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Fat-Cat: Document-Driven Metacognitive Multi-Agent System for Complex Reasoning
Tong Yang, Yemin Wang, Chaoning Zhang +1
The effectiveness of LLM-based agents is often limited not by model capacity alone, but by how efficiently contextual information is utilized at runtime. Existing agent frameworks…
TriPlay-RL: Tri-Role Self-Play Reinforcement Learning for LLM Safety Alignment
Zhewen Tan, Wenhan Yu, Jianfeng Si +9
In recent years, safety risks associated with large language models have become increasingly prominent, highlighting the urgent need to mitigate the generation of toxic and harmful…
Beyond Invisibility: Learning Robust Visible Watermarks for Stronger Copyright Protection
Tianci Liu, Tong Yang, Quan Zhang +1
As AI advances, copyrighted content faces growing risk of unauthorized use, whether through model training or direct misuse. Building upon invisible adversarial perturbation, recen…
HATA: Trainable and Hardware-Efficient Hash-Aware Top-k Attention for Scalable Large Model Inference
Ping Gong, Jiawei Yi, Shengnan Wang +13
Large Language Models (LLMs) have emerged as a pivotal research area, yet the attention module remains a critical bottleneck in LLM inference, even with techniques like KVCache to…
CFT-RAG: An Entity Tree Based Retrieval Augmented Generation Algorithm With Cuckoo Filter
Zihang Li, Yangdong Ruan, Wenjun Liu +2
Although retrieval-augmented generation(RAG) significantly improves generation quality by retrieving external knowledge bases and integrating generated content, it faces computatio…