Search Results for author: Zihan Wang

Found 92 papers, 52 papers with code

“Average” Approximates “First Principal Component”? An Empirical Analysis on Representations from Neural Language Models

no code implementations EMNLP 2021 Zihan Wang, chengyu dong, Jingbo Shang

In this paper, we present an empirical property of these representations—”average” approximates “first principal component”.

DeepSeek-V2: A Strong, Economical, and Efficient Mixture-of-Experts Language Model

1 code implementation7 May 2024 DeepSeek-AI, Aixin Liu, Bei Feng, Bin Wang, Bingxuan Wang, Bo Liu, Chenggang Zhao, Chengqi Dengr, Chong Ruan, Damai Dai, Daya Guo, Dejian Yang, Deli Chen, Dongjie Ji, Erhang Li, Fangyun Lin, Fuli Luo, Guangbo Hao, Guanting Chen, Guowei Li, H. Zhang, Hanwei Xu, Hao Yang, Haowei Zhang, Honghui Ding, Huajian Xin, Huazuo Gao, Hui Li, Hui Qu, J. L. Cai, Jian Liang, JianZhong Guo, Jiaqi Ni, Jiashi Li, Jin Chen, Jingyang Yuan, Junjie Qiu, Junxiao Song, Kai Dong, Kaige Gao, Kang Guan, Lean Wang, Lecong Zhang, Lei Xu, Leyi Xia, Liang Zhao, Liyue Zhang, Meng Li, Miaojun Wang, Mingchuan Zhang, Minghua Zhang, Minghui Tang, Mingming Li, Ning Tian, Panpan Huang, Peiyi Wang, Peng Zhang, Qihao Zhu, Qinyu Chen, Qiushi Du, R. J. Chen, R. L. Jin, Ruiqi Ge, Ruizhe Pan, Runxin Xu, Ruyi Chen, S. S. Li, Shanghao Lu, Shangyan Zhou, Shanhuang Chen, Shaoqing Wu, Shengfeng Ye, Shirong Ma, Shiyu Wang, Shuang Zhou, Shuiping Yu, Shunfeng Zhou, Size Zheng, T. Wang, Tian Pei, Tian Yuan, Tianyu Sun, W. L. Xiao, Wangding Zeng, Wei An, Wen Liu, Wenfeng Liang, Wenjun Gao, Wentao Zhang, X. Q. Li, Xiangyue Jin, Xianzu Wang, Xiao Bi, Xiaodong Liu, Xiaohan Wang, Xiaojin Shen, Xiaokang Chen, Xiaosha Chen, Xiaotao Nie, Xiaowen Sun, Xiaoxiang Wang, Xin Liu, Xin Xie, Xingkai Yu, Xinnan Song, Xinyi Zhou, Xinyu Yang, Xuan Lu, Xuecheng Su, Y. Wu, Y. K. Li, Y. X. Wei, Y. X. Zhu, Yanhong Xu, Yanping Huang, Yao Li, Yao Zhao, Yaofeng Sun, Yaohui Li, Yaohui Wang, Yi Zheng, Yichao Zhang, Yiliang Xiong, Yilong Zhao, Ying He, Ying Tang, Yishi Piao, Yixin Dong, Yixuan Tan, Yiyuan Liu, Yongji Wang, Yongqiang Guo, Yuchen Zhu, Yuduan Wang, Yuheng Zou, Yukun Zha, Yunxian Ma, Yuting Yan, Yuxiang You, Yuxuan Liu, Z. Z. Ren, Zehui Ren, Zhangli Sha, Zhe Fu, Zhen Huang, Zhen Zhang, Zhenda Xie, Zhewen Hao, Zhihong Shao, Zhiniu Wen, Zhipeng Xu, Zhongyu Zhang, Zhuoshu Li, Zihan Wang, Zihui Gu, Zilin Li, Ziwei Xie

MLA guarantees efficient inference through significantly compressing the Key-Value (KV) cache into a latent vector, while DeepSeekMoE enables training strong models at an economical cost through sparse computation.

