11 papers
MemoNoveltyAgent: A Historical Research Memory-Aware Agent Workflow for Paper Novelty Assessment
Jiajun Hou, Hexuan Deng, Wenxiang Jiao +4
To alleviate the heavy burden of paper screening, researchers increasingly rely on existing AI agents, such as AI reviewers or DeepResearch, for paper evaluation and novelty assess…
MASPO: Joint Prompt Optimization for LLM-based Multi-Agent Systems
Zhexuan Wang, Xuebo Liu, Li Wang +4
Large language model (LLM)-based Multi-agent systems (MAS) have shown promise in tackling complex collaborative tasks, where agents are typically orchestrated via role-specific pro…
SeaPO: Strategic Error Amplification for Robust Preference Optimization of Large Language Models
Jun Rao, Yunjie Liao, Xuebo Liu +6
Existing alignment methods for preference optimization of large language models (LLMs) aim to enhance model performance by utilizing pairs of positive and negative samples. However…
AQuilt: Weaving Logic and Self-Inspection into Low-Cost, High-Relevance Data Synthesis for Specialist LLMs
Xiaopeng Ke, Hexuan Deng, Xuebo Liu +4
Despite the impressive performance of large language models (LLMs) in general domains, they often underperform in specialized domains. Existing approaches typically rely on data sy…
APT: Improving Specialist LLM Performance with Weakness Case Acquisition and Iterative Preference Training
Jun Rao, Zepeng Lin, Xuebo Liu +6
Large Language Models (LLMs) often require domain-specific fine-tuning to address targeted tasks, which risks degrading their general capabilities. Maintaining a balance between do…
DynamicKV: Task-Aware Adaptive KV Cache Compression for Long Context LLMs
Xiabin Zhou, Wenbin Wang, Minyan Zeng +5
Efficient KV cache management in LLMs is crucial for long-context tasks like RAG and summarization. Existing KV cache compression methods enforce a fixed pattern, neglecting task-s…