237 citations · 1.2k across the 87 of their papers we have counts for
82 papers · 1 filter
Retrospective Progress-Aware Self-Refinement for LLM Agent Training
Xinbei Ma, Congmin Zheng, Jiyang Qiu +11
Long-horizon LLM-based agents receive rich environmental observations during interaction, yet outcome rewards provide limited explicit supervision about how individual actions adva…
The Hunger Game Debate: On the Emergence of Over-Competition in Multi-Agent Systems
Xinbei Ma, Ruotian Ma, Xingyu Chen +14
LLM-based multi-agent systems demonstrate great potential for tackling complex problems, but how competition shapes their behavior remains underexplored. This paper investigates th…
How Deep is Love in LLMs' Hearts? Exploring Semantic Size in Human-like Cognition
Yao Yao, Yifei Yang, Xinbei Ma +4
How human cognitive abilities are formed has long captivated researchers. However, a significant challenge lies in developing meaningful methods to measure these complex processes.…
MEGen: Generative Backdoor into Large Language Models via Model Editing
Jiyang Qiu, Xinbei Ma, Zhuosheng Zhang +3
Large language models (LLMs) have exhibited remarkable versatility and adaptability, while their widespread adoption across various applications also raises critical safety concern…
Caution for the Environment: Multimodal LLM Agents are Susceptible to Environmental Distractions
Xinbei Ma, Yiting Wang, Yao Yao +4
This paper investigates the faithfulness of multimodal large language model (MLLM) agents in a graphical user interface (GUI) environment, aiming to address the research question o…
DOCBENCH: A Benchmark for Evaluating LLM-based Document Reading Systems
Anni Zou, Wenhao Yu, Hongming Zhang +5
Recently, there has been a growing interest among large language model (LLM) developers in LLM-based document reading systems, which enable users to upload their own documents and…
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…
CoCo-Agent: A Comprehensive Cognitive MLLM Agent for Smartphone GUI Automation
Xinbei Ma, Zhuosheng Zhang, Hai Zhao
Multimodal large language models (MLLMs) have shown remarkable potential as human-like autonomous language agents to interact with real-world environments, especially for graphical…
On the Robustness of Editing Large Language Models
Xinbei Ma, Tianjie Ju, Jiyang Qiu +4
Large language models (LLMs) have played a pivotal role in building communicative AI, yet they encounter the challenge of efficient updates. Model editing enables the manipulation…
GLaPE: Gold Label-agnostic Prompt Evaluation and Optimization for Large Language Model
Xuanchang Zhang, Zhuosheng Zhang, Hai Zhao
Despite the rapid progress of large language models (LLMs), their task performance remains sensitive to prompt design. Recent studies have explored leveraging the LLM itself as an…
Igniting Language Intelligence: The Hitchhiker's Guide From Chain-of-Thought Reasoning to Language Agents
Zhuosheng Zhang, Yao Yao, Aston Zhang +8
Large language models (LLMs) have dramatically enhanced the field of language intelligence, as demonstrably evidenced by their formidable empirical performance across a spectrum of…
MedAgents: Large Language Models as Collaborators for Zero-shot Medical Reasoning
Xiangru Tang, Anni Zou, Zhuosheng Zhang +5
Large language models (LLMs), despite their remarkable progress across various general domains, encounter significant barriers in medicine and healthcare. This field faces unique c…
Generalizable Chain-of-Thought Prompting in Mixed-task Scenarios with Large Language Models
Anni Zou, Zhuosheng Zhang, Hai Zhao +1
Large language models (LLMs) have unveiled remarkable reasoning capabilities by exploiting chain-of-thought (CoT) prompting, which generates intermediate reasoning chains to serve…
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…
You Only Look at Screens: Multimodal Chain-of-Action Agents
Zhuosheng Zhang, Aston Zhang
Autonomous graphical user interface (GUI) agents aim to facilitate task automation by interacting with the user interface without manual intervention. Recent studies have investiga…
Meta-Reasoning: Semantics-Symbol Deconstruction for Large Language Models
Yiming Wang, Zhuosheng Zhang, Pei Zhang +2
Neural-symbolic methods have demonstrated efficiency in enhancing the reasoning abilities of large language models (LLMs). However, existing methods mainly rely on syntactically ma…
Decker: Double Check with Heterogeneous Knowledge for Commonsense Fact Verification
Anni Zou, Zhuosheng Zhang, Hai Zhao
Commonsense fact verification, as a challenging branch of commonsense question-answering (QA), aims to verify through facts whether a given commonsense claim is correct or not. Ans…
Element-aware Summarization with Large Language Models: Expert-aligned Evaluation and Chain-of-Thought Method
Yiming Wang, Zhuosheng Zhang, Rui Wang
Automatic summarization generates concise summaries that contain key ideas of source documents. As the most mainstream datasets for the news sub-domain, CNN/DailyMail and BBC XSum…
Exploring Human-Like Translation Strategy with Large Language Models
Zhiwei He, Tian Liang, Wenxiang Jiao +6
Large language models (LLMs) have demonstrated impressive capabilities in general scenarios, exhibiting a level of aptitude that approaches, in some aspects even surpasses, human-l…
Is ChatGPT a General-Purpose Natural Language Processing Task Solver?
Chengwei Qin, Aston Zhang, Zhuosheng Zhang +3
Spurred by advancements in scale, large language models (LLMs) have demonstrated the ability to perform a variety of natural language processing (NLP) tasks zero-shot -- i.e., with…
Multimodal Chain-of-Thought Reasoning in Language Models
Zhuosheng Zhang, Aston Zhang, Mu Li +3
Large language models (LLMs) have shown impressive performance on complex reasoning by leveraging chain-of-thought (CoT) prompting to generate intermediate reasoning chains as the…
Channel-aware Decoupling Network for Multi-turn Dialogue Comprehension
Zhuosheng Zhang, Hai Zhao, Longxiang Liu
Training machines to understand natural language and interact with humans is one of the major goals of artificial intelligence. Recent years have witnessed an evolution from matchi…
Universal Multimodal Representation for Language Understanding
Zhuosheng Zhang, Kehai Chen, Rui Wang +4
Representation learning is the foundation of natural language processing (NLP). This work presents new methods to employ visual information as assistant signals to general NLP task…
Self-Prompting Large Language Models for Zero-Shot Open-Domain QA
Junlong Li, Jinyuan Wang, Zhuosheng Zhang +1
Open-Domain Question Answering (ODQA) aims to answer questions without explicitly providing specific background documents. This task becomes notably challenging in a zero-shot sett…