Language Modelling Reinforcement Learning (RL)

Tele-FLM Technical Report

no code implementations25 Apr 2024 Xiang Li, Yiqun Yao, Xin Jiang, Xuezhi Fang, Chao Wang, Xinzhang Liu, Zihan Wang, Yu Zhao, Xin Wang, Yuyao Huang, Shuangyong Song, Yongxiang Li, Zheng Zhang, Bo Zhao, Aixin Sun, Yequan Wang, Zhongjiang He, Zhongyuan Wang, Xuelong Li, Tiejun Huang

Large language models (LLMs) have showcased profound capabilities in language understanding and generation, facilitating a wide array of applications.

Language Modelling Large Language Model

Learn from Failure: Fine-Tuning LLMs with Trial-and-Error Data for Intuitionistic Propositional Logic Proving

no code implementations10 Apr 2024 Chenyang An, Zhibo Chen, Qihao Ye, Emily First, Letian Peng, Jiayun Zhang, Zihan Wang, Sorin Lerner, Jingbo Shang

Recent advances in Automated Theorem Proving have shown the effectiveness of leveraging a (large) language model that generates tactics (i. e. proof steps) to search through proof states.

Automated Theorem Proving Language Modelling +1

Multi-scale Dynamic and Hierarchical Relationship Modeling for Facial Action Units Recognition

1 code implementation9 Apr 2024 Zihan Wang, Siyang Song, Cheng Luo, Songhe Deng, Weicheng Xie, Linlin Shen

Human facial action units (AUs) are mutually related in a hierarchical manner, as not only they are associated with each other in both spatial and temporal domains but also AUs located in the same/close facial regions show stronger relationships than those of different facial regions.

AirShot: Efficient Few-Shot Detection for Autonomous Exploration

2 code implementations7 Apr 2024 Zihan Wang, Bowen Li, Chen Wang, Sebastian Scherer

Few-shot object detection has drawn increasing attention in the field of robotic exploration, where robots are required to find unseen objects with a few online provided examples.

Few-Shot Object Detection object-detection

ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline

1 code implementation3 Apr 2024 Yifan Xu, Xiao Liu, Xinghan Liu, Zhenyu Hou, Yueyan Li, Xiaohan Zhang, Zihan Wang, Aohan Zeng, Zhengxiao Du, Wenyi Zhao, Jie Tang, Yuxiao Dong

Large language models (LLMs) have shown excellent mastering of human language, but still struggle in real-world applications that require mathematical problem-solving.

Math

Lookahead Exploration with Neural Radiance Representation for Continuous Vision-Language Navigation

1 code implementation2 Apr 2024 Zihan Wang, Xiangyang Li, Jiahao Yang, Yeqi Liu, Junjie Hu, Ming Jiang, Shuqiang Jiang

Vision-and-language navigation (VLN) enables the agent to navigate to a remote location following the natural language instruction in 3D environments.

Navigate Vision and Language Navigation +1

MetaIE: Distilling a Meta Model from LLM for All Kinds of Information Extraction Tasks

1 code implementation30 Mar 2024 Letian Peng, Zilong Wang, Feng Yao, Zihan Wang, Jingbo Shang

We construct the distillation dataset via sampling sentences from language model pre-training datasets (e. g., OpenWebText in our implementation) and prompting an LLM to identify the typed spans of "important information".

Language Modelling named-entity-recognition +2

Is Mamba Effective for Time Series Forecasting?

1 code implementation17 Mar 2024 Zihan Wang, Fanheng Kong, Shi Feng, Ming Wang, Xiaocui Yang, Han Zhao, Daling Wang, Yifei Zhang

For TSF tasks, these characteristics enable Mamba to comprehend hidden patterns as the Transformer and reduce computational overhead compared to the Transformer.

Computational Efficiency Time Series +1

Towards Robustness and Diversity: Continual Learning in Dialog Generation with Text-Mixup and Batch Nuclear-Norm Maximization

no code implementations16 Mar 2024 Zihan Wang, Jiayu Xiao, Mengxiang Li, Zhongjiang He, Yongxiang Li, Chao Wang, Shuangyong Song

In our dynamic world where data arrives in a continuous stream, continual learning enables us to incrementally add new tasks/domains without the need to retrain from scratch.

