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cs.LG2026
1% of Tokens Can Be Enough: On Gradient Estimation in On-Policy Distillation
Huanxin Sheng, Zhiling Ye, Haonan Wang +3
Sparse on-policy distillation (OPD) allocates teacher supervision to a small subset of tokens in student-generated trajectories. However, useful teacher guidance can yield a noisy…
cs.LG2026
MetaToolAgent: Towards Generalizable Tool Usage in LLMs through Meta-Learning
Zheng Fang, Wolfgang Mayer, Zeyu Zhang +4
Tool learning is increasingly important for large language models (LLMs) to effectively coordinate and utilize a diverse set of tools in order to solve complex real-world tasks. By…