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Yuhang Jiang

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#machine learning Preprint Sep 2026

You Only Edit Once: Incentivizing In-Context Capability of LLMs via Local Demonstration Refinement

In-context learning (ICL) is crucial for boosting the inference performance of large language models (LLMs). However, the effectiveness of ICL in LLMs is greatly influenced by the choice of demonstration sets. Exhaustive searches over these sets are combinatorial, and existing selectors often rely on relevance or likel...

Jia-Rong Wen, Qi Wang, Yun Qu et al. · 0 citations
#machine learning Preprint Sep 2026

Median Temporal Ensembling: Training-Free Robust Aggregation for Action-Chunked Visuomotor Policies

Action-chunked visuomotor policies predict overlapping trajectories, so every executed action is covered by several predictions. Temporal ensembling smooths execution by combining these predictions with an exponentially weighted mean. One corrupted prediction can move the aggregate without bound: its breakdown point is...

Yuhang Jiang · 0 citations

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