Rui Zhang, Bo Tang

We propose a new MDR method named EDDA with two key components, i. e., embedding disentangling recommender and domain alignment, to tackle the two challenges respectively.

Transfer Learning

Relational Contrastive Learning for Scene Text Recognition

1 code implementation1 Aug 2023 Jinglei Zhang, Tiancheng Lin, Yi Xu, Kai Chen, Rui Zhang

We argue that such prior contextual information can be interpreted as the relations of textual primitives due to the heterogeneous text and background, which can provide effective self-supervised labels for representation learning.

Contrastive Learning Representation Learning +1

MESED: A Multi-modal Entity Set Expansion Dataset with Fine-grained Semantic Classes and Hard Negative Entities

1 code implementation27 Jul 2023 Yangning Li, Tingwei Lu, Yinghui Li, Tianyu Yu, Shulin Huang, Hai-Tao Zheng, Rui Zhang, Jun Yuan

The Entity Set Expansion (ESE) task aims to expand a handful of seed entities with new entities belonging to the same semantic class.

AutoAlign: Fully Automatic and Effective Knowledge Graph Alignment enabled by Large Language Models

no code implementations18 Jul 2023 Rui Zhang, Yixin Su, Bayu Distiawan Trisedya, Xiaoyan Zhao, Min Yang, Hong Cheng, Jianzhong Qi

In this paper, we propose the first fully automatic alignment method named AutoAlign, which does not require any manually crafted seed alignments.

Entity Alignment Entity Embeddings +1

Energy Beamforming for RF Wireless Power Transfer with Dynamic Metasurface Antennas

no code implementations3 Jul 2023 Amirhossein Azarbahram, Onel L. A. Lopez, Richard D. Souza, Rui Zhang, Matti Latva-aho

Radio frequency (RF) wireless power transfer (WPT) is a promising technology for Internet of Things networks.

How far is Language Model from 100% Few-shot Named Entity Recognition in Medical Domain

1 code implementation1 Jul 2023 Mingchen Li, Rui Zhang

Recent advancements in language models (LMs) have led to the emergence of powerful models such as Small LMs (e. g., T5) and Large LMs (e. g., GPT-4).

few-shot-ner Few-shot NER +4

Cramér-Rao Bound Minimization for IRS-Enabled Multiuser Integrated Sensing and Communications

no code implementations30 Jun 2023 Xianxin Song, Xiaoqi Qin, Jie Xu, Rui Zhang

Accordingly, we model two types of CU receivers, namely Type-I and Type-II CU receivers, which do not have and have the capability of canceling the interference from the sensing signals, respectively.

RF-Based Simultaneous Localization and Source Seeking for Multi-Robot Systems

no code implementations27 Jun 2023 Ke Xu, Rui Zhang, He Chen

This paper considers a radio-frequency (RF)-based simultaneous localization and source-seeking (SLASS) problem in multi-robot systems, where multiple robots jointly localize themselves and an RF source using distance-only measurements extracted from RF signals and then control themselves to approach the source.

Pushing the Limits of Machine Design: Automated CPU Design with AI

1 code implementation21 Jun 2023 Shuyao Cheng, Pengwei Jin, Qi Guo, Zidong Du, Rui Zhang, Yunhao Tian, Xing Hu, Yongwei Zhao, Yifan Hao, Xiangtao Guan, Husheng Han, Zhengyue Zhao, Ximing Liu, Ling Li, Xishan Zhang, Yuejie Chu, Weilong Mao, Tianshi Chen, Yunji Chen

By efficiently exploring a search space of unprecedented size 10^{10^{540}}, which is the largest one of all machine-designed objects to our best knowledge, and thus pushing the limits of machine design, our approach generates an industrial-scale RISC-V CPU within only 5 hours.

Towards Open-World Recommendation with Knowledge Augmentation from Large Language Models

no code implementations19 Jun 2023 Yunjia Xi, Weiwen Liu, Jianghao Lin, Jieming Zhu, Bo Chen, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu

In this work, we propose an Open-World Knowledge Augmented Recommendation Framework with Large Language Models, dubbed KAR, to acquire two types of external knowledge from LLMs -- the reasoning knowledge on user preferences and the factual knowledge on items.

Recommendation Systems

FewSAR: A Few-shot SAR Image Classification Benchmark

1 code implementation16 Jun 2023 Rui Zhang, Ziqi Wang, Yang Li, Jiabao Wang, Zhiteng Wang

Motivated by this observation, we propose a novel few-shot SAR image classification benchmark (FewSAR) to address this issue.

Classification Few-Shot Learning +2

Equitable Multi-task Learning

no code implementations15 Jun 2023 Jun Yuan, Rui Zhang

To solve the issue, we in-depth investigate the equity problem for MTL and find that regularizing relative contribution of different tasks (i. e. value of task-specific loss divides its raw gradient norm) in updating shared parameter can improve generalization performance of MTL.

Multi-Task Learning

Online Prototype Alignment for Few-shot Policy Transfer

1 code implementation12 Jun 2023 Qi Yi, Rui Zhang, Shaohui Peng, Jiaming Guo, Yunkai Gao, Kaizhao Yuan, Ruizhi Chen, Siming Lan, Xing Hu, Zidong Du, Xishan Zhang, Qi Guo, Yunji Chen

Domain adaptation in reinforcement learning (RL) mainly deals with the changes of observation when transferring the policy to a new environment.

Domain Adaptation Reinforcement Learning (RL)

Learning Domain-Aware Detection Head with Prompt Tuning

no code implementations9 Jun 2023 Haochen Li, Rui Zhang, Hantao Yao, Xinkai Song, Yifan Hao, Yongwei Zhao, Ling Li, Yunji Chen

Domain adaptive object detection (DAOD) aims to generalize detectors trained on an annotated source domain to an unlabelled target domain.

Domain Adaptation object-detection +1

XSemPLR: Cross-Lingual Semantic Parsing in Multiple Natural Languages and Meaning Representations

1 code implementation7 Jun 2023 Yusen Zhang, Jun Wang, Zhiguo Wang, Rui Zhang

However, existing CLSP models are separately proposed and evaluated on datasets of limited tasks and applications, impeding a comprehensive and unified evaluation of CLSP on a diverse range of NLs and MRs. To this end, we present XSemPLR, a unified benchmark for cross-lingual semantic parsing featured with 22 natural languages and 8 meaning representations by examining and selecting 9 existing datasets to cover 5 tasks and 164 domains.

Cross-Lingual Transfer Semantic Parsing +2

Flew Over Learning Trap: Learn Unlearnable Samples by Progressive Staged Training

1 code implementation3 Jun 2023 Pucheng Dang, Xing Hu, Kaidi Xu, Jinhao Duan, Di Huang, Husheng Han, Rui Zhang, Zidong Du, Qi Guo, Yunji Chen

Unlearning techniques are proposed to prevent third parties from exploiting unauthorized data, which generate unlearnable samples by adding imperceptible perturbations to data for public publishing.

Unlearnable Examples for Diffusion Models: Protect Data from Unauthorized Exploitation

no code implementations2 Jun 2023 Zhengyue Zhao, Jinhao Duan, Xing Hu, Kaidi Xu, Chenan Wang, Rui Zhang, Zidong Du, Qi Guo, Yunji Chen

This imperceptible protective noise makes the data almost unlearnable for diffusion models, i. e., diffusion models trained or fine-tuned on the protected data cannot generate high-quality and diverse images related to the protected training data.

Denoising Image Generation

ANPL: Compiling Natural Programs with Interactive Decomposition

no code implementations29 May 2023 Di Huang, Ziyuan Nan, Xing Hu, Pengwei Jin, Shaohui Peng, Yuanbo Wen, Rui Zhang, Zidong Du, Qi Guo, Yewen Pu, Yunji Chen

Given an ANPL program, the ANPL compiler generates a cohesive Python program that implements the functionalities in hole, while respecting the dataflows specified in sketch.

