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cs.CL2026
When LLM Meets Tree Search: A Systematic View of Inference as Search in Large Language Models
Jiaqi Wei, Xiang Zhang, Yuejin Yang +10
As pretraining scaling laws approach saturation, Test-Time Scaling (TTS) has emerged as an important direction for improving reasoning by allocating inference-time compute to a fix…
cs.CL2026
From Player to Master: Enhancing Test-Time Learning of LLM Agents via Reinforcement Learning over Memory
Yishuo Cai, Xingyu Guo, Xuancheng Huang +8
Large language model (LLM) agents are increasingly deployed in long-running settings where improving through experience at test time becomes important. A common approach is to upda…
cs.CL2026
GroupGPT: A Token-efficient and Privacy-preserving Agentic Framework for Multi-User Chat Assistant
Zhuokang Shen, Yifan Wang, Hanyu Chen +6
Recent advances in large language models (LLMs) have enabled increasingly capable chatbots. However, most existing systems focus on single-user settings and do not generalize well…