Search Results for author: Nan Xu

Found 33 papers, 11 papers with code

3D-RPE: Enhancing Long-Context Modeling Through 3D Rotary Position Encoding

no code implementations14 Jun 2024 Xindian Ma, Wenyuan Liu, Peng Zhang, Nan Xu

3D-RPE is an advanced version of the widely used 2D Rotary Position Encoding (RoPE), with two major advantages for modeling long contexts: controllable long-term decay and improved position resolution.

mChartQA: A universal benchmark for multimodal Chart Question Answer based on Vision-Language Alignment and Reasoning

no code implementations2 Apr 2024 Jingxuan Wei, Nan Xu, Guiyong Chang, Yin Luo, Bihui Yu, Ruifeng Guo

In the fields of computer vision and natural language processing, multimodal chart question-answering, especially involving color, structure, and textless charts, poses significant challenges.

Chart Question Answering Language Modelling +1

Monotonic Paraphrasing Improves Generalization of Language Model Prompting

no code implementations24 Mar 2024 Qin Liu, Fei Wang, Nan Xu, Tianyi Yan, Tao Meng, Muhao Chen

In this paper, we propose monotonic paraphrasing (MonoPara), an end-to-end decoding strategy that paraphrases given prompts or instructions into their lower perplexity counterparts based on an ensemble of a paraphrase LM for prompt (or instruction) rewriting, and a target LM (i. e. the prompt or instruction executor) that constrains the generation for lower perplexity.

Language Modelling

YAYI-UIE: A Chat-Enhanced Instruction Tuning Framework for Universal Information Extraction

1 code implementation24 Dec 2023 Xinglin Xiao, Yijie Wang, Nan Xu, Yuqi Wang, Hanxuan Yang, Minzheng Wang, Yin Luo, Lei Wang, Wenji Mao, Daniel Zeng

The difficulty of the information extraction task lies in dealing with the task-specific label schemas and heterogeneous data structures.

UIE

MMA-Diffusion: MultiModal Attack on Diffusion Models

2 code implementations CVPR 2024 Yijun Yang, Ruiyuan Gao, Xiaosen Wang, Tsung-Yi Ho, Nan Xu, Qiang Xu

In recent years, Text-to-Image (T2I) models have seen remarkable advancements, gaining widespread adoption.

Cognitive Overload: Jailbreaking Large Language Models with Overloaded Logical Thinking

no code implementations16 Nov 2023 Nan Xu, Fei Wang, Ben Zhou, Bang Zheng Li, Chaowei Xiao, Muhao Chen

While large language models (LLMs) have demonstrated increasing power, they have also given rise to a wide range of harmful behaviors.

Evaluating Large Language Models on Controlled Generation Tasks

1 code implementation23 Oct 2023 Jiao Sun, Yufei Tian, Wangchunshu Zhou, Nan Xu, Qian Hu, Rahul Gupta, John Frederick Wieting, Nanyun Peng, Xuezhe Ma

While recent studies have looked into the abilities of large language models in various benchmark tasks, including question generation, reading comprehension, multilingual and etc, there have been few studies looking into the controllability of large language models on generation tasks.

Question Generation Question-Generation +2

AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models

2 code implementations3 Oct 2023 Xiaogeng Liu, Nan Xu, Muhao Chen, Chaowei Xiao

In light of these challenges, we intend to answer this question: Can we develop an approach that can automatically generate stealthy jailbreak prompts?

Decision Making

CEO: Corpus-based Open-Domain Event Ontology Induction

no code implementations22 May 2023 Nan Xu, Hongming Zhang, Jianshu Chen

Existing event-centric NLP models often only apply to the pre-defined ontology, which significantly restricts their generalization capabilities.

Look-back Decoding for Open-Ended Text Generation

1 code implementation22 May 2023 Nan Xu, Chunting Zhou, Asli Celikyilmaz, Xuezhe Ma

Given a prefix (context), open-ended generation aims to decode texts that are coherent, which do not abruptly drift from previous topics, and informative, which do not suffer from undesired repetitions.

Story Generation

CAMEL: Curvature-Augmented Manifold Embedding and Learning

no code implementations5 Mar 2023 Nan Xu, Yongming Liu

CAMEL utilizes a topology metric defined on the Riemannian manifold, and a unique Riemannian metric for both distance and curvature to enhance its expressibility.

Computational Efficiency Dimensionality Reduction +1

Does Your Model Classify Entities Reasonably? Diagnosing and Mitigating Spurious Correlations in Entity Typing

1 code implementation25 May 2022 Nan Xu, Fei Wang, Bangzheng Li, Mingtao Dong, Muhao Chen

Due to shortcuts from surface patterns to annotated entity labels and biased training, existing entity typing models are subject to the problem of spurious correlations.

counterfactual Data Augmentation +2

Functional Connectivity of the Brain Across Rodents and Humans

no code implementations10 Nov 2021 Nan Xu, Theodore J. LaGrow, Nmachi Anumba, Azalea Lee, Xiaodi Zhang, Behnaz Yousefi, Yasmine Bassil, Gloria Perrin Clavijo, Vahid Khalilzad Sharghi, Eric Maltbie, Lisa Meyer-Baese, Maysam Nezafati, Wen-Ju Pan, Shella Keilholz

This review begins by examining similarities and differences in anatomical features, acquisition parameters, and preprocessing techniques, as factors that contribute to functional connectivity.

