55 citations · 117 across the 26 of their papers we have counts for
27 papers
Qwen-AgentWorld: Language World Models for General Agents
Yuxin Zuo, Zikai Xiao, Li Sheng +30
A world model predicts environment dynamics based on current observations and actions, serving as a core cognitive mechanism for reasoning and planning. In this work, we investigat…
Training LLMs for Multi-Step Tool Orchestration with Constrained Data Synthesis and Graduated Rewards
Cheng Jiayang, Xin Liu, Zhihan Zhang +8
Multi-step tool orchestration remains challenging for LLMs, as state-of-the-art models frequently fail on full sequence execution due to parameter errors. Training for these workfl…
AMemGym: Interactive Memory Benchmarking for Assistants in Long-Horizon Conversations
Cheng Jiayang, Dongyu Ru, Lin Qiu +4
Long-horizon interactions between users and LLM-based assistants necessitate effective memory management, yet current approaches face challenges in training and evaluation of memor…
NewtonBench: Benchmarking Generalizable Scientific Law Discovery in LLM Agents
Tianshi Zheng, Kelvin Kiu-Wai Tam, Newt Hue-Nam K. Nguyen +10
Large language models are emerging as powerful tools for scientific law discovery, a foundational challenge in AI-driven science. However, existing benchmarks for this task suffer…
InteGround: On the Evaluation of Verification and Retrieval Planning in Integrative Grounding
Cheng Jiayang, Qianqian Zhuang, Haoran Li +4
Grounding large language models (LLMs) in external knowledge sources is a promising method for faithful prediction. While existing grounding approaches work well for simple queries…
XToM: Exploring the Multilingual Theory of Mind for Large Language Models
Chunkit Chan, Yauwai Yim, Hongchuan Zeng +14
Theory of Mind (ToM), the ability to infer mental states in others, is pivotal for human social cognition. Existing evaluations of ToM in LLMs are largely limited to English, negle…
LogiDynamics: Unraveling the Dynamics of Inductive, Abductive and Deductive Logical Inferences in LLM Reasoning
Tianshi Zheng, Jiayang Cheng, Chunyang Li +6
Modern large language models (LLMs) employ diverse logical inference mechanisms for reasoning, making the strategic optimization of these approaches critical for advancing their ca…
Top Ten Challenges Towards Agentic Neural Graph Databases
Jiaxin Bai, Zihao Wang, Yukun Zhou +16
Graph databases (GDBs) like Neo4j and TigerGraph excel at handling interconnected data but lack advanced inference capabilities. Neural Graph Databases (NGDBs) address this by inte…
Can Language Models Learn to Skip Steps?
Tengxiao Liu, Qipeng Guo, Xiangkun Hu +4
Trained on vast corpora of human language, language models demonstrate emergent human-like reasoning abilities. Yet they are still far from true intelligence, which opens up intrig…
Persona Knowledge-Aligned Prompt Tuning Method for Online Debate
Chunkit Chan, Cheng Jiayang, Xin Liu +7
Debate is the process of exchanging viewpoints or convincing others on a particular issue. Recent research has provided empirical evidence that the persuasiveness of an argument is…
ECon: On the Detection and Resolution of Evidence Conflicts
Cheng Jiayang, Chunkit Chan, Qianqian Zhuang +7
The rise of large language models (LLMs) has significantly influenced the quality of information in decision-making systems, leading to the prevalence of AI-generated content and c…
ActPlan-1K: Benchmarking the Procedural Planning Ability of Visual Language Models in Household Activities
Ying Su, Zhan Ling, Haochen Shi +3
Large language models~(LLMs) have been adopted to process textual task description and accomplish procedural planning in embodied AI tasks because of their powerful reasoning abili…
RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation
Dongyu Ru, Lin Qiu, Xiangkun Hu +15
Despite Retrieval-Augmented Generation (RAG) showing promising capability in leveraging external knowledge, a comprehensive evaluation of RAG systems is still challenging due to th…
Privacy Checklist: Privacy Violation Detection Grounding on Contextual Integrity Theory
Haoran Li, Wei Fan, Yulin Chen +5
Privacy research has attracted wide attention as individuals worry that their private data can be easily leaked during interactions with smart devices, social platforms, and AI app…
OpenResearcher: Unleashing AI for Accelerated Scientific Research
Yuxiang Zheng, Shichao Sun, Lin Qiu +13
The rapid growth of scientific literature imposes significant challenges for researchers endeavoring to stay updated with the latest advancements in their fields and delve into new…
LLMs Assist NLP Researchers: Critique Paper (Meta-)Reviewing
Jiangshu Du, Yibo Wang, Wenting Zhao +37
This work is motivated by two key trends. On one hand, large language models (LLMs) have shown remarkable versatility in various generative tasks such as writing, drawing, and ques…
Boosting Scientific Concepts Understanding: Can Analogy from Teacher Models Empower Student Models?
Siyu Yuan, Cheng Jiayang, Lin Qiu +1
Analogical reasoning plays a critical role in human cognition, enabling us to understand new concepts by associating them with familiar ones. Previous research in the AI community…
NegotiationToM: A Benchmark for Stress-testing Machine Theory of Mind on Negotiation Surrounding
Chunkit Chan, Cheng Jiayang, Yauwai Yim +7
Large Language Models (LLMs) have sparked substantial interest and debate concerning their potential emergence of Theory of Mind (ToM) ability. Theory of mind evaluations currently…
EventGround: Narrative Reasoning by Grounding to Eventuality-centric Knowledge Graphs
Cheng Jiayang, Lin Qiu, Chunkit Chan +3
Narrative reasoning relies on the understanding of eventualities in story contexts, which requires a wealth of background world knowledge. To help machines leverage such knowledge,…
CANDLE: Iterative Conceptualization and Instantiation Distillation from Large Language Models for Commonsense Reasoning
Weiqi Wang, Tianqing Fang, Chunyang Li +9
The sequential process of conceptualization and instantiation is essential to generalizable commonsense reasoning as it allows the application of existing knowledge to unfamiliar s…
StoryAnalogy: Deriving Story-level Analogies from Large Language Models to Unlock Analogical Understanding
Cheng Jiayang, Lin Qiu, Tsz Ho Chan +9
Analogy-making between narratives is crucial for human reasoning. In this paper, we evaluate the ability to identify and generate analogies by constructing a first-of-its-kind larg…
Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity
Cunxiang Wang, Xiaoze Liu, Yuanhao Yue +13
This survey addresses the crucial issue of factuality in Large Language Models (LLMs). As LLMs find applications across diverse domains, the reliability and accuracy of their outpu…
Self-Consistent Narrative Prompts on Abductive Natural Language Inference
Chunkit Chan, Xin Liu, Tsz Ho Chan +4
Abduction has long been seen as crucial for narrative comprehension and reasoning about everyday situations. The abductive natural language inference (NLI) task has been propose…
DiscoPrompt: Path Prediction Prompt Tuning for Implicit Discourse Relation Recognition
Chunkit Chan, Xin Liu, Jiayang Cheng +4
Implicit Discourse Relation Recognition (IDRR) is a sophisticated and challenging task to recognize the discourse relations between the arguments with the absence of discourse conn…