Deep Graph Neural Networks via Flexible Subgraph Aggregation

no code implementations9 May 2023 Jingbo Zhou, Yixuan Du, Ruqiong Zhang, Di Jin, Carl Yang, Rui Zhang

Based on this, we propose a sampling-based node-level residual module (SNR) that can achieve a more flexible utilization of different hops of subgraph aggregation by introducing node-level parameters sampled from a learnable distribution.

Self-supervised Learning for Pre-Training 3D Point Clouds: A Survey

no code implementations8 May 2023 Ben Fei, Weidong Yang, Liwen Liu, Tianyue Luo, Rui Zhang, Yixuan Li, Ying He

Finally, we share our thoughts on some of the challenges and potential issues that future research in self-supervised learning for pre-training 3D point clouds may encounter.

Autonomous Driving Representation Learning +1

CSGCL: Community-Strength-Enhanced Graph Contrastive Learning

1 code implementation8 May 2023 Han Chen, Ziwen Zhao, Yuhua Li, Yixiong Zou, Ruixuan Li, Rui Zhang

Graph Contrastive Learning (GCL) is an effective way to learn generalized graph representations in a self-supervised manner, and has grown rapidly in recent years.

Contrastive Learning Link Prediction +2

Denoising Multi-modal Sequential Recommenders with Contrastive Learning

no code implementations3 May 2023 Dong Yao, Shengyu Zhang, Zhou Zhao, Jieming Zhu, Wenqiao Zhang, Rui Zhang, Xiaofei He, Fei Wu

In contrast, modalities that do not cause users' behaviors are potential noises and might mislead the learning of a recommendation model.

Contrastive Learning Denoising +2

Accurate and Efficient Event-based Semantic Segmentation Using Adaptive Spiking Encoder-Decoder Network

no code implementations24 Apr 2023 Rui Zhang, Luziwei Leng, Kaiwei Che, Hu Zhang, Jie Cheng, Qinghai Guo, Jiangxing Liao, Ran Cheng

Leveraging the low-power, event-driven computation and the inherent temporal dynamics, spiking neural networks (SNNs) are potentially ideal solutions for processing dynamic and asynchronous signals from event-based sensors.

Event-based vision Semantic Segmentation

Joint Beam Scheduling and Power Allocation for SWIPT in Mixed Near- and Far-Field Channels

no code implementations17 Apr 2023 Yunpu Zhang, Changsheng You, Weijie Yuan, Fan Liu, Rui Zhang

Extremely large-scale array (XL-array) has emerged as a promising technology to enhance the spectrum efficiency and spatial resolution in future wireless networks, leading to a fundamental paradigm shift from conventional far-field communications towards the new near-field communications.


False Claims against Model Ownership Resolution

no code implementations13 Apr 2023 Jian Liu, Rui Zhang, Sebastian Szyller, Kui Ren, N. Asokan

Our core idea is that a malicious accuser can deviate (without detection) from the specified MOR process by finding (transferable) adversarial examples that successfully serve as evidence against independent suspect models.

Fair-CDA: Continuous and Directional Augmentation for Group Fairness

no code implementations1 Apr 2023 Rui Sun, Fengwei Zhou, Zhenhua Dong, Chuanlong Xie, Lanqing Hong, Jiawei Li, Rui Zhang, Zhen Li, Zhenguo Li

By adjusting the perturbation strength in the direction of the paths, our proposed augmentation is controllable and auditable.

Data Augmentation Disentanglement +1

Knowledge-augmented Frame Semantic Parsing with Hybrid Prompt-tuning

no code implementations25 Mar 2023 Rui Zhang, Yajing Sun, Jingyuan Yang, Wei Peng

We propose a novel Knowledge-Augmented Frame Semantic Parsing Architecture (KAF-SPA) to enhance semantic representation by incorporating accurate frame knowledge into PLMs during frame semantic parsing.

Knowledge Probing Semantic Parsing

Visual-Language Prompt Tuning with Knowledge-guided Context Optimization

1 code implementation CVPR 2023 Hantao Yao, Rui Zhang, Changsheng Xu

Representative CoOp-based work combines the learnable textual tokens with the class tokens to obtain specific textual knowledge.

Language Modelling

Bounding System-Induced Biases in Recommender Systems with A Randomized Dataset

1 code implementation21 Mar 2023 Dugang Liu, Pengxiang Cheng, Zinan Lin, Xiaolian Zhang, Zhenhua Dong, Rui Zhang, Xiuqiang He, Weike Pan, Zhong Ming

To bridge this gap, we study the debiasing problem from a new perspective and propose to directly minimize the upper bound of an ideal objective function, which facilitates a better potential solution to the system-induced biases.

Recommendation Systems

A Cross-institutional Evaluation on Breast Cancer Phenotyping NLP Algorithms on Electronic Health Records

no code implementations15 Mar 2023 Sicheng Zhou, Nan Wang, LiWei Wang, Ju Sun, Anne Blaes, Hongfang Liu, Rui Zhang

We developed three types of NLP models (i. e., conditional random field, bi-directional long short-term memory and CancerBERT) to extract cancer phenotypes from clinical texts.

Conceptual Reinforcement Learning for Language-Conditioned Tasks

no code implementations9 Mar 2023 Shaohui Peng, Xing Hu, Rui Zhang, Jiaming Guo, Qi Yi, Ruizhi Chen, Zidong Du, Ling Li, Qi Guo, Yunji Chen

Recently, the language-conditioned policy is proposed to facilitate policy transfer through learning the joint representation of observation and text that catches the compact and invariant information across environments.

reinforcement-learning Reinforcement Learning (RL)

Compressed Interaction Graph based Framework for Multi-behavior Recommendation

1 code implementation4 Mar 2023 Wei Guo, Chang Meng, Enming Yuan, ZhiCheng He, Huifeng Guo, Yingxue Zhang, Bo Chen, Yaochen Hu, Ruiming Tang, Xiu Li, Rui Zhang

However, it is challenging to explore multi-behavior data due to the unbalanced data distribution and sparse target behavior, which lead to the inadequate modeling of high-order relations when treating multi-behavior data ''as features'' and gradient conflict in multitask learning when treating multi-behavior data ''as labels''.

Multi-Task Learning

Ultra-low Precision Multiplication-free Training for Deep Neural Networks

no code implementations28 Feb 2023 Chang Liu, Rui Zhang, Xishan Zhang, Yifan Hao, Zidong Du, Xing Hu, Ling Li, Qi Guo

The energy-efficient works try to decrease the precision of multiplication or replace the multiplication with energy-efficient operations such as addition or bitwise shift, to reduce the energy consumption of FP32 multiplications.


Dirichlet-based Uncertainty Calibration for Active Domain Adaptation

1 code implementation27 Feb 2023 Mixue Xie, Shuang Li, Rui Zhang, Chi Harold Liu

Active domain adaptation (DA) aims to maximally boost the model adaptation on a new target domain by actively selecting limited target data to annotate, whereas traditional active learning methods may be less effective since they do not consider the domain shift issue.

Active Learning Domain Adaptation +2

Online Symbolic Regression with Informative Query

no code implementations21 Feb 2023 Pengwei Jin, Di Huang, Rui Zhang, Xing Hu, Ziyuan Nan, Zidong Du, Qi Guo, Yunji Chen

Symbolic regression, the task of extracting mathematical expressions from the observed data $\{ \vx_i, y_i \}$, plays a crucial role in scientific discovery.

regression Symbolic Regression

A method for incremental discovery of financial event types based on anomaly detection

no code implementations16 Feb 2023 Dianyue Gu, Zixu Li, Zhenhai Guan, Rui Zhang, Lan Huang

Event datasets in the financial domain are often constructed based on actual application scenarios, and their event types are weakly reusable due to scenario constraints; at the same time, the massive and diverse new financial big data cannot be limited to the event types defined for specific scenarios.

