6 papers
Episodic Memory Temporal Consistency for Cooperative Multi-Agent Reinforcement Learning
Zicheng Zhao, Yu Lan, Chengzhengxu Li +2
Cooperative Multi-Agent Reinforcement Learning (MARL) frequently suffers from severe reward sparsity and exploration bottlenecks. While episodic memory mechanisms mitigate these is…
Can Reasoning Path still be Effective as Input? Bridging Post-Reasoning to Chain-of-Thought Compression
Chengzhengxu Li, Xiaoming Liu, Zhaohan Zhang +5
Recent developments have enabled advanced reasoning in Large Language Models (LLMs) via long Chain-of-Thought (CoT), trading efficiency during inference for performance. Existing w…
MGTEVAL: An Interactive Platform for Systemtic Evaluation of Machine-Generated Text Detectors
Yuanfan Li, Qi Zhou, Chengzhengxu Li +5
We present MGTEVAL, an extensible platform for systematic evaluation of Machine-Generated Text (MGT) detectors. Despite rapid progress in MGT detection, existing evaluations are of…
MGT-Prism: Enhancing Domain Generalization for Machine-Generated Text Detection via Spectral Alignment
Shengchao Liu, Xiaoming Liu, Chengzhengxu Li +4
Large Language Models have shown growing ability to generate fluent and coherent texts that are highly similar to the writing style of humans. Current detectors for Machine-Generat…
HACo-Det: A Study Towards Fine-Grained Machine-Generated Text Detection under Human-AI Coauthoring
Zhixiong Su, Yichen Wang, Herun Wan +2
The misuse of large language models (LLMs) poses potential risks, motivating the development of machine-generated text (MGT) detection. Existing literature primarily concentrates o…
Iron Sharpens Iron: Defending Against Attacks in Machine-Generated Text Detection with Adversarial Training
Yuanfan Li, Zhaohan Zhang, Chengzhengxu Li +2
Machine-generated Text (MGT) detection is crucial for regulating and attributing online texts. While the existing MGT detectors achieve strong performance, they remain vulnerable t…