Continual Learning Data Augmentation +1

Learning with Noisy Foundation Models

no code implementations11 Mar 2024 Hao Chen, Jindong Wang, Zihan Wang, Ran Tao, Hongxin Wei, Xing Xie, Masashi Sugiyama, Bhiksha Raj

Foundation models are usually pre-trained on large-scale datasets and then adapted to downstream tasks through tuning.

Utilizing Local Hierarchy with Adversarial Training for Hierarchical Text Classification

1 code implementation29 Feb 2024 Zihan Wang, Peiyi Wang, Houfeng Wang

Hierarchical text classification (HTC) is a challenging subtask of multi-label classification due to its complex taxonomic structure.

Multi-Label Classification text-classification +1

VN Network: Embedding Newly Emerging Entities with Virtual Neighbors

no code implementations21 Feb 2024 Yongquan He, Zihan Wang, Peng Zhang, Zhaopeng Tu, Zhaochun Ren

To address this issue, recent works apply the graph neural network on the existing neighbors of the unseen entities.

Knowledge Graph Completion Network Embedding

Data Reconstruction Attacks and Defenses: A Systematic Evaluation

no code implementations13 Feb 2024 Sheng Liu, Zihan Wang, Qi Lei

In this work, we propose a strong reconstruction attack in the setting of federated learning.

Federated Learning Reconstruction Attack

Multi-step Problem Solving Through a Verifier: An Empirical Analysis on Model-induced Process Supervision

no code implementations5 Feb 2024 Zihan Wang, Yunxuan Li, Yuexin Wu, Liangchen Luo, Le Hou, Hongkun Yu, Jingbo Shang

Process supervision, using a trained verifier to evaluate the intermediate steps generated by reasoner, has demonstrated significant improvements in multi-step problem solving.

GSM8K Math

SciGLM: Training Scientific Language Models with Self-Reflective Instruction Annotation and Tuning

1 code implementation15 Jan 2024 Dan Zhang, Ziniu Hu, Sining Zhoubian, Zhengxiao Du, Kaiyu Yang, Zihan Wang, Yisong Yue, Yuxiao Dong, Jie Tang

To bridge these gaps, we introduce SciGLM, a suite of scientific language models able to conduct college-level scientific reasoning.

Math Mathematical Reasoning

Class-Imbalanced Semi-Supervised Learning for Large-Scale Point Cloud Semantic Segmentation via Decoupling Optimization

no code implementations13 Jan 2024 Mengtian Li, Shaohui Lin, Zihan Wang, Yunhang Shen, Baochang Zhang, Lizhuang Ma

Semi-supervised learning (SSL), thanks to the significant reduction of data annotation costs, has been an active research topic for large-scale 3D scene understanding.

Pseudo Label Representation Learning +2

CogAgent: A Visual Language Model for GUI Agents

1 code implementation14 Dec 2023 Wenyi Hong, Weihan Wang, Qingsong Lv, Jiazheng Xu, Wenmeng Yu, Junhui Ji, Yan Wang, Zihan Wang, Yuxuan Zhang, Juanzi Li, Bin Xu, Yuxiao Dong, Ming Ding, Jie Tang

People are spending an enormous amount of time on digital devices through graphical user interfaces (GUIs), e. g., computer or smartphone screens.

Language Modelling Visual Question Answering

Multi-Defendant Legal Judgment Prediction via Hierarchical Reasoning

1 code implementation10 Dec 2023 Yougang Lyu, Jitai Hao, Zihan Wang, Kai Zhao, Shen Gao, Pengjie Ren, Zhumin Chen, Fang Wang, Zhaochun Ren

Multiple defendants in a criminal fact description generally exhibit complex interactions, and cannot be well handled by existing Legal Judgment Prediction (LJP) methods which focus on predicting judgment results (e. g., law articles, charges, and terms of penalty) for single-defendant cases.

