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cs.AI2026
Selective Regenerative Decoding: Trajectory-Level Intervention for Inference-Time Reasoning
Sophia Xiao Pu, Yumo Xu, Sailik Sengupta +5
Inference-time decoding methods improve LLM reasoning by exploring multiple candidate trajectories, yet treat each trajectory as atomic: either retaining it whole or discarding it…
cs.AI2026
MemToolAgent: Leveraging Memory for Tool Using Agents Based on Environment and User Feedback
Suleyman Armagan Er, Danilo Ribeiro, Yogesh Virkar +5
Modern large language model (LLM) agents can use external tools to help users solve complex tasks. However, for problems that require learning from long-term historical events or f…