11 papers
Belief Memory: Agent Memory Under Partial Observability
Junfeng Liao, Qizhou Wang, Jianing Zhu +3
LLM agents that operate over long context depend on external memory to accumulate knowledge over time. However, existing methods typically store each observation as a single determ…
When Personalization Tricks Detectors: The Feature-Inversion Trap in Machine-Generated Text Detection
Lang Gao, Xuhui Li, Chenxi Wang +7
Large language models (LLMs) have grown more powerful in language generation, producing fluent text and even imitating personal style. Yet, this ability also heightens the risk of…
The Stepwise Deception: Simulating the Evolution from True News to Fake News with LLM Agents
Yuhan Liu, Zirui Song, Juntian Zhang +3
With the growing spread of misinformation online, understanding how true news evolves into fake news has become crucial for early detection and prevention. However, previous resear…
Thinking Before Running! Efficient Code Generation with Thorough Exploration and Optimal Refinement
Xiaoqing Zhang, Yuhan Liu, Flood Sung +3
Code generation is crucial in software engineering for automating the coding process efficiently. While test-time computation methods show promise, they suffer from high latency du…
More is not always better? Enhancing Many-Shot In-Context Learning with Differentiated and Reweighting Objectives
Xiaoqing Zhang, Ang Lv, Yuhan Liu +6
Large language models (LLMs) excel at few-shot in-context learning (ICL) without requiring parameter updates. However, as ICL demonstrations increase from a few to many, performanc…
SAGraph: A Large-Scale Social Graph Dataset with Comprehensive Context for Influencer Selection in Marketing
Xiaoqing Zhang, Yuhan Liu, Jianzhou Wang +3
Influencer marketing campaign success heavily depends on identifying key opinion leaders who can effectively leverage their credibility and reach to promote products or services. T…