Less than One-shot: Named Entity Recognition via Extremely Weak Supervision

1 code implementation6 Nov 2023 Letian Peng, Zihan Wang, Jingbo Shang

We study the named entity recognition (NER) problem under the extremely weak supervision (XWS) setting, where only one example entity per type is given in a context-free way.

named-entity-recognition Named Entity Recognition +1

EmojiLM: Modeling the New Emoji Language

1 code implementation3 Nov 2023 Letian Peng, Zilong Wang, Hang Liu, Zihan Wang, Jingbo Shang

With the rapid development of the internet, online social media welcomes people with different backgrounds through its diverse content.

Language Modelling Large Language Model

Autonomous Robotic Reinforcement Learning with Asynchronous Human Feedback

no code implementations31 Oct 2023 Max Balsells, Marcel Torne, Zihan Wang, Samedh Desai, Pulkit Agrawal, Abhishek Gupta

We evaluate this system on a suite of robotic tasks in simulation and demonstrate its effectiveness at learning behaviors both in simulation and the real world.

reinforcement-learning Self-Supervised Learning

ToxicChat: Unveiling Hidden Challenges of Toxicity Detection in Real-World User-AI Conversation

no code implementations26 Oct 2023 Zi Lin, Zihan Wang, Yongqi Tong, Yangkun Wang, Yuxin Guo, Yujia Wang, Jingbo Shang

This benchmark contains the rich, nuanced phenomena that can be tricky for current toxicity detection models to identify, revealing a significant domain difference compared to social media content.

Chatbot

Evoke: Evoking Critical Thinking Abilities in LLMs via Reviewer-Author Prompt Editing

no code implementations20 Oct 2023 Xinyu Hu, Pengfei Tang, Simiao Zuo, Zihan Wang, Bowen Song, Qiang Lou, Jian Jiao, Denis Charles

In Evoke, there are two instances of a same LLM: one as a reviewer (LLM-Reviewer), it scores the current prompt; the other as an author (LLM-Author), it edits the prompt by considering the edit history and the reviewer's feedback.

Logical Fallacy Detection

Generalizing Few-Shot Named Entity Recognizers to Unseen Domains with Type-Related Features

1 code implementation15 Oct 2023 Zihan Wang, Ziqi Zhao, Zhumin Chen, Pengjie Ren, Maarten de Rijke, Zhaochun Ren

To address this limitation, recent studies enable generalization to an unseen target domain with only a few labeled examples using data augmentation techniques.

Data Augmentation few-shot-ner +5

Robust and Interpretable Medical Image Classifiers via Concept Bottleneck Models

no code implementations4 Oct 2023 An Yan, Yu Wang, Yiwu Zhong, Zexue He, Petros Karypis, Zihan Wang, chengyu dong, Amilcare Gentili, Chun-Nan Hsu, Jingbo Shang, Julian McAuley

Medical image classification is a critical problem for healthcare, with the potential to alleviate the workload of doctors and facilitate diagnoses of patients.

Image Classification Language Modelling +1

MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback

1 code implementation19 Sep 2023 Xingyao Wang, Zihan Wang, Jiateng Liu, Yangyi Chen, Lifan Yuan, Hao Peng, Heng Ji

However, current evaluation protocols often emphasize benchmark performance with single-turn exchanges, neglecting the nuanced interactions among the user, LLMs, and external tools, while also underestimating the importance of natural language feedback from users.

Decision Making

GridMM: Grid Memory Map for Vision-and-Language Navigation

1 code implementation ICCV 2023 Zihan Wang, Xiangyang Li, Jiahao Yang, Yeqi Liu, Shuqiang Jiang

Vision-and-language navigation (VLN) enables the agent to navigate to a remote location following the natural language instruction in 3D environments.

Navigate Vision and Language Navigation

Breadcrumbs to the Goal: Goal-Conditioned Exploration from Human-in-the-Loop Feedback

1 code implementation20 Jul 2023 Marcel Torne, Max Balsells, Zihan Wang, Samedh Desai, Tao Chen, Pulkit Agrawal, Abhishek Gupta

This procedure can leverage noisy, asynchronous human feedback to learn policies with no hand-crafted reward design or exploration bonuses.