Anomaly Detection Deep Clustering +1

Intelligent Reflecting Surface Aided Wireless Sensing: Applications and Design Issues

no code implementations12 Feb 2023 Xiaodan Shao, Changsheng You, Rui Zhang

Intelligent reflecting surface (IRS) is an emerging technology that is able to significantly improve the performance of wireless communications, by smartly tuning signal reflections at a large number of passive reflecting elements.

Monte Carlo Neural Operator for Learning PDEs via Probabilistic Representation

no code implementations10 Feb 2023 Rui Zhang, Qi Meng, Rongchan Zhu, Yue Wang, Wenlei Shi, Shihua Zhang, Zhi-Ming Ma, Tie-Yan Liu

Neural operators, which use deep neural networks to approximate the solution mappings of partial differential equation (PDE) systems, are emerging as a new paradigm for PDE simulation.

Target-Mounted Intelligent Reflecting Surface for Joint Location and Orientation Estimation

no code implementations23 Jan 2023 Peilan Wang, Weidong Mei, Jun Fang, Rui Zhang

In this paper, we propose a new application of IRS for device-free target sensing via joint location and orientation estimation.

Adaptive Depth Graph Attention Networks

no code implementations16 Jan 2023 Jingbo Zhou, Yixuan Du, Ruqiong Zhang, Rui Zhang

As one of the most popular GNN architectures, the graph attention networks (GAT) is considered the most advanced learning architecture for graph representation and has been widely used in various graph mining tasks with impressive results.

Graph Attention Graph Mining

Exploring a multi_stage feedback teaching mode for graduate students of software engineering discipline based on project_driven competition

no code implementations19 Dec 2022 Xiangdong Pei, Rui Zhang

Aiming at the current problems of theory-oriented, practice-light, and lack of innovation ability in the teaching of postgraduate software engineering courses, a multi-stage feedback teaching mode for software engineering postgraduates based on competition project_driven is proposed.

Adaptive Low-Precision Training for Embeddings in Click-Through Rate Prediction

no code implementations12 Dec 2022 Shiwei Li, Huifeng Guo, Lu Hou, Wei zhang, Xing Tang, Ruiming Tang, Rui Zhang, Ruixuan Li

To this end, we formulate a novel quantization training paradigm to compress the embeddings from the training stage, termed low-precision training (LPT).

Click-Through Rate Prediction Quantization

Electromagnetic Environment Analysis of High-Power Wireless Charging Device

no code implementations8 Dec 2022 Zhengyang Zhang, Zhihui Liu, Wenjin Zhang, Rui Zhang, Xiang Xiao

Conclusion This paper explores the radiation level and distribution of the electromagnetic field around this type of charging equipment.

Vocal Bursts Intensity Prediction

Optimal Sparse Regression Trees

1 code implementation28 Nov 2022 Rui Zhang, Rui Xin, Margo Seltzer, Cynthia Rudin

Regression trees are one of the oldest forms of AI models, and their predictions can be made without a calculator, which makes them broadly useful, particularly for high-stakes applications.

Clustering regression

3-D Positioning and Resource Allocation for Multi-UAV Base Stations Under Blockage-Aware Channel Model

no code implementations23 Nov 2022 Pengfei Yi, Lipeng Zhu, Zhenyu Xiao, Rui Zhang, Zhu Han, Xiang-Gen Xia

Based on the proposed channel model, we formulate the joint optimization problem of UAV three-dimensional (3-D) positioning and resource allocation, by power allocation, user association, and subcarrier allocation, to maximize the minimum achievable rate among users.

A Bird's-eye View of Reranking: from List Level to Page Level

1 code implementation17 Nov 2022 Yunjia Xi, Jianghao Lin, Weiwen Liu, Xinyi Dai, Weinan Zhang, Rui Zhang, Ruiming Tang, Yong Yu

Moreover, simply applying a shared network for all the lists fails to capture the commonalities and distinctions in user behaviors on different lists.

Recommendation Systems

A Generalized Doubly Robust Learning Framework for Debiasing Post-Click Conversion Rate Prediction

no code implementations12 Nov 2022 Quanyu Dai, Haoxuan Li, Peng Wu, Zhenhua Dong, Xiao-Hua Zhou, Rui Zhang, Jie Sun

However, in this paper, by theoretically analyzing the bias, variance and generalization bounds of DR methods, we find that existing DR approaches may have poor generalization caused by inaccurate estimation of propensity scores and imputation errors, which often occur in practice.

