15 papers
SelfMem: Self-Optimizing Memory for AI Agents
Shu Yang, Junchao Wu, Derek F. Wong +1
While current AI agents support increasingly long context windows, tool use, and skill execution for long-horizon tasks, they still require memory systems to effectively leverage h…
Seeing the Poem: Image-Semantic Detection of AI-Generated Modern Chinese Poetry with MLLMs
Shanshan Wang, Fengying Ye, Hanjia Lyu +6
Previous detection studies have shown that LLMs cannot be effectively used as detectors, but these studies have not addressed modern Chinese poetry. Moreover, no relevant research…
DetectRL-X: Towards Reliable Multilingual and Real-World LLM-Generated Text Detection
Junchao Wu, Yefeng Liu, Chenyu Zhu +8
The effective detection and governance of Large Language Model (LLM) generated content has become increasingly critical due to the growing risk of misuse. Despite the impressive pe…
Neuron-Aware Data Selection In Instruction Tuning For Large Language Models
Xin Chen, Junchao Wu, Shu Yang +6
Instruction Tuning (IT) has been proven to be an effective approach to unlock the powerful capabilities of large language models (LLMs). Recent studies indicate that excessive IT d…
Can Large Language Models Identify Implicit Suicidal Ideation? An Empirical Evaluation
Tong Li, Shu Yang, Junchao Wu +6
We present a comprehensive evaluation framework for assessing Large Language Models' (LLMs) capabilities in suicide prevention, focusing on two critical aspects: the Identification…
Investigating CoT Monitorability in Large Reasoning Models
Shu Yang, Junchao Wu, Xilin Gong +4
Large Reasoning Models (LRMs) have demonstrated remarkable performance on complex tasks by engaging in extended reasoning before producing final answers. Beyond improving abilities…