Decision Making reinforcement-learning +1

BPKD: Boundary Privileged Knowledge Distillation For Semantic Segmentation

1 code implementation13 Jun 2023 Liyang Liu, Zihan Wang, Minh Hieu Phan, BoWen Zhang, Jinchao Ge, Yifan Liu

Current knowledge distillation approaches in semantic segmentation tend to adopt a holistic approach that treats all spatial locations equally.

Knowledge Distillation Segmentation +1

RETA-LLM: A Retrieval-Augmented Large Language Model Toolkit

1 code implementation8 Jun 2023 Jiongnan Liu, Jiajie Jin, Zihan Wang, Jiehan Cheng, Zhicheng Dou, Ji-Rong Wen

To support research in this area and facilitate the development of retrieval-augmented LLM systems, we develop RETA-LLM, a {RET}reival-{A}ugmented LLM toolkit.

Answer Generation Fact Checking +5

Implicit bias of SGD in $L_{2}$-regularized linear DNNs: One-way jumps from high to low rank

no code implementations25 May 2023 Zihan Wang, Arthur Jacot

The $L_{2}$-regularized loss of Deep Linear Networks (DLNs) with more than one hidden layers has multiple local minima, corresponding to matrices with different ranks.

Matrix Completion

Deep Neural Networks in Video Human Action Recognition: A Review

no code implementations25 May 2023 Zihan Wang, Yang Yang, Zhi Liu, Yifan Zheng

Our current related research addresses multiple novel proposed research works and compares their advantages and disadvantages between the derived deep learning frameworks rather than machine learning frameworks.

Action Recognition Optical Flow Estimation +1

ClusterLLM: Large Language Models as a Guide for Text Clustering

1 code implementation24 May 2023 Yuwei Zhang, Zihan Wang, Jingbo Shang

First, we prompt ChatGPT for insights on clustering perspective by constructing hard triplet questions <does A better correspond to B than C>, where A, B and C are similar data points that belong to different clusters according to small embedder.

Clustering Language Modelling +2

Debiasing Made State-of-the-art: Revisiting the Simple Seed-based Weak Supervision for Text Classification

1 code implementation24 May 2023 chengyu dong, Zihan Wang, Jingbo Shang

We show that the limited performance of seed matching is largely due to the label bias injected by the simple seed-match rule, which prevents the classifier from learning reliable confidence for selecting high-quality pseudo-labels.

text-classification Text Classification

Goal-Driven Explainable Clustering via Language Descriptions

1 code implementation23 May 2023 Zihan Wang, Jingbo Shang, Ruiqi Zhong

We propose a new task formulation, "Goal-Driven Clustering with Explanations" (GoalEx), which represents both the goal and the explanations as free-form language descriptions.

Clustering Language Modelling

A Benchmark on Extremely Weakly Supervised Text Classification: Reconcile Seed Matching and Prompting Approaches

1 code implementation22 May 2023 Zihan Wang, Tianle Wang, Dheeraj Mekala, Jingbo Shang

Etremely Weakly Supervised Text Classification (XWS-TC) refers to text classification based on minimal high-level human guidance, such as a few label-indicative seed words or classification instructions.

Benchmarking text-classification +1

WOT-Class: Weakly Supervised Open-world Text Classification

1 code implementation21 May 2023 Tianle Wang, Zihan Wang, Weitang Liu, Jingbo Shang

State-of-the-art weakly supervised text classification methods, while significantly reduced the required human supervision, still requires the supervision to cover all the classes of interest.

Image Classification text-classification +1

Dual-Granularity Contrastive Learning for Session-based Recommendation

no code implementations18 Apr 2023 Zihan Wang, Gang Wu, Haotong Wang

At factor-level, we employ Disentangled Representation Learning to obtain finer-grained data(e. g. factor-level embeddings), with which we can construct factor-level convolution channels.