Generalization Bounds Imputation +1

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

3 code implementations9 Nov 2022 BigScience Workshop, :, Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, Matthias Gallé, Jonathan Tow, Alexander M. Rush, Stella Biderman, Albert Webson, Pawan Sasanka Ammanamanchi, Thomas Wang, Benoît Sagot, Niklas Muennighoff, Albert Villanova del Moral, Olatunji Ruwase, Rachel Bawden, Stas Bekman, Angelina McMillan-Major, Iz Beltagy, Huu Nguyen, Lucile Saulnier, Samson Tan, Pedro Ortiz Suarez, Victor Sanh, Hugo Laurençon, Yacine Jernite, Julien Launay, Margaret Mitchell, Colin Raffel, Aaron Gokaslan, Adi Simhi, Aitor Soroa, Alham Fikri Aji, Amit Alfassy, Anna Rogers, Ariel Kreisberg Nitzav, Canwen Xu, Chenghao Mou, Chris Emezue, Christopher Klamm, Colin Leong, Daniel van Strien, David Ifeoluwa Adelani, Dragomir Radev, Eduardo González Ponferrada, Efrat Levkovizh, Ethan Kim, Eyal Bar Natan, Francesco De Toni, Gérard Dupont, Germán Kruszewski, Giada Pistilli, Hady Elsahar, Hamza Benyamina, Hieu Tran, Ian Yu, Idris Abdulmumin, Isaac Johnson, Itziar Gonzalez-Dios, Javier de la Rosa, Jenny Chim, Jesse Dodge, Jian Zhu, Jonathan Chang, Jörg Frohberg, Joseph Tobing, Joydeep Bhattacharjee, Khalid Almubarak, Kimbo Chen, Kyle Lo, Leandro von Werra, Leon Weber, Long Phan, Loubna Ben allal, Ludovic Tanguy, Manan Dey, Manuel Romero Muñoz, Maraim Masoud, María Grandury, Mario Šaško, Max Huang, Maximin Coavoux, Mayank Singh, Mike Tian-Jian Jiang, Minh Chien Vu, Mohammad A. Jauhar, Mustafa Ghaleb, Nishant Subramani, Nora Kassner, Nurulaqilla Khamis, Olivier Nguyen, Omar Espejel, Ona de Gibert, Paulo Villegas, Peter Henderson, Pierre Colombo, Priscilla Amuok, Quentin Lhoest, Rheza Harliman, Rishi Bommasani, Roberto Luis López, Rui Ribeiro, Salomey Osei, Sampo Pyysalo, Sebastian Nagel, Shamik Bose, Shamsuddeen Hassan Muhammad, Shanya Sharma, Shayne Longpre, Somaieh Nikpoor, Stanislav Silberberg, Suhas Pai, Sydney Zink, Tiago Timponi Torrent, Timo Schick, Tristan Thrush, Valentin Danchev, Vassilina Nikoulina, Veronika Laippala, Violette Lepercq, Vrinda Prabhu, Zaid Alyafeai, Zeerak Talat, Arun Raja, Benjamin Heinzerling, Chenglei Si, Davut Emre Taşar, Elizabeth Salesky, Sabrina J. Mielke, Wilson Y. Lee, Abheesht Sharma, Andrea Santilli, Antoine Chaffin, Arnaud Stiegler, Debajyoti Datta, Eliza Szczechla, Gunjan Chhablani, Han Wang, Harshit Pandey, Hendrik Strobelt, Jason Alan Fries, Jos Rozen, Leo Gao, Lintang Sutawika, M Saiful Bari, Maged S. Al-shaibani, Matteo Manica, Nihal Nayak, Ryan Teehan, Samuel Albanie, Sheng Shen, Srulik Ben-David, Stephen H. Bach, Taewoon Kim, Tali Bers, Thibault Fevry, Trishala Neeraj, Urmish Thakker, Vikas Raunak, Xiangru Tang, Zheng-Xin Yong, Zhiqing Sun, Shaked Brody, Yallow Uri, Hadar Tojarieh, Adam Roberts, Hyung Won Chung, Jaesung Tae, Jason Phang, Ofir Press, Conglong Li, Deepak Narayanan, Hatim Bourfoune, Jared Casper, Jeff Rasley, Max Ryabinin, Mayank Mishra, Minjia Zhang, Mohammad Shoeybi, Myriam Peyrounette, Nicolas Patry, Nouamane Tazi, Omar Sanseviero, Patrick von Platen, Pierre Cornette, Pierre François Lavallée, Rémi Lacroix, Samyam Rajbhandari, Sanchit Gandhi, Shaden Smith, Stéphane Requena, Suraj Patil, Tim Dettmers, Ahmed Baruwa, Amanpreet Singh, Anastasia Cheveleva, Anne-Laure Ligozat, Arjun Subramonian, Aurélie Névéol, Charles Lovering, Dan Garrette, Deepak Tunuguntla, Ehud Reiter, Ekaterina Taktasheva, Ekaterina Voloshina, Eli Bogdanov, Genta Indra Winata, Hailey Schoelkopf, Jan-Christoph Kalo, Jekaterina Novikova, Jessica Zosa Forde, Jordan Clive, Jungo Kasai, Ken Kawamura, Liam Hazan, Marine Carpuat, Miruna Clinciu, Najoung Kim, Newton Cheng, Oleg Serikov, Omer Antverg, Oskar van der Wal, Rui Zhang, Ruochen Zhang, Sebastian Gehrmann, Shachar Mirkin, Shani Pais, Tatiana Shavrina, Thomas Scialom, Tian Yun, Tomasz Limisiewicz, Verena Rieser, Vitaly Protasov, Vladislav Mikhailov, Yada Pruksachatkun, Yonatan Belinkov, Zachary Bamberger, Zdeněk Kasner, Alice Rueda, Amanda Pestana, Amir Feizpour, Ammar Khan, Amy Faranak, Ana Santos, Anthony Hevia, Antigona Unldreaj, Arash Aghagol, Arezoo Abdollahi, Aycha Tammour, Azadeh HajiHosseini, Bahareh Behroozi, Benjamin Ajibade, Bharat Saxena, Carlos Muñoz Ferrandis, Daniel McDuff, Danish Contractor, David Lansky, Davis David, Douwe Kiela, Duong A. Nguyen, Edward Tan, Emi Baylor, Ezinwanne Ozoani, Fatima Mirza, Frankline Ononiwu, Habib Rezanejad, Hessie Jones, Indrani Bhattacharya, Irene Solaiman, Irina Sedenko, Isar Nejadgholi, Jesse Passmore, Josh Seltzer, Julio Bonis Sanz, Livia Dutra, Mairon Samagaio, Maraim Elbadri, Margot Mieskes, Marissa Gerchick, Martha Akinlolu, Michael McKenna, Mike Qiu, Muhammed Ghauri, Mykola Burynok, Nafis Abrar, Nazneen Rajani, Nour Elkott, Nour Fahmy, Olanrewaju Samuel, Ran An, Rasmus Kromann, Ryan Hao, Samira Alizadeh, Sarmad Shubber, Silas Wang, Sourav Roy, Sylvain Viguier, Thanh Le, Tobi Oyebade, Trieu Le, Yoyo Yang, Zach Nguyen, Abhinav Ramesh Kashyap, Alfredo Palasciano, Alison Callahan, Anima Shukla, Antonio Miranda-Escalada, Ayush Singh, Benjamin Beilharz, Bo wang, Caio Brito, Chenxi Zhou, Chirag Jain, Chuxin Xu, Clémentine Fourrier, Daniel León Periñán, Daniel Molano, Dian Yu, Enrique Manjavacas, Fabio Barth, Florian Fuhrimann, Gabriel Altay, Giyaseddin Bayrak, Gully Burns, Helena U. Vrabec, Imane Bello, Ishani Dash, Jihyun Kang, John Giorgi, Jonas Golde, Jose David Posada, Karthik Rangasai Sivaraman, Lokesh Bulchandani, Lu Liu, Luisa Shinzato, Madeleine Hahn de Bykhovetz, Maiko Takeuchi, Marc Pàmies, Maria A Castillo, Marianna Nezhurina, Mario Sänger, Matthias Samwald, Michael Cullan, Michael Weinberg, Michiel De Wolf, Mina Mihaljcic, Minna Liu, Moritz Freidank, Myungsun Kang, Natasha Seelam, Nathan Dahlberg, Nicholas Michio Broad, Nikolaus Muellner, Pascale Fung, Patrick Haller, Ramya Chandrasekhar, Renata Eisenberg, Robert Martin, Rodrigo Canalli, Rosaline Su, Ruisi Su, Samuel Cahyawijaya, Samuele Garda, Shlok S Deshmukh, Shubhanshu Mishra, Sid Kiblawi, Simon Ott, Sinee Sang-aroonsiri, Srishti Kumar, Stefan Schweter, Sushil Bharati, Tanmay Laud, Théo Gigant, Tomoya Kainuma, Wojciech Kusa, Yanis Labrak, Yash Shailesh Bajaj, Yash Venkatraman, Yifan Xu, Yingxin Xu, Yu Xu, Zhe Tan, Zhongli Xie, Zifan Ye, Mathilde Bras, Younes Belkada, Thomas Wolf

Large language models (LLMs) have been shown to be able to perform new tasks based on a few demonstrations or natural language instructions.

Language Modelling Multilingual NLP

MACSum: Controllable Summarization with Mixed Attributes

1 code implementation9 Nov 2022 Yusen Zhang, Yang Liu, ZiYi Yang, Yuwei Fang, Yulong Chen, Dragomir Radev, Chenguang Zhu, Michael Zeng, Rui Zhang

We propose two simple and effective parameter-efficient approaches for the new task of mixed controllable summarization based on hard prompt tuning and soft prefix tuning.


XRICL: Cross-lingual Retrieval-Augmented In-Context Learning for Cross-lingual Text-to-SQL Semantic Parsing

no code implementations25 Oct 2022 Peng Shi, Rui Zhang, He Bai, Jimmy Lin

We also include global translation exemplars for a target language to facilitate the translation process for large language models.

Retrieval Semantic Parsing +3

On the Robustness of Dataset Inference

no code implementations24 Oct 2022 Sebastian Szyller, Rui Zhang, Jian Liu, N. Asokan

However, in a subspace of the same setting, we prove that DI suffers from high false positives (FPs) -- it can incorrectly identify an independent model trained with non-overlapping data from the same distribution as stolen.

ReasTAP: Injecting Table Reasoning Skills During Pre-training via Synthetic Reasoning Examples

1 code implementation22 Oct 2022 Yilun Zhao, Linyong Nan, Zhenting Qi, Rui Zhang, Dragomir Radev

Reasoning over tabular data requires both table structure understanding and a broad set of table reasoning skills.

Ranked #2 on Semantic Parsing on WikiSQL (Denotation accuracy (test) metric)

Fact Verification Question Answering +3

Strategic Decisions Survey, Taxonomy, and Future Directions from Artificial Intelligence Perspective

no code implementations22 Oct 2022 Caesar Wu, Kotagiri Ramamohanarao, Rui Zhang, Pascal Bouvry

Strategic Decision-Making is always challenging because it is inherently uncertain, ambiguous, risky, and complex.