A Multi-scale Time-series Dataset with Benchmark for Machine Learning in Decarbonized Energy Grids

1 code implementation12 Oct 2021 Xiangtian Zheng, Nan Xu, Loc Trinh, Dongqi Wu, Tong Huang, S. Sivaranjani, Yan Liu, Le Xie

The electric grid is a key enabling infrastructure for the ambitious transition towards carbon neutrality as we grapple with climate change.

Time Series Time Series Analysis

AnANet: Modeling Association and Alignment for Cross-modal Correlation Classification

no code implementations2 Sep 2021 Nan Xu, Junyan Wang, Yuan Tian, Ruike Zhang, Wenji Mao

Thus researchers study the definition of cross-modal correlation category and construct various classification systems and predictive models.

Classification

A Direct Slip Ratio Estimation Method based on an Intelligent Tire and Machine Learning

no code implementations9 Jun 2021 Nan Xu, Zepeng Tang, Hassan Askari, Jianfeng Zhou, Amir Khajepour

The proposed estimation model is able to estimate the slip ratio continuously and stably using only the acceleration from the intelligent tire system, and the estimated slip ratio range can reach 30%.

Autonomous Vehicles BIG-bench Machine Learning

MIMIC-IF: Interpretability and Fairness Evaluation of Deep Learning Models on MIMIC-IV Dataset

no code implementations12 Feb 2021 Chuizheng Meng, Loc Trinh, Nan Xu, Yan Liu

The recent release of large-scale healthcare datasets has greatly propelled the research of data-driven deep learning models for healthcare applications.

Fairness Feature Importance +1

An Examination of Preference-based Reinforcement Learning for Treatment Recommendation

no code implementations1 Jan 2021 Nan Xu, Nitin Kamra, Yan Liu

Treatment recommendation is a complex multi-faceted problem with many conflicting objectives, e. g., optimizing the survival rate (or expected lifetime), mitigating negative impacts, reducing financial expenses and time costs, avoiding over-treatment, etc.

reinforcement-learning Reinforcement Learning (RL)

Differentially Private Adversarial Robustness Through Randomized Perturbations

no code implementations27 Sep 2020 Nan Xu, Oluwaseyi Feyisetan, Abhinav Aggarwal, Zekun Xu, Nathanael Teissier

Deep Neural Networks, despite their great success in diverse domains, are provably sensitive to small perturbations on correctly classified examples and lead to erroneous predictions.

Adversarial Robustness Semantic Similarity +1

Lateral Force Prediction using Gaussian Process Regression for Intelligent Tire Systems

no code implementations25 Sep 2020 Bruno Henrique Groenner Barbosa, Nan Xu, Hassan Askari, Amir Khajepour

It is delineated that the proposed intelligent tire system can provide reliable information about the tire-road interactions even in the case of high slip angles.

GPR regression

Reasoning with Multimodal Sarcastic Tweets via Modeling Cross-Modality Contrast and Semantic Association

no code implementations ACL 2020 Nan Xu, Zhixiong Zeng, Wenji Mao

In multimodal context, sarcasm is no longer a pure linguistic phenomenon, and due to the nature of social media short text, the opposite is more often manifested via cross-modality expressions.

Relation Relation Network +1

Modeling Conversation Structure and Temporal Dynamics for Jointly Predicting Rumor Stance and Veracity

no code implementations IJCNLP 2019 Penghui Wei, Nan Xu, Wenji Mao

The bottom component of our framework classifies the stances of tweets in a conversation discussing a rumor via modeling the structural property based on a novel graph convolutional network.

Multi-Task Learning Stance Classification

VASPKIT: A User-friendly Interface Facilitating High-throughput Computing and Analysis Using VASP Code

1 code implementation22 Aug 2019 Vei Wang, Nan Xu, Jin Cheng Liu, Gang Tang, Wen-Tong Geng

The executable versions of VASPKIT and the related examples, together with the tutorials, are available in its official website vaspkit. com.

Materials Science

CoLight: Learning Network-level Cooperation for Traffic Signal Control

4 code implementations11 May 2019 Hua Wei, Nan Xu, Huichu Zhang, Guanjie Zheng, Xinshi Zang, Chacha Chen, Wei-Nan Zhang, Yanmin Zhu, Kai Xu, Zhenhui Li

To enable cooperation of traffic signals, in this paper, we propose a model, CoLight, which uses graph attentional networks to facilitate communication.

Multi-agent Reinforcement Learning

Joint Adaptive Neighbours and Metric Learning for Multi-view Subspace Clustering

no code implementations12 Sep 2017 Nan Xu, Yanqing Guo, Jiujun Wang, Xiangyang Luo, Ran He

In this method, we use the subspace representations of different views to adaptively learn a consensus similarity matrix, uncovering the subspace structure and avoiding noisy nature of original data.

Clustering Metric Learning +2

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