Contrastive Learning Data Augmentation +2

CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Evaluations on HumanEval-X

2 code implementations30 Mar 2023 Qinkai Zheng, Xiao Xia, Xu Zou, Yuxiao Dong, Shan Wang, Yufei Xue, Zihan Wang, Lei Shen, Andi Wang, Yang Li, Teng Su, Zhilin Yang, Jie Tang

Large pre-trained code generation models, such as OpenAI Codex, can generate syntax- and function-correct code, making the coding of programmers more productive and our pursuit of artificial general intelligence closer.

Code Generation

Spatio-Temporal AU Relational Graph Representation Learning For Facial Action Units Detection

1 code implementation19 Mar 2023 Zihan Wang, Siyang Song, Cheng Luo, Yuzhi Zhou, shiling Wu, Weicheng Xie, Linlin Shen

This paper presents our Facial Action Units (AUs) detection submission to the fifth Affective Behavior Analysis in-the-wild Competition (ABAW).

Graph Learning Graph Representation Learning

PiMAE: Point Cloud and Image Interactive Masked Autoencoders for 3D Object Detection

1 code implementation CVPR 2023 Anthony Chen, Kevin Zhang, Renrui Zhang, Zihan Wang, Yuheng Lu, Yandong Guo, Shanghang Zhang

Masked Autoencoders learn strong visual representations and achieve state-of-the-art results in several independent modalities, yet very few works have addressed their capabilities in multi-modality settings.

3D Object Detection Decoder +3

Commentary Generation from Data Records of Multiplayer Strategy Esports Game

no code implementations21 Dec 2022 Zihan Wang, Naoki Yoshinaga

In this study, we therefore introduce the task of generating game commentaries from esports' data records.

Data-to-Text Generation Decoder

Reconstructing Training Data from Model Gradient, Provably

no code implementations7 Dec 2022 Zihan Wang, Jason D. Lee, Qi Lei

Understanding when and how much a model gradient leaks information about the training sample is an important question in privacy.

Federated Learning Tensor Decomposition

Multilingual Speech Emotion Recognition With Multi-Gating Mechanism and Neural Architecture Search

no code implementations31 Oct 2022 Zihan Wang, Qi Meng, HaiFeng Lan, Xinrui Zhang, Kehao Guo, Akshat Gupta

While Speech Emotion Recognition (SER) is a common application for popular languages, it continues to be a problem for low-resourced languages, i. e., languages with no pretrained speech-to-text recognition models.

Neural Architecture Search Speech Emotion Recognition

WavSpA: Wavelet Space Attention for Boosting Transformers' Long Sequence Learning Ability

no code implementations5 Oct 2022 Yufan Zhuang, Zihan Wang, Fangbo Tao, Jingbo Shang

Recent works show that learning attention in the Fourier space can improve the long sequence learning capability of Transformers.

M^4I: Multi-modal Models Membership Inference

1 code implementation15 Sep 2022 Pingyi Hu, Zihan Wang, Ruoxi Sun, Hu Wang, Minhui Xue

To achieve this, we propose Multi-modal Models Membership Inference (M^4I) with two attack methods to infer the membership status, named metric-based (MB) M^4I and feature-based (FB) M^4I, respectively.

Image Captioning Inference Attack +2

CV 3315 Is All You Need : Semantic Segmentation Competition

1 code implementation25 Jun 2022 Akide Liu, Zihan Wang

This competition focus on Urban-Sense Segmentation based on the vehicle camera view.

Decoder Segmentation +1

Debiasing Learning for Membership Inference Attacks Against Recommender Systems

1 code implementation24 Jun 2022 Zihan Wang, Na Huang, Fei Sun, Pengjie Ren, Zhumin Chen, Hengliang Luo, Maarten de Rijke, Zhaochun Ren

To address the above limitations, we propose a Debiasing Learning for Membership Inference Attacks against recommender systems (DL-MIA) framework that has four main components: (1) a difference vector generator, (2) a disentangled encoder, (3) a weight estimator, and (4) an attack model.