Decision Making

Imbalanced Classification in Medical Imaging via Regrouping

no code implementations21 Oct 2022 Le Peng, Yash Travadi, Rui Zhang, Ying Cui, Ju Sun

We propose performing imbalanced classification by regrouping majority classes into small classes so that we turn the problem into balanced multiclass classification.

Image Classification imbalanced classification +1

TransAlign: Fully Automatic and Effective Entity Alignment for Knowledge Graphs

no code implementations16 Oct 2022 Rui Zhang, Xiaoyan Zhao, Bayu Distiawan Trisedya, Min Yang, Hong Cheng, Jianzhong Qi

The task of entity alignment between knowledge graphs (KGs) aims to identify every pair of entities from two different KGs that represent the same entity.

Entity Alignment Entity Embeddings +1

ConEntail: An Entailment-based Framework for Universal Zero and Few Shot Classification with Supervised Contrastive Pretraining

1 code implementation14 Oct 2022 Ranran Haoran Zhang, Aysa Xuemo Fan, Rui Zhang

To fill these gaps, we propose ConEntail, a new framework for universal zero and few shot classification with supervised contrastive pretraining.

Classification Natural Language Inference +1

Object-Category Aware Reinforcement Learning

no code implementations13 Oct 2022 Qi Yi, Rui Zhang, Shaohui Peng, Jiaming Guo, Xing Hu, Zidong Du, Xishan Zhang, Qi Guo, Yunji Chen

Object-oriented reinforcement learning (OORL) is a promising way to improve the sample efficiency and generalization ability over standard RL.

Feature Engineering Object Discovery +2

Causality-driven Hierarchical Structure Discovery for Reinforcement Learning

no code implementations13 Oct 2022 Shaohui Peng, Xing Hu, Rui Zhang, Ke Tang, Jiaming Guo, Qi Yi, Ruizhi Chen, Xishan Zhang, Zidong Du, Ling Li, Qi Guo, Yunji Chen

To address this issue, we propose CDHRL, a causality-driven hierarchical reinforcement learning framework, leveraging a causality-driven discovery instead of a randomness-driven exploration to effectively build high-quality hierarchical structures in complicated environments.

Hierarchical Reinforcement Learning reinforcement-learning +1

Active and Passive IRS Jointly Aided Communication: Deployment Design and Achievable Rate

1 code implementation12 Sep 2022 Min Fu, Rui Zhang

In this letter, we study the wireless point-to-point communication from a transmitter (Tx) to a receiver (Rx), which is jointly aided by an active intelligent reflecting surface (AIRS) and a passive IRS (PIRS).

Selective Annotation Makes Language Models Better Few-Shot Learners

1 code implementation5 Sep 2022 Hongjin Su, Jungo Kasai, Chen Henry Wu, Weijia Shi, Tianlu Wang, Jiayi Xin, Rui Zhang, Mari Ostendorf, Luke Zettlemoyer, Noah A. Smith, Tao Yu

Departing from recent in-context learning methods, we formulate an annotation-efficient, two-step framework: selective annotation that chooses a pool of examples to annotate from unlabeled data in advance, followed by prompt retrieval that retrieves task examples from the annotated pool at test time.

Code Generation Retrieval

A Novel SCA-Based Method for Beamforming Optimization in IRS/RIS-Assisted MU-MISO Downlink

1 code implementation25 Aug 2022 Vaibhav Kumar, Rui Zhang, Marco Di Renzo, Le-Nam Tran

In this letter, we consider the fundamental problem of jointly designing the transmit beamformers and the phase-shifts of the intelligent reflecting surface (IRS) / reconfigurable intelligent surface (RIS) to minimize the transmit power, subject to quality-of-service constraints at individual users in an IRS-assisted multiuser multiple-input single-output downlink communication system.

EgPDE-Net: Building Continuous Neural Networks for Time Series Prediction with Exogenous Variables

1 code implementation3 Aug 2022 Penglei Gao, Xi Yang, Kaizhu Huang, Rui Zhang, Ping Guo, John Y. Goulermas

While exogenous variables have a major impact on performance improvement in time series analysis, inter-series correlation and time dependence among them are rarely considered in the present continuous methods.

Time Series Time Series Prediction

Code Comment Inconsistency Detection with BERT and Longformer

1 code implementation29 Jul 2022 Theo Steiner, Rui Zhang

Comments, or natural language descriptions of source code, are standard practice among software developers.

Natural Language Inference

FRIB: Low-poisoning Rate Invisible Backdoor Attack based on Feature Repair

no code implementations26 Jul 2022 Hui Xia, Xiugui Yang, Xiangyun Qian, Rui Zhang

To solve the above problems, we propose the idea of feature repair for the first time and introduce the blind watermark technique to repair the poisoned features lost during the generation of poisoned data.

Backdoor Attack

LEO Satellite Access Network (LEO-SAN) Towards 6G: Challenges and Approaches

1 code implementation25 Jul 2022 Zhenyu Xiao, Junyi Yang, Tianqi Mao, Chong Xu, Rui Zhang, Zhu Han, Xiang-Gen Xia

With the rapid development of satellite communication technologies, the space-based access network has been envisioned as a promising complementary part of the future 6G network.


Deep Manifold Learning with Graph Mining

no code implementations18 Jul 2022 Xuelong Li, Ziheng Jiao, Hongyuan Zhang, Rui Zhang

Admittedly, Graph Convolution Network (GCN) has achieved excellent results on graph datasets such as social networks, citation networks, etc.

Graph Mining

SepLUT: Separable Image-adaptive Lookup Tables for Real-time Image Enhancement

1 code implementation18 Jul 2022 Canqian Yang, Meiguang Jin, Yi Xu, Rui Zhang, Ying Chen, Huaida Liu

Image-adaptive lookup tables (LUTs) have achieved great success in real-time image enhancement tasks due to their high efficiency for modeling color transforms.

Image Enhancement Photo Retouching

Outpainting by Queries

1 code implementation12 Jul 2022 Kai Yao, Penglei Gao, Xi Yang, Kaizhu Huang, Jie Sun, Rui Zhang

Image outpainting, which is well studied with Convolution Neural Network (CNN) based framework, has recently drawn more attention in computer vision.

Image Outpainting

MIA 2022 Shared Task: Evaluating Cross-lingual Open-Retrieval Question Answering for 16 Diverse Languages

no code implementations NAACL (MIA) 2022 Akari Asai, Shayne Longpre, Jungo Kasai, Chia-Hsuan Lee, Rui Zhang, Junjie Hu, Ikuya Yamada, Jonathan H. Clark, Eunsol Choi

We present the results of the Workshop on Multilingual Information Access (MIA) 2022 Shared Task, evaluating cross-lingual open-retrieval question answering (QA) systems in 16 typologically diverse languages.

Question Answering Retrieval

Detecting Arbitrary Order Beneficial Feature Interactions for Recommender Systems

1 code implementation28 Jun 2022 Yixin Su, Yunxiang Zhao, Sarah Erfani, Junhao Gan, Rui Zhang

Detecting beneficial feature interactions is essential in recommender systems, and existing approaches achieve this by examining all the possible feature interactions.

Recommendation Systems

SSMI: How to Make Objects of Interest Disappear without Accessing Object Detectors?

no code implementations22 Jun 2022 Hui Xia, Rui Zhang, Zi Kang, Shuliang Jiang

Most black-box adversarial attack schemes for object detectors mainly face two shortcomings: requiring access to the target model and generating inefficient adversarial examples (failing to make objects disappear in large numbers).

Adversarial Attack object-detection +2

AdvSmo: Black-box Adversarial Attack by Smoothing Linear Structure of Texture

no code implementations22 Jun 2022 Hui Xia, Rui Zhang, Shuliang Jiang, Zi Kang

We construct the adversarial examples without relying on any internal information to the target model and design the imperceptible-high attack success rate constraint to guide the Gabor filter to select appropriate angles and scales to smooth the linear texture from the input images to generate adversarial examples.

