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cs.AI2026
-mem: Efficient Online Memory for Large Language Models
Jingdi Lei, Di Zhang, Junxian Li +7
Large language models increasingly need to accumulate and reuse historical information in long-term assistants and agent systems. Simply expanding the context window is costly and…
cs.LG2026
Boosting LLM Reasoning via Human-Inspired Reward Shaping
Wenze Lin, Zhen Yang, Xitai Jiang +2
Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a promising paradigm for enhancing reasoning in Large Language Models (LLMs). However, existing reward formulat…