Recommendation Systems

Formulating Few-shot Fine-tuning Towards Language Model Pre-training: A Pilot Study on Named Entity Recognition

1 code implementation24 May 2022 Zihan Wang, Kewen Zhao, Zilong Wang, Jingbo Shang

Fine-tuning pre-trained language models has recently become a common practice in building NLP models for various tasks, especially few-shot tasks.

Few-shot NER Language Modelling +2

WeDef: Weakly Supervised Backdoor Defense for Text Classification

no code implementations24 May 2022 Lesheng Jin, Zihan Wang, Jingbo Shang

Inspired by this observation, in WeDef, we define the reliability of samples based on whether the predictions of the weak classifier agree with their labels in the poisoned training set.

backdoor defense text-classification +1

Beyond the Granularity: Multi-Perspective Dialogue Collaborative Selection for Dialogue State Tracking

1 code implementation ACL 2022 Jinyu Guo, Kai Shuang, Jijie Li, Zihan Wang, Yixuan Liu

However, no matter how the dialogue history is used, each existing model uses its own consistent dialogue history during the entire state tracking process, regardless of which slot is updated.

Dialogue State Tracking

Effectively Using Long and Short Sessions for Multi-Session-based Recommendations

no code implementations9 May 2022 Zihan Wang, Gang Wu, Yan Wang

The RNN often used in previous work is not suitable to process short sessions, because RNN only focuses on the sequential relationship, which we find is not the only relationship between items in short sessions.

Session-Based Recommendations

HPT: Hierarchy-aware Prompt Tuning for Hierarchical Text Classification

1 code implementation28 Apr 2022 Zihan Wang, Peiyi Wang, Tianyu Liu, Binghuai Lin, Yunbo Cao, Zhifang Sui, Houfeng Wang

However, in this paradigm, there exists a huge gap between the classification tasks with sophisticated label hierarchy and the masked language model (MLM) pretraining tasks of PLMs and thus the potentials of PLMs can not be fully tapped.

Language Modelling Multi-Label Classification +2

Weakly Supervised Correspondence Learning

no code implementations2 Mar 2022 Zihan Wang, Zhangjie Cao, Yilun Hao, Dorsa Sadigh

Correspondence learning is a fundamental problem in robotics, which aims to learn a mapping between state, action pairs of agents of different dynamics or embodiments.

Learning from Imperfect Demonstrations via Adversarial Confidence Transfer

no code implementations7 Feb 2022 Zhangjie Cao, Zihan Wang, Dorsa Sadigh

Existing learning from demonstration algorithms usually assume access to expert demonstrations.

An Interactive Visualization Tool for Understanding Active Learning

1 code implementation9 Nov 2021 Zihan Wang, Jialin Lu, Oliver Snow, Martin Ester

Despite recent progress in artificial intelligence and machine learning, many state-of-the-art methods suffer from a lack of explainability and transparency.

Active Learning BIG-bench Machine Learning

Membership Inference Attacks Against Recommender Systems

1 code implementation16 Sep 2021 Minxing Zhang, Zhaochun Ren, Zihan Wang, Pengjie Ren, Zhumin Chen, Pengfei Hu, Yang Zhang

In this paper, we make the first attempt on quantifying the privacy leakage of recommender systems through the lens of membership inference.

Recommendation Systems

Dual Slot Selector via Local Reliability Verification for Dialogue State Tracking

1 code implementation ACL 2021 Jinyu Guo, Kai Shuang, Jijie Li, Zihan Wang

However, the overwhelming majority of the slots in each turn should simply inherit the slot values from the previous turn.

Dialogue State Tracking

Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganography

no code implementations20 Jul 2021 Zihan Wang, Olivia Byrnes, Hu Wang, Ruoxi Sun, Congbo Ma, Huaming Chen, Qi Wu, Minhui Xue

The advancement of secure communication and identity verification fields has significantly increased through the use of deep learning techniques for data hiding.