Adversarial Attack Adversarial Defense

Deep Random Vortex Method for Simulation and Inference of Navier-Stokes Equations

no code implementations20 Jun 2022 Rui Zhang, Peiyan Hu, Qi Meng, Yue Wang, Rongchan Zhu, Bingguang Chen, Zhi-Ming Ma, Tie-Yan Liu

To this end, we propose the \emph{Deep Random Vortex Method} (DRVM), which combines the neural network with a random vortex dynamics system equivalent to the Navier-Stokes equation.

An F-shape Click Model for Information Retrieval on Multi-block Mobile Pages

1 code implementation17 Jun 2022 Lingyue Fu, Jianghao Lin, Weiwen Liu, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu

However, with the development of user interface (UI) design, the layout of displayed items on a result page tends to be multi-block (i. e., multi-list) style instead of a single list, which requires different assumptions to model user behaviors more accurately.

Information Retrieval Retrieval

A Survey on Gradient Inversion: Attacks, Defenses and Future Directions

no code implementations15 Jun 2022 Rui Zhang, Song Guo, Junxiao Wang, Xin Xie, DaCheng Tao

In particular, we dig out some critical ingredients from the iteration-based attacks, including data initialization, model training and gradient matching.

Regularization Penalty Optimization for Addressing Data Quality Variance in OoD Algorithms

no code implementations12 Jun 2022 Runpeng Yu, Hong Zhu, Kaican Li, Lanqing Hong, Rui Zhang, Nanyang Ye, Shao-Lun Huang, Xiuqiang He

Due to the poor generalization performance of traditional empirical risk minimization (ERM) in the case of distributional shift, Out-of-Distribution (OoD) generalization algorithms receive increasing attention.


Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

1 code implementation9 Jun 2022 Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, Abu Awal Md Shoeb, Abubakar Abid, Adam Fisch, Adam R. Brown, Adam Santoro, Aditya Gupta, Adrià Garriga-Alonso, Agnieszka Kluska, Aitor Lewkowycz, Akshat Agarwal, Alethea Power, Alex Ray, Alex Warstadt, Alexander W. Kocurek, Ali Safaya, Ali Tazarv, Alice Xiang, Alicia Parrish, Allen Nie, Aman Hussain, Amanda Askell, Amanda Dsouza, Ambrose Slone, Ameet Rahane, Anantharaman S. Iyer, Anders Andreassen, Andrea Madotto, Andrea Santilli, Andreas Stuhlmüller, Andrew Dai, Andrew La, Andrew Lampinen, Andy Zou, Angela Jiang, Angelica Chen, Anh Vuong, Animesh Gupta, Anna Gottardi, Antonio Norelli, Anu Venkatesh, Arash Gholamidavoodi, Arfa Tabassum, Arul Menezes, Arun Kirubarajan, Asher Mullokandov, Ashish Sabharwal, Austin Herrick, Avia Efrat, Aykut Erdem, Ayla Karakaş, B. Ryan Roberts, Bao Sheng Loe, Barret Zoph, Bartłomiej Bojanowski, Batuhan Özyurt, Behnam Hedayatnia, Behnam Neyshabur, Benjamin Inden, Benno Stein, Berk Ekmekci, Bill Yuchen Lin, Blake Howald, Bryan Orinion, Cameron Diao, Cameron Dour, Catherine Stinson, Cedrick Argueta, César Ferri Ramírez, Chandan Singh, Charles Rathkopf, Chenlin Meng, Chitta Baral, Chiyu Wu, Chris Callison-Burch, Chris Waites, Christian Voigt, Christopher D. Manning, Christopher Potts, Cindy Ramirez, Clara E. Rivera, Clemencia Siro, Colin Raffel, Courtney Ashcraft, Cristina Garbacea, Damien Sileo, Dan Garrette, Dan Hendrycks, Dan Kilman, Dan Roth, Daniel Freeman, Daniel Khashabi, Daniel Levy, Daniel Moseguí González, Danielle Perszyk, Danny Hernandez, Danqi Chen, Daphne Ippolito, Dar Gilboa, David Dohan, David Drakard, David Jurgens, Debajyoti Datta, Deep Ganguli, Denis Emelin, Denis Kleyko, Deniz Yuret, Derek Chen, Derek Tam, Dieuwke Hupkes, Diganta Misra, Dilyar Buzan, Dimitri Coelho Mollo, Diyi Yang, Dong-Ho Lee, Dylan Schrader, Ekaterina Shutova, Ekin Dogus Cubuk, Elad Segal, Eleanor Hagerman, Elizabeth Barnes, Elizabeth Donoway, Ellie Pavlick, Emanuele Rodola, Emma Lam, Eric Chu, Eric Tang, Erkut Erdem, Ernie Chang, Ethan A. Chi, Ethan Dyer, Ethan Jerzak, Ethan Kim, Eunice Engefu Manyasi, Evgenii Zheltonozhskii, Fanyue Xia, Fatemeh Siar, Fernando Martínez-Plumed, Francesca Happé, Francois Chollet, Frieda Rong, Gaurav Mishra, Genta Indra Winata, Gerard de Melo, Germán Kruszewski, Giambattista Parascandolo, Giorgio Mariani, Gloria Wang, Gonzalo Jaimovitch-López, Gregor Betz, Guy Gur-Ari, Hana Galijasevic, Hannah Kim, Hannah Rashkin, Hannaneh Hajishirzi, Harsh Mehta, Hayden Bogar, Henry Shevlin, Hinrich Schütze, Hiromu Yakura, Hongming Zhang, Hugh Mee Wong, Ian Ng, Isaac Noble, Jaap Jumelet, Jack Geissinger, Jackson Kernion, Jacob Hilton, Jaehoon Lee, Jaime Fernández Fisac, James B. Simon, James Koppel, James Zheng, James Zou, Jan Kocoń, Jana Thompson, Janelle Wingfield, Jared Kaplan, Jarema Radom, Jascha Sohl-Dickstein, Jason Phang, Jason Wei, Jason Yosinski, Jekaterina Novikova, Jelle Bosscher, Jennifer Marsh, Jeremy Kim, Jeroen Taal, Jesse Engel, Jesujoba Alabi, Jiacheng Xu, Jiaming Song, Jillian Tang, Joan Waweru, John Burden, John Miller, John U. Balis, Jonathan Batchelder, Jonathan Berant, Jörg Frohberg, Jos Rozen, Jose Hernandez-Orallo, Joseph Boudeman, Joseph Guerr, Joseph Jones, Joshua B. Tenenbaum, Joshua S. Rule, Joyce Chua, Kamil Kanclerz, Karen Livescu, Karl Krauth, Karthik Gopalakrishnan, Katerina Ignatyeva, Katja Markert, Kaustubh D. Dhole, Kevin Gimpel, Kevin Omondi, Kory Mathewson, Kristen Chiafullo, Ksenia Shkaruta, Kumar Shridhar, Kyle McDonell, Kyle Richardson, Laria Reynolds, Leo Gao, Li Zhang, Liam Dugan, Lianhui Qin, Lidia Contreras-Ochando, Louis-Philippe Morency, Luca Moschella, Lucas Lam, Lucy Noble, Ludwig Schmidt, Luheng He, Luis Oliveros Colón, Luke Metz, Lütfi Kerem Şenel, Maarten Bosma, Maarten Sap, Maartje ter Hoeve, Maheen Farooqi, Manaal Faruqui, Mantas Mazeika, Marco Baturan, Marco Marelli, Marco Maru, Maria Jose Ramírez Quintana, Marie Tolkiehn, Mario Giulianelli, Martha Lewis, Martin Potthast, Matthew L. Leavitt, Matthias Hagen, Mátyás Schubert, Medina Orduna Baitemirova, Melody Arnaud, Melvin McElrath, Michael A. Yee, Michael Cohen, Michael Gu, Michael Ivanitskiy, Michael Starritt, Michael Strube, Michał Swędrowski, Michele Bevilacqua, Michihiro Yasunaga, Mihir Kale, Mike Cain, Mimee Xu, Mirac Suzgun, Mitch Walker, Mo Tiwari, Mohit Bansal, Moin Aminnaseri, Mor Geva, Mozhdeh Gheini, Mukund Varma T, Nanyun Peng, Nathan A. Chi, Nayeon Lee, Neta Gur-Ari Krakover, Nicholas Cameron, Nicholas Roberts, Nick Doiron, Nicole Martinez, Nikita Nangia, Niklas Deckers, Niklas Muennighoff, Nitish Shirish Keskar, Niveditha S. Iyer, Noah Constant, Noah Fiedel, Nuan Wen, Oliver Zhang, Omar Agha, Omar Elbaghdadi, Omer Levy, Owain Evans, Pablo Antonio Moreno Casares, Parth Doshi, Pascale Fung, Paul Pu Liang, Paul Vicol, Pegah Alipoormolabashi, Peiyuan Liao, Percy Liang, Peter Chang, Peter Eckersley, Phu Mon Htut, Pinyu Hwang, Piotr Miłkowski, Piyush Patil, Pouya Pezeshkpour, Priti Oli, Qiaozhu Mei, Qing Lyu, Qinlang Chen, Rabin Banjade, Rachel Etta Rudolph, Raefer Gabriel, Rahel Habacker, Ramon Risco, Raphaël Millière, Rhythm Garg, Richard Barnes, Rif A. Saurous, Riku Arakawa, Robbe Raymaekers, Robert Frank, Rohan Sikand, Roman Novak, Roman Sitelew, Ronan LeBras, Rosanne Liu, Rowan Jacobs, Rui Zhang, Ruslan Salakhutdinov, Ryan Chi, Ryan Lee, Ryan Stovall, Ryan Teehan, Rylan Yang, Sahib Singh, Saif M. Mohammad, Sajant Anand, Sam Dillavou, Sam Shleifer, Sam Wiseman, Samuel Gruetter, Samuel R. Bowman, Samuel S. Schoenholz, Sanghyun Han, Sanjeev Kwatra, Sarah A. Rous, Sarik Ghazarian, Sayan Ghosh, Sean Casey, Sebastian Bischoff, Sebastian Gehrmann, Sebastian Schuster, Sepideh Sadeghi, Shadi Hamdan, Sharon Zhou, Shashank Srivastava, Sherry Shi, Shikhar Singh, Shima Asaadi, Shixiang Shane Gu, Shubh Pachchigar, Shubham Toshniwal, Shyam Upadhyay, Shyamolima, Debnath, Siamak Shakeri, Simon Thormeyer, Simone Melzi, Siva Reddy, Sneha Priscilla Makini, Soo-Hwan Lee, Spencer Torene, Sriharsha Hatwar, Stanislas Dehaene, Stefan Divic, Stefano Ermon, Stella Biderman, Stephanie Lin, Stephen Prasad, Steven T. Piantadosi, Stuart M. Shieber, Summer Misherghi, Svetlana Kiritchenko, Swaroop Mishra, Tal Linzen, Tal Schuster, Tao Li, Tao Yu, Tariq Ali, Tatsu Hashimoto, Te-Lin Wu, Théo Desbordes, Theodore Rothschild, Thomas Phan, Tianle Wang, Tiberius Nkinyili, Timo Schick, Timofei Kornev, Titus Tunduny, Tobias Gerstenberg, Trenton Chang, Trishala Neeraj, Tushar Khot, Tyler Shultz, Uri Shaham, Vedant Misra, Vera Demberg, Victoria Nyamai, Vikas Raunak, Vinay Ramasesh, Vinay Uday Prabhu, Vishakh Padmakumar, Vivek Srikumar, William Fedus, William Saunders, William Zhang, Wout Vossen, Xiang Ren, Xiaoyu Tong, Xinran Zhao, Xinyi Wu, Xudong Shen, Yadollah Yaghoobzadeh, Yair Lakretz, Yangqiu Song, Yasaman Bahri, Yejin Choi, Yichi Yang, Yiding Hao, Yifu Chen, Yonatan Belinkov, Yu Hou, Yufang Hou, Yuntao Bai, Zachary Seid, Zhuoye Zhao, Zijian Wang, Zijie J. Wang, ZiRui Wang, Ziyi Wu

BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models.

Common Sense Reasoning Memorization

MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data

1 code implementation ACL 2022 Yilun Zhao, Yunxiang Li, Chenying Li, Rui Zhang

Numerical reasoning over hybrid data containing both textual and tabular content (e. g., financial reports) has recently attracted much attention in the NLP community.

Question Answering

QoE-Aware Resource Allocation for Semantic Communication Networks

no code implementations28 May 2022 Lei Yan, Zhijin Qin, Rui Zhang, Yongzhao Li, Geoffrey Ye Li

Specifically, an approximate measure of semantic entropy is first developed to quantify the semantic information for different tasks, based on which a novel quality-of-experience (QoE) model is proposed.

ES-GNN: Generalizing Graph Neural Networks Beyond Homophily with Edge Splitting

1 code implementation27 May 2022 Jingwei Guo, Kaizhu Huang, Rui Zhang, Xinping Yi

While Graph Neural Networks (GNNs) have achieved enormous success in multiple graph analytical tasks, modern variants mostly rely on the strong inductive bias of homophily.

Denoising Inductive Bias

BARS: Towards Open Benchmarking for Recommender Systems

3 code implementations19 May 2022 Jieming Zhu, Quanyu Dai, Liangcai Su, Rong Ma, Jinyang Liu, Guohao Cai, Xi Xiao, Rui Zhang

Despite significant progress made in both research and practice of recommender systems, to date, there is a lack of a widely-recognized benchmarking standard in this field.

Benchmarking Recommendation Systems

Neural Program Synthesis with Query

no code implementations ICLR 2022 Di Huang, Rui Zhang, Xing Hu, Xishan Zhang, Pengwei Jin, Nan Li, Zidong Du, Qi Guo, Yunji Chen

In this work, we propose a query-based framework that trains a query neural network to generate informative input-output examples automatically and interactively from a large query space.

Program Synthesis

Improving Transferability for Domain Adaptive Detection Transformers

1 code implementation29 Apr 2022 Kaixiong Gong, Shuang Li, Shugang Li, Rui Zhang, Chi Harold Liu, Qiang Chen

We implement the findings and the alignment modules into our adaptation method, and it benchmarks the DETR-style detector on the domain shift settings.

Object Detection Unsupervised Domain Adaptation

Multi-Level Interaction Reranking with User Behavior History

1 code implementation20 Apr 2022 Yunjia Xi, Weiwen Liu, Jieming Zhu, Xilong Zhao, Xinyi Dai, Ruiming Tang, Weinan Zhang, Rui Zhang, Yong Yu

MIR combines low-level cross-item interaction and high-level set-to-list interaction, where we view the candidate items to be reranked as a set and the users' behavior history in chronological order as a list.

Recommendation Systems

Solving The Long-Tailed Problem via Intra- and Inter-Category Balance

no code implementations20 Apr 2022 Renhui Zhang, Tiancheng Lin, Rui Zhang, Yi Xu

Benchmark datasets for visual recognition assume that data is uniformly distributed, while real-world datasets obey long-tailed distribution.

Self Supervised Lesion Recognition For Breast Ultrasound Diagnosis

no code implementations18 Apr 2022 Yuanfan Guo, Canqian Yang, Tiancheng Lin, Chunxiao Li, Rui Zhang, Yi Xu

Since an ultrasound image only describes a partial 2D projection of a 3D lesion, such paradigm ignores the semantic relationship between different views of a lesion, which is inconsistent with the traditional diagnosis where sonographers analyze a lesion from at least two views.

