6 papers
Beyond Meta-Reasoning: Metacognitive Consolidation for Self-Improving LLM Reasoning
Ziqing Zhuang, Linhai Zhang, Jiasheng Si +2
Large language models (LLMs) have demonstrated strong reasoning capabilities, and as existing approaches for enhancing LLM reasoning continue to mature, increasing attention has sh…
SCOPE: Optimizing Key-Value Cache Compression in Long-context Generation
Jialong Wu, Zhenglin Wang, Linhai Zhang +3
Key-Value (KV) cache has become a bottleneck of LLMs for long-context generation. Despite the numerous efforts in this area, the optimization for the decoding phase is generally ig…
Explainable Depression Detection in Clinical Interviews with Personalized Retrieval-Augmented Generation
Linhai Zhang, Ziyang Gao, Deyu Zhou +1
Depression is a widespread mental health disorder, and clinical interviews are the gold standard for assessment. However, their reliance on scarce professionals highlights the need…
PROPER: A Progressive Learning Framework for Personalized Large Language Models with Group-Level Adaptation
Linhai Zhang, Jialong Wu, Deyu Zhou +1
Personalized large language models (LLMs) aim to tailor their outputs to user preferences. Recent advances in parameter-efficient fine-tuning (PEFT) methods have highlighted the ef…
Rehearse With User: Personalized Opinion Summarization via Role-Playing based on Large Language Models
Yanyue Zhang, Yulan He, Deyu Zhou
Personalized opinion summarization is crucial as it considers individual user interests while generating product summaries. Recent studies show that although large language models…
RGAR: Recurrence Generation-augmented Retrieval for Factual-aware Medical Question Answering
Sichu Liang, Linhai Zhang, Hongyu Zhu +3
Medical question answering requires extensive access to specialized conceptual knowledge. The current paradigm, Retrieval-Augmented Generation (RAG), acquires expertise medical kno…