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cs.LG2026
Drafting Agents, Not Just Tokens: Speculative Recursive Self-Improvement for Agentic Systems
Xin Xu, Ke Cheng, Hao Wang +11
Improving an agent through successive revisions requires balancing exploration and evaluation under a limited budget. A narrow search can miss useful sequences of edits, while full…
cs.LG2026
SelectTTRL: Representation-Guided Data Selection for Efficient Test-Time Reinforcement Learning
Yi Li, Linan Yue, Weibo Gao
Test-Time Reinforcement Learning (TTRL) enables large language models to adapt directly on unlabeled test problems by constructing pseudo-labels from multiple sampled responses. Ho…