Contrastive Learning

Contrastive Learning with Positive-Negative Frame Mask for Music Representation

no code implementations17 Mar 2022 Dong Yao, Zhou Zhao, Shengyu Zhang, Jieming Zhu, Yudong Zhu, Rui Zhang, Xiuqiang He

We devise a novel contrastive learning objective to accommodate both self-augmented positives/negatives sampled from the same music.

Contrastive Learning Cover song identification +2

An Interpretable Neuro-Symbolic Reasoning Framework for Task-Oriented Dialogue Generation

1 code implementation ACL 2022 Shiquan Yang, Rui Zhang, Sarah Erfani, Jey Han Lau

To obtain a transparent reasoning process, we introduce neuro-symbolic to perform explicit reasoning that justifies model decisions by reasoning chains.

Dialogue Generation Task-Oriented Dialogue Systems

Matrix Completion via Non-Convex Relaxation and Adaptive Correlation Learning

no code implementations4 Mar 2022 Xuelong Li, Hongyuan Zhang, Rui Zhang

We theoretically validate that it is equivalent to the existing matrix completion models.

Matrix Completion

Bridge the Gap between Supervised and Unsupervised Learning for Fine-Grained Classification

no code implementations1 Mar 2022 Jiabao Wang, Yang Li, Xiu-Shen Wei, Hang Li, Zhuang Miao, Rui Zhang

Unsupervised learning technology has caught up with or even surpassed supervised learning technology in general object classification (GOC) and person re-identification (re-ID).

Clustering Contrastive Learning +3

Mining On Alzheimer's Diseases Related Knowledge Graph to Identity Potential AD-related Semantic Triples for Drug Repurposing

no code implementations17 Feb 2022 Yi Nian, Xinyue Hu, Rui Zhang, Jingna Feng, Jingcheng Du, Fang Li, Yong Chen, Cui Tao

The 1, 672, 110 filtered triples were used to train with knowledge graph completion algorithms (i. e., TransE, DistMult, and ComplEx) to predict candidates that might be helpful for AD treatment or prevention.

Graph Mining

Neural Re-ranking in Multi-stage Recommender Systems: A Review

1 code implementation14 Feb 2022 Weiwen Liu, Yunjia Xi, Jiarui Qin, Fei Sun, Bo Chen, Weinan Zhang, Rui Zhang, Ruiming Tang

As the final stage of the multi-stage recommender system (MRS), re-ranking directly affects user experience and satisfaction by rearranging the input ranking lists, and thereby plays a critical role in MRS. With the advances in deep learning, neural re-ranking has become a trending topic and been widely applied in industrial applications.

Recommendation Systems Re-Ranking

Predicting Cancer Treatments Induced Cardiotoxicity of Breast Cancer Patients

no code implementations31 Jan 2022 Sicheng Zhou, Rui Zhang, Anne Blaes, Chetan Shenoy, Gyorgy Simon

After adjusting for baseline differences in cardiovascular health, patients who received chemotherapy or targeted therapy appeared to have higher risk of cardiotoxicity than patients who received radiation therapy.

Generalised Image Outpainting with U-Transformer

1 code implementation27 Jan 2022 Penglei Gao, Xi Yang, Rui Zhang, John Y. Goulermas, Yujie Geng, Yuyao Yan, Kaizhu Huang

In this paper, we develop a novel transformer-based generative adversarial neural network called U-Transformer for generalised image outpainting problem.

Image Outpainting

Target Sensing with Intelligent Reflecting Surface: Architecture and Performance

no code implementations22 Jan 2022 Xiaodan Shao, Changsheng You, Wenyan Ma, Xiaoming Chen, Rui Zhang

Intelligent reflecting surface (IRS) has emerged as a promising technology to reconfigure the radio propagation environment by dynamically controlling wireless signal's amplitude and/or phase via a large number of reflecting elements.

On the Opportunity of Causal Learning in Recommendation Systems: Foundation, Estimation, Prediction and Challenges

no code implementations18 Jan 2022 Peng Wu, Haoxuan Li, yuhao deng, Wenjie Hu, Quanyu Dai, Zhenhua Dong, Jie Sun, Rui Zhang, Xiao-Hua Zhou

Recently, recommender system (RS) based on causal inference has gained much attention in the industrial community, as well as the states of the art performance in many prediction and debiasing tasks.

Causal Inference Recommendation Systems

Resource allocation for text semantic communications

1 code implementation16 Jan 2022 Lei Yan, Zhijin Qin, Rui Zhang, Yongzhao Li, Geoffrey Ye Li

Semantic communications have shown its great potential to improve the transmission reliability, especially in the low signal-to-noise regime.

ISNet: Shape Matters for Infrared Small Target Detection

1 code implementation CVPR 2022 Mingjin Zhang, Rui Zhang, Yuxiang Yang, Haichen Bai, Jing Zhang, Jie Guo

TOAA block calculates the low-level information with attention mechanism in both row and column directions and fuses it with the high-level information to capture the shape characteristic of targets and suppress noises.


Rethinking Influence Functions of Neural Networks in the Over-parameterized Regime

no code implementations15 Dec 2021 Rui Zhang, Shihua Zhang

However, the classic implicit Hessian-vector product (IHVP) method for calculating IF is fragile, and theoretical analysis of IF in the context of neural networks is still lacking.

An Overview of Signal Processing Techniques for RIS/IRS-aided Wireless Systems

no code implementations11 Dec 2021 Cunhua Pan, Gui Zhou, Kangda Zhi, Sheng Hong, Tuo Wu, Yijin Pan, Hong Ren, Marco Di Renzo, A. Lee Swindlehurst, Rui Zhang, Angela Yingjun Zhang

In the past as well as present wireless communication systems, the wireless propagation environment is regarded as an uncontrollable black box that impairs the received signal quality, and its negative impacts are compensated for by relying on the design of various sophisticated transmission/reception schemes.

Feature-based Recognition Framework for Super-resolution Images

no code implementations4 Dec 2021 Jing Hu, Meiqi Zhang, Rui Zhang

In practical application, the performance of recognition network usually decreases when being applied on super-resolution images.


MISS: Multi-Interest Self-Supervised Learning Framework for Click-Through Rate Prediction

no code implementations30 Nov 2021 Wei Guo, Can Zhang, ZhiCheng He, Jiarui Qin, Huifeng Guo, Bo Chen, Ruiming Tang, Xiuqiang He, Rui Zhang

With the help of two novel CNN-based multi-interest extractors, self-supervision signals are discovered with full considerations of different interest representations (point-wise and union-wise), interest dependencies (short-range and long-range), and interest correlations (inter-item and intra-item).

Click-Through Rate Prediction Contrastive Learning +3

AnchorGAE: General Data Clustering via $O(n)$ Bipartite Graph Convolution

no code implementations12 Nov 2021 Hongyuan Zhang, Jiankun Shi, Rui Zhang, Xuelong Li

The core problems mainly come from two aspects: (1) the graph is unavailable in the most clustering scenes so that how to construct high-quality graphs on the non-graph data is usually the most important part; (2) given n samples, the graph-based clustering methods usually consume at least $\mathcal O(n^2)$ time to build graphs and the graph convolution requires nearly $\mathcal O(n^2)$ for a dense graph and $\mathcal O(|\mathcal{E}|)$ for a sparse one with $|\mathcal{E}|$ edges.


Learning Controllable Elements Oriented Representations for Reinforcement Learning

no code implementations29 Sep 2021 Qi Yi, Jiaming Guo, Rui Zhang, Shaohui Peng, Xing Hu, Xishan Zhang, Ke Tang, Zidong Du, Qi Guo, Yunji Chen

Deep Reinforcement Learning (deep RL) has been successfully applied to solve various decision-making problems in recent years.

Decision Making