3 citations · 12 across the 19 of their papers we have counts for
9 papers · 1 filter
CivWorldBench: Evaluating Language World Models in Structured Multi-Agent Sandbox Worlds
Ang Li, Haofei Yu, Zhengwei Tao +7
The growing use of language models for forecasting motivates a broader evaluation of their world-model capabilities. Such evaluation must go beyond predictive accuracy to assess hi…
Not All or None: Dynamic Construction of Target-aware Memory Graph for Conversational Stance Detection
Yifan Xiang, Bin Liang, Yuqi Huang +2
Stance detection is crucial for understanding the underlying attitude of an expression towards a target. Conversational stance detection is a more challenging stance detection task…
Write, Execute, Refine: From Skill Follower to Skill Optimizer via Reinforcement Learning from Execution Feedback
Kang Peng, Zhiwei Zhang, Yichen Zhang +7
Expert-written natural language skills can improve tool-using agents, yet agent-authored skills perform 8--11 points worse than using no skill. While inference-time loops can repai…
ReSURE: Regularizing Supervision Unreliability for Multi-turn Dialogue Fine-tuning
Yiming Du, Yifan Xiang, Bin Liang +3
Fine-tuning multi-turn dialogue systems requires high-quality supervision but often suffers from degraded performance when exposed to low-quality data. Supervision errors in early…
MemGuide: Intent-Driven Memory Selection for Goal-Oriented Multi-Session LLM Agents
Yiming Du, Bingbing Wang, Yang He +7
Modern task-oriented dialogue (TOD) systems increasingly rely on large language model (LLM) agents, leveraging Retrieval-Augmented Generation (RAG) and long-context capabilities fo…
A Comprehensive Evaluation on Event Reasoning of Large Language Models
Zhengwei Tao, Zhi Jin, Yifan Zhang +7
Event reasoning is a fundamental ability that underlies many applications. It requires event schema knowledge to perform global reasoning and needs to deal with the diversity of th…
Role Prompting Guided Domain Adaptation with General Capability Preserve for Large Language Models
Rui Wang, Fei Mi, Yi Chen +5
The growing interest in Large Language Models (LLMs) for specialized applications has revealed a significant challenge: when tailored to specific domains, LLMs tend to experience c…
Multi-modal Stance Detection: New Datasets and Model
Bin Liang, Ang Li, Jingqian Zhao +5
Stance detection is a challenging task that aims to identify public opinion from social media platforms with respect to specific targets. Previous work on stance detection largely…
Mitigating Biases of Large Language Models in Stance Detection with Counterfactual Augmented Calibration
Ang Li, Jingqian Zhao, Bin Liang +6
Stance detection is critical for understanding the underlying position or attitude expressed toward a topic. Large language models (LLMs) have demonstrated significant advancements…