3 citations · 8 across the 13 of their papers we have counts for
15 papers
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…
World Model-Guided Reinforcement Learning via Counterfactual User Engagement Simulation
Ang Li, Xin Xu, Bin Liang +4
Reinforcement learning for user-centric agents is limited by the cost, latency, and risk of collecting online feedback, as well as by the lack of counterfactual comparisons under t…
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…
Expectation Alignment of Language Models for Real-World User Expectations
Miaomiao Li, Yang Wang, Bin Liang +3
Large language models (LLMs) have demonstrated remarkable performance on standard benchmarks, yet it remains largely unexplored whether they truly meet user expectations. Existing…
Memory-T1: Reinforcement Learning for Temporal Reasoning in Multi-session Agents
Yiming Du, Baojun Wang, Yifan Xiang +11
Temporal reasoning over long, multi-session dialogues is a critical capability for conversational agents. However, existing works and our pilot study have shown that as dialogue hi…
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…
MemeReaCon: Probing Contextual Meme Understanding in Large Vision-Language Models
Zhengyi Zhao, Shubo Zhang, Yuxi Zhang +10
Memes have emerged as a popular form of multimodal online communication, where their interpretation heavily depends on the specific context in which they appear. Current approaches…
T: An Adaptive Test-Time Scaling Strategy for Contextual Question Answering
Zhengyi Zhao, Shubo Zhang, Zezhong Wang +7
Recent advances in Large Language Models (LLMs) have demonstrated remarkable performance in Contextual Question Answering (CQA). However, prior approaches typically employ elaborat…
WHERE and WHICH: Iterative Debate for Biomedical Synthetic Data Augmentation
Zhengyi Zhao, Shubo Zhang, Bin Liang +2
In Biomedical Natural Language Processing (BioNLP) tasks, such as Relation Extraction, Named Entity Recognition, and Text Classification, the scarcity of high-quality data remains…
FReM: A Flexible Reasoning Mechanism for Balancing Quick and Slow Thinking in Long-Context Question Answering
Zhengyi Zhao, Shubo Zhang, Zezhong Wang +3
Long-context question-answering (LCQA) systems have greatly benefited from the powerful reasoning capabilities of large language models (LLMs), which can be categorized into slow a…
EventWeave: A Dynamic Framework for Capturing Core and Supporting Events in Dialogue Systems
Zhengyi Zhao, Shubo Zhang, Yiming Du +5
Large language models have improved dialogue systems, but often process conversational turns in isolation, overlooking the event structures that guide natural interactions. Hence w…
OSPC: Detecting Harmful Memes with Large Language Model as a Catalyst
Jingtao Cao, Zheng Zhang, Hongru Wang +3
Memes, which rapidly disseminate personal opinions and positions across the internet, also pose significant challenges in propagating social bias and prejudice. This study presents…
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…
CoCoCo: Improving Text-Guided Video Inpainting for Better Consistency, Controllability and Compatibility
Bojia Zi, Shihao Zhao, Xianbiao Qi +6
Recent advancements in video generation have been remarkable, yet many existing methods struggle with issues of consistency and poor text-video alignment. Moreover, the field lacks…
PerLTQA: A Personal Long-Term Memory Dataset for Memory Classification, Retrieval, and Synthesis in Question Answering
Yiming Du, Hongru Wang, Zhengyi Zhao +5
Long-term memory plays a critical role in personal interaction, considering long-term memory can better leverage world knowledge, historical information, and preferences in dialogu…