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cs.CL2025
BARD: budget-aware reasoning distillation
Lujie Niu, Lei Shen, Yi Jiang +4
While long Chain-of-Thought (CoT) distillation effectively transfers reasoning capability to smaller language models, the reasoning process often remains redundant and computationa…
cs.CL2025
TDR: Task-Decoupled Retrieval with Fine-Grained LLM Feedback for In-Context Learning
Yifu Chen, Bingchen Huang, Zhiling Wang +4
In-context learning (ICL) has become a classic approach for enabling LLMs to handle various tasks based on a few input-output examples. The effectiveness of ICL heavily relies on t…
cs.CL2025
SEO: Stochastic Experience Optimization for Large Language Models
Jitao Xu, Hongyun Zhou, Lei Shen +3
Large Language Models (LLMs) can benefit from useful experiences to improve their performance on specific tasks. However, finding helpful experiences for different LLMs is not obvi…