2 papers
cs.CL2026
AtomMem: Building Simple and Effective Memory System for LLM Agents via Atomic Facts
Yanyu Yao, Shangze Li, Zhi Zheng +4
Large language models (LLMs) demonstrate strong reasoning and generation abilities, but their fixed context windows limit long-term information accumulation and reuse across multi-…
cs.AI2026
Entropy-KL Divergence-based Token Masking: A Novel Approach for Selective Fine-tuning of Large Language Models
Qi Liu, Mingdi Sun, Yongyi He +5
Supervised fine-tuning (SFT) followed by reinforcement learning (RL) has become a standard post-training paradigm for large language models. This paradigm provides a cold-start for…