activity
20162024
most citedUniversal Multimodal Representation for Language Understanding

35 citations · 65 across the 15 of their papers we have counts for

collaborators

15 papers

cs.CL2024

Mitigating Misleading Chain-of-Thought Reasoning with Selective Filtering

Yexin Wu, Zhuosheng Zhang, Hai Zhao

Large language models have manifested remarkable capabilities by leveraging chain-of-thought (CoT) reasoning techniques to solve intricate questions through step-by-step reasoning…

cs.CL20232 cited

Multi-grained Evidence Inference for Multi-choice Reading Comprehension

Yilin Zhao, Hai Zhao, Sufeng Duan

Multi-choice Machine Reading Comprehension (MRC) is a major and challenging task for machines to answer questions according to provided options. Answers in multi-choice MRC cannot…

cs.CL20231 cited

Self-prompted Chain-of-Thought on Large Language Models for Open-domain Multi-hop Reasoning

Jinyuan Wang, Junlong Li, Hai Zhao

In open-domain question-answering (ODQA), most existing questions require single-hop reasoning on commonsense. To further extend this task, we officially introduce open-domain mult…

cs.CL2023

Multi-turn Dialogue Comprehension from a Topic-aware Perspective

Xinbei Ma, Yi Xu, Hai Zhao +1

Dialogue related Machine Reading Comprehension requires language models to effectively decouple and model multi-turn dialogue passages. As a dialogue development goes after the int…

cs.CL2023

CSPRD: A Financial Policy Retrieval Dataset for Chinese Stock Market

Jinyuan Wang, Hai Zhao, Zhong Wang +6

In recent years, great advances in pre-trained language models (PLMs) have sparked considerable research focus and achieved promising performance on the approach of dense passage r…

cs.CL2023

Enhancing Visually-Rich Document Understanding via Layout Structure Modeling

Qiwei Li, Zuchao Li, Xiantao Cai +2

In recent years, the use of multi-modal pre-trained Transformers has led to significant advancements in visually-rich document understanding. However, existing models have mainly f…