b'Wenxuan Zhou'

research

∙ 05/28/2023

Robust Natural Language Understanding with Residual Attention Debiasing

Natural language understanding (NLU) models often suffer from unintended...

0 Fei Wang, et al. ∙

research

∙ 05/24/2023

Getting Sick After Seeing a Doctor? Diagnosing and Mitigating Knowledge Conflicts in Event Temporal Reasoning

Event temporal reasoning aims at identifying the temporal relations betw...

0 Tianqing Fang, et al. ∙

research

∙ 05/24/2023

A Causal View of Entity Bias in (Large) Language Models

Entity bias widely affects pretrained (large) language models, causing t...

0 Fei Wang, et al. ∙

research

∙ 05/22/2023

EntRED: Benchmarking Relation Extraction with Fewer Shortcuts

Entity names play an effective role in relation extraction (RE) and ofte...

0 Yiwei Wang, et al. ∙

research

∙ 05/06/2023

Learning Hybrid Actor-Critic Maps for 6D Non-Prehensile Manipulation

Manipulating objects without grasping them is an essential component of ...

0 Wenxuan Zhou, et al. ∙

research

∙ 03/20/2023

Context-faithful Prompting for Large Language Models

Large language models (LLMs) encode parametric knowledge about world fac...

0 Wenxuan Zhou, et al. ∙

research

∙ 12/21/2022

Continual Contrastive Finetuning Improves Low-Resource Relation Extraction

Relation extraction (RE), which has relied on structurally annotated cor...

0 Wenxuan Zhou, et al. ∙

research

∙ 12/21/2022

Multi-hop Evidence Retrieval for Cross-document Relation Extraction

Relation Extraction (RE) has been extended to cross-document scenarios b...

0 Keming Lu, et al. ∙

research

∙ 11/02/2022

Learning to Grasp the Ungraspable with Emergent Extrinsic Dexterity

A simple gripper can solve more complex manipulation tasks if it can uti...

0 Wenxuan Zhou, et al. ∙

research

∙ 10/10/2022

Parameter-Efficient Tuning with Special Token Adaptation

Parameter-efficient tuning aims at updating only a small subset of param...

0 Xiaoocong Yang, et al. ∙

research

∙ 05/19/2022

Summarization as Indirect Supervision for Relation Extraction

Relation extraction (RE) models have been challenged by their reliance o...

0 Keming Lu, et al. ∙

research

∙ 05/08/2022

GRAPHCACHE: Message Passing as Caching for Sentence-Level Relation Extraction

Entity types and textual context are essential properties for sentence-l...

0 Yiwei Wang, et al. ∙

research

∙ 05/08/2022

Should We Rely on Entity Mentions for Relation Extraction? Debiasing Relation Extraction with Counterfactual Analysis

Recent literature focuses on utilizing the entity information in the sen...

0 Yiwei Wang, et al. ∙

research

∙ 04/29/2022

Answer Consolidation: Formulation and Benchmarking

Current question answering (QA) systems primarily consider the single-an...

0 Wenxuan Zhou, et al. ∙

research

∙ 04/12/2022

Offline Distillation for Robot Lifelong Learning with Imbalanced Experience

Robots will experience non-stationary environment dynamics throughout th...

0 Wenxuan Zhou, et al. ∙

research

∙ 12/16/2021

δ-SAM: Sharpness-Aware Minimization with Dynamic Reweighting

Deep neural networks are often overparameterized and may not easily achi...

0 Wenxuan Zhou, et al. ∙

research

∙ 04/18/2021

Contrastive Out-of-Distribution Detection for Pretrained Transformers

Pretrained transformers achieve remarkable performance when the test dat...

0 Wenxuan Zhou, et al. ∙

research

∙ 04/17/2021

Learning from Noisy Labels for Entity-Centric Information Extraction

Recent efforts for information extraction have relied on many deep neura...

0 Wenxuan Zhou, et al. ∙

research

∙ 03/16/2021

Lyapunov Barrier Policy Optimization

Deploying Reinforcement Learning (RL) agents in the real-world require t...

0 Harshit Sikchi, et al. ∙

research

∙ 02/02/2021

An Improved Baseline for Sentence-level Relation Extraction

Sentence-level relation extraction (RE) aims at identifying the relation...

0 Wenxuan Zhou, et al. ∙

research

∙ 11/14/2020

PLAS: Latent Action Space for Offline Reinforcement Learning

The goal of offline reinforcement learning is to learn a policy from a f...

0 Wenxuan Zhou, et al. ∙

research

∙ 10/21/2020

Document-Level Relation Extraction with Adaptive Thresholding and Localized Context Pooling

Document-level relation extraction (RE) poses new challenges compared to...

0 Wenxuan Zhou, et al. ∙

research

∙ 08/23/2020

Learning Off-Policy with Online Planning

We propose Learning Off-Policy with Online Planning (LOOP), combining th...

0 Harshit Sikchi, et al. ∙

research

∙ 08/21/2020

A Variational Approach to Unsupervised Sentiment Analysis

In this paper, we propose a variational approach to unsupervised sentime...

0 Ziqian Zeng, et al. ∙

research

∙ 11/10/2019

Improving BERT Fine-tuning with Embedding Normalization

Large pre-trained sentence encoders like BERT start a new chapter in nat...

0 Wenxuan Zhou, et al. ∙

research

∙ 11/04/2019

Learning to Annotate: Modularizing Data Augmentation for Text Classifiers with Natural Language Explanations

Deep neural networks usually require massive labeled data, which restric...

0 Ziqi Wang, et al. ∙

research

∙ 11/04/2019

Learning to Annotate: Modularizing Data Augmentation for TextClassifiers with Natural Language Explanations

Deep neural networks usually require massive labeled data, which restric...

0 Ziqi Wang, et al. ∙

research

∙ 09/05/2019

Neural Rule Grounding for Low-Resource Relation Extraction

While deep neural models have gained successes on information extraction...

0 Wenxuan Zhou, et al. ∙

research

∙ 07/26/2019

Environment Probing Interaction Policies

A key challenge in reinforcement learning (RL) is environment generaliza...

0 Wenxuan Zhou, et al. ∙

research

∙ 04/10/2019

A Variational Approach to Weakly Supervised Document-Level Multi-Aspect Sentiment Classification

In this paper, we propose a variational approach to weakly supervised do...

0 Ziqian Zeng, et al. ∙

Wenxuan Zhou

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