23 citations · 28 across the 16 of their papers we have counts for
19 papers
SkillHorizon: Constructing Long-Horizon Agent Tasks through Skill Composition
Yuxuan Liu, Zhaochen Su, Hangyu Guo +11
Long-horizon agents must complete workflows in which later activities depend on earlier outputs and changes to shared state. A key challenge for evaluation is to expand task requir…
E-Commerce Bench: Evaluating LLM Agents on Long-Horizon Autonomous Business Operation
Wei Fan, Xinjie Shen, Xudong Guo +8
Long-horizon agentic tasks go beyond chaining short tasks over more interaction turns. Their evolving dynamic environments and long-range dependencies require Large Language Models…
Isolation as a First-Class Principle for LLM-Agent System Safety: Concepts, Taxonomy, Challenges and Future Directions
Huihao Jing, Wenbin Hu, Shaojin Chen +10
The capability of LLM agents to function as the ``brain'' of a system fundamentally expands the scope of analysis beyond a standalone model. Consequently, safety is no longer only…
Can LLMs Time Travel? Enhancing Temporal Consistency in Legal Agentic Search through Reinforcement Learning
Wei Fan, Yining Zhou, Mufan Zhang +8
While large language models (LLMs) augmented with agentic search capabilities show promise for legal reasoning, they overlook a fundamental constraint that applicable law must matc…
DeepPlanner: Scaling Planning Capability for Deep Research Agents via Advantage Shaping
Wei Fan, Wenlin Yao, Zheng Li +6
Large language models (LLMs) augmented with multi-step reasoning and action generation abilities have shown promise in leveraging external tools to tackle complex tasks that requir…
MASLegalBench: Benchmarking Multi-Agent Systems in Deductive Legal Reasoning
Huihao Jing, Wenbin Hu, Hongyu Luo +4
Multi-agent systems (MAS), leveraging the remarkable capabilities of Large Language Models (LLMs), show great potential in addressing complex tasks. In this context, integrating MA…
Structuring the Unstructured: A Systematic Review of Text-to-Structure Generation for Agentic AI with a Universal Evaluation Framework
Zheye Deng, Chunkit Chan, Tianshi Zheng +3
The evolution of AI systems toward agentic operation and context-aware retrieval necessitates transforming unstructured text into structured formats like tables, knowledge graphs,…
SessionIntentBench: A Multi-task Inter-session Intention-shift Modeling Benchmark for E-commerce Customer Behavior Understanding
Yuqi Yang, Weiqi Wang, Baixuan Xu +13
Session history is a common way of recording user interacting behaviors throughout a browsing activity with multiple products. For example, if an user clicks a product webpage and…
AutoSchemaKG: Autonomous Knowledge Graph Construction through Dynamic Schema Induction from Web-Scale Corpora
Jiaxin Bai, Wei Fan, Qi Hu +17
We present AutoSchemaKG, a framework for fully autonomous knowledge graph construction that eliminates the need for predefined schemas. Our system leverages large language models t…
Legal Rule Induction: Towards Generalizable Principle Discovery from Analogous Judicial Precedents
Wei Fan, Tianshi Zheng, Yiran Hu +7
Legal rules encompass not only codified statutes but also implicit adjudicatory principles derived from precedents that contain discretionary norms, social morality, and policy. Wh…
Evaluating and Enhancing LLMs Agent based on Theory of Mind in Guandan: A Multi-Player Cooperative Game under Imperfect Information
Yauwai Yim, Chunkit Chan, Tianyu Shi +4
Large language models (LLMs) have shown success in handling simple games with imperfect information and enabling multi-agent coordination, but their ability to facilitate practical…
GoldCoin: Grounding Large Language Models in Privacy Laws via Contextual Integrity Theory
Wei Fan, Haoran Li, Zheye Deng +2
Privacy issues arise prominently during the inappropriate transmission of information between entities. Existing research primarily studies privacy by exploring various privacy att…
On the Role of Entity and Event Level Conceptualization in Generalizable Reasoning: A Survey of Tasks, Methods, Applications, and Future Directions
Weiqi Wang, Tianqing Fang, Haochen Shi +8
Conceptualization, a fundamental element of human cognition, plays a pivotal role in human generalizable reasoning. Generally speaking, it refers to the process of sequentially abs…
Text-Tuple-Table: Towards Information Integration in Text-to-Table Generation via Global Tuple Extraction
Zheye Deng, Chunkit Chan, Weiqi Wang +5
The task of condensing large chunks of textual information into concise and structured tables has gained attention recently due to the emergence of Large Language Models (LLMs) and…
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…
AbsInstruct: Eliciting Abstraction Ability from LLMs through Explanation Tuning with Plausibility Estimation
Zhaowei Wang, Wei Fan, Qing Zong +7
Abstraction ability is crucial in human intelligence, which can also benefit various tasks in NLP study. Existing work shows that LLMs are deficient in abstract ability, and how to…
PrivLM-Bench: A Multi-level Privacy Evaluation Benchmark for Language Models
Haoran Li, Dadi Guo, Donghao Li +7
The rapid development of language models (LMs) brings unprecedented accessibility and usage for both models and users. On the one hand, powerful LMs achieve state-of-the-art perfor…
Chain-of-Choice Hierarchical Policy Learning for Conversational Recommendation
Wei Fan, Weijia Zhang, Weiqi Wang +2
Conversational Recommender Systems (CRS) illuminate user preferences via multi-round interactive dialogues, ultimately navigating towards precise and satisfactory recommendations.…
Multi-step Jailbreaking Privacy Attacks on ChatGPT
Haoran Li, Dadi Guo, Wei Fan +4
With the rapid progress of large language models (LLMs), many downstream NLP tasks can be well solved given appropriate prompts. Though model developers and researchers work hard o…