---
format: "aidr-story-markdown/v1"
id: "aa7a4d63416f5b160d585b5616dede43ad143e5ae3f09b186e1acb2cbd526781"
canonical_url: "https://aidr.today/aa7a4d63?lang=en"
title: "Prompt-agnostic Language Models"
lang: "en"
requested_lang: "en"
available_langs: ["en","vi"]
translation_fallback: null
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published_at: "2026-10-30T04:00:00.000Z"
category: "Research"
topics: ["llm"]
source_urls: ["https://arxiv.org/abs/2610.37683"]
summary: "Researchers introduce Prompt-TIES and Prompt-DARE, two gradient-merging methods that reduce interference between per-paraphrasing gradients during instruction tuning to improve prompt robustness in large language models."
---

# Prompt\-agnostic Language Models

> [Open the canonical story](<https://aidr.today/aa7a4d63?lang=en>)

**Published:** 2026-10-30T04:00:00.000Z
**Category:** Research
**Topics:** llm

## Summary

Researchers introduce Prompt\-TIES and Prompt\-DARE, two gradient\-merging methods that reduce interference between per\-paraphrasing gradients during instruction tuning to improve prompt robustness in large language models\.

## Sources

- [Story source](<https://arxiv.org/abs/2610.37683>)