UCPhrase: Unsupervised Context-aware Quality Phrase Tagging

2 code implementations28 May 2021 Xiaotao Gu, Zihan Wang, Zhenyu Bi, Yu Meng, Liyuan Liu, Jiawei Han, Jingbo Shang

Training a conventional neural tagger based on silver labels usually faces the risk of overfitting phrase surface names.

Keyphrase Extraction Language Modelling +3

XCrossNet: Feature Structure-Oriented Learning for Click-Through Rate Prediction

1 code implementation22 Apr 2021 Runlong Yu, Yuyang Ye, Qi Liu, Zihan Wang, Chunfeng Yang, Yucheng Hu, Enhong Chen

Motivated by this, we propose a novel Extreme Cross Network, abbreviated XCrossNet, which aims at learning dense and sparse feature interactions in an explicit manner.

Click-Through Rate Prediction Feature Engineering +1

"Average" Approximates "First Principal Component"? An Empirical Analysis on Representations from Neural Language Models

1 code implementation18 Apr 2021 Zihan Wang, chengyu dong, Jingbo Shang

In this paper, we present an empirical property of these representations -- "average" approximates "first principal component".

Low-Power Wireless Wearable ECG Monitoring Chestbelt Based on Ferroelectric Microprocessor

no code implementations6 Nov 2020 Zhendong Ai, Zihan Wang, Wei Cui

The ECG monitoring device, abbreviated as ECGM, is designed based on ferroelectric microprocessor which provides ultra-low power consumption and contains four parts-MCU, BLE, Sensors and Power.

Emora: An Inquisitive Social Chatbot Who Cares For You

no code implementations10 Sep 2020 Sarah E. Finch, James D. Finch, Ali Ahmadvand, Ingyu, Choi, Xiangjue Dong, Ruixiang Qi, Harshita Sahijwani, Sergey Volokhin, Zihan Wang, ZiHao Wang, Jinho D. Choi

Inspired by studies on the overwhelming presence of experience-sharing in human-human conversations, Emora, the social chatbot developed by Emory University, aims to bring such experience-focused interaction to the current field of conversational AI.

Chatbot intent-classification +1

Cross-Lingual Ability of Multilingual BERT: An Empirical Study

no code implementations ICLR 2020 Karthikeyan K, Zihan Wang, Stephen Mayhew, Dan Roth

Recent work has exhibited the surprising cross-lingual abilities of multilingual BERT (M-BERT) -- surprising since it is trained without any cross-lingual objective and with no aligned data.

named-entity-recognition Named Entity Recognition +2

Discriminative Topic Mining via Category-Name Guided Text Embedding

1 code implementation20 Aug 2019 Yu Meng, Jiaxin Huang, Guangyuan Wang, Zihan Wang, Chao Zhang, Yu Zhang, Jiawei Han

We propose a new task, discriminative topic mining, which leverages a set of user-provided category names to mine discriminative topics from text corpora.

Document Classification General Classification +3

Raw-to-End Name Entity Recognition in Social Media

1 code implementation14 Aug 2019 Liyuan Liu, Zihan Wang, Jingbo Shang, Dandong Yin, Heng Ji, Xiang Ren, Shaowen Wang, Jiawei Han

Our model neither requires the conversion from character sequences to word sequences, nor assumes tokenizer can correctly detect all word boundaries.

named-entity-recognition Named Entity Recognition +1

ECG Identification under Exercise and Rest Situations via Various Learning Methods

no code implementations11 May 2019 Zihan Wang, Yaoguang Li, Wei Cui

By applying various existing learning methods to our ECG dataset, we find that current methods which can well support the identification of individuals under rests, do not suffice to present satisfying ECGID performance under exercise situations, therefore exposing the deficiency of existing ECG identification methods.

A Data-Efficient Framework for Training and Sim-to-Real Transfer of Navigation Policies

no code implementations11 Oct 2018 Homanga Bharadhwaj, Zihan Wang, Yoshua Bengio, Liam Paull

Learning effective visuomotor policies for robots purely from data is challenging, but also appealing since a learning-based system should not require manual tuning or calibration.

Meta-Learning

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