Topic: repair

4 stories found

Thursday, November 5, 2026

research40

Rewrite, Then Veto: Rewriter-Agnostic Edit Gating for LLM-Based Post-OCR Correction

A new method called EditVeto has been proposed to address the issue of language models altering correctly transcribed text when correcting OCR outputs of historical documents. This technique acts as a veto gate after full-context rewriting by LLMs, ensuring only necessary edits are made.

arxiv.orgโ†—

Monday, November 2, 2026

research40

HyperRepair: Recovering Forgotten General Capabilities of Fine-Tuned Language Models

A new method called HyperRepair has been developed to recover the general capabilities of fine-tuned language models without compromising their specialized performance, addressing the common trade-off faced by existing techniques. This breakthrough could enhance the versatility and reliability of language models across various applications.

arxiv.orgโ†—

Monday, October 26, 2026

research35

Don't Forget What You Just Learned: Self-Directed Repair Turns Agent Mistakes Into Lasting Lessons

Intelligent agents should self-improve by learning from their mistakes, but current systems forget lessons quickly, hindering long-term progress. This issue highlights the need for more robust mechanisms to ensure agent experiences lead to lasting improvements.

arxiv.orgโ†—

๐ŸŒฟ That's all for now. Come back tomorrow.

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