---
title: 'LLMs Get Lost In Multi-Turn Conversation'
license: CC-BY-4.0
license_url: https://creativecommons.org/licenses/by/4.0/
license_note: 'paper is CC BY 4.0 (verified on arXiv abs page 2026-11-11; icon by-4.0.png, http://creativecommons.org/licenses/by/4.0/); note is our own summary'
source: https://iinventedlight.com/library/notes/2505-06120-llms-lost-in-multiturn.md
source_license: 'CC BY 4.0'
attribution: 'Summary by iinventedlight (AI-assisted). Source: Philippe Laban, Hiroaki Hayashi, Yingbo Zhou, Jennifer Neville, LLMs Get Lost In Multi-Turn Conversation (CC BY 4.0).'
author: 'iinventedlight (AI-assisted)'
date: 2026-11-11
status: published
approved_by: "Cole Withington, 2026-11-11 20:07 PT, Librarian chat widget t1715u: \"okay you can publish the ones you're comfortable with\""
checked_on: 2026-11-11
as_of: 2026-11-11
confidence: medium
untested: 'Not reproduced. Abs page and HTML key sections read 2026-11-11. Named code URLs checked for HTTP 200; code not run.'
category: arxiv
topic_area: 'ai-research: agent memory and context compaction'
tags: agents, memory, compaction, arxiv
arxiv_id: 2505.06120
alias: 2505.06120-llms-lost-in-multiturn
sources:
  - id: S1
    title: 'LLMs Get Lost In Multi-Turn Conversation'
    publisher: arXiv
    authors: 'Philippe Laban, Hiroaki Hayashi, Yingbo Zhou, Jennifer Neville'
    url: https://arxiv.org/abs/2505.06120
    version_read: 'v1 (9 May 2025)'
    accessed: 2026-11-11
    license: 'CC BY 4.0'
---
# LLMs Get Lost In Multi-Turn Conversation

## Summary
The top open- and closed-weight LLMs tested exhibit significantly lower performance in multi-turn conversations than single-turn, with an average drop of 39% across six generation tasks. The 15 LLMs tested perform much worse in multi-turn settings (-35%), explained by some loss in aptitude, and large losses in reliability. When LLMs take a wrong turn in a conversation, they get lost and do not recover. [S1]

## Claims
- id: C1
  claim: 'They report an average 39% drop across six generation tasks.'
  source: S1
  evidence: "an average drop of 39% across six generation tasks"
- id: C2
  claim: 'They report that 15 models perform much worse in multi-turn settings.'
  source: S1
  evidence: "The 15 LLMs we test perform much worse in multi-turn settings (-35%)"
- id: C3
  claim: 'A public Microsoft repository name appears in the HTML.'
  source: S1
  evidence: "Microsoft/lost_in_conversation"

## Verification
- Code available: HTML points to https://github.com/Microsoft/lost_in_conversation (HTTP 200 on 2026-11-11) and https://huggingface.co/datasets/Microsoft/lost_in_conversation (HTTP 200). Not run.
- Reproduced: not reproduced (2026-11-11). Code not run.
- Related work: Live note ao-context-long-context-limits. This paper is about multi-turn conversation, not compaction, but it is a core context-use result for agents that talk over many turns.
- Limits: Results are from simulated sharded conversations, not live users. The paper also reports a -35% multi-turn figure for the 15 models tested; both figures are author-reported and refer to slightly different summaries in the text.
- License: CC BY 4.0 on the abs page (2026-11-11; icon by-4.0.png; http://creativecommons.org/licenses/by/4.0/). Submitted 9 May 2025 (v1). Sources: [S1] https://arxiv.org/abs/2505.06120, v1 (9 May 2025). checked_on: 2026-11-11.

## When to apply
Use when asking why an assistant degrades over a back-and-forth chat, even if it can solve the same task when the request is fully specified up front.

## Facts
- id: F1
  claim: 'The authors report an average 39% drop from single-turn to multi-turn performance across six generation tasks.'
  confidence: medium
  date: 2026-11-11
  sources: [S1]
  license: CC BY 4.0
- id: F2
  claim: 'They report that 15 tested models perform much worse in multi-turn settings, described as a 35% drop, with larger losses in reliability than in aptitude.'
  confidence: medium
  date: 2026-11-11
  sources: [S1]
  license: CC BY 4.0
- id: F3
  claim: 'In one summary, multi-turn underspecified conversations reached 65% against single-turn 90%.'
  confidence: medium
  date: 2026-11-11
  sources: [S1]
  license: CC BY 4.0

## Sources
- [S1] arXiv 2505.06120, https://arxiv.org/abs/2505.06120. License: CC BY 4.0. v1 (9 May 2025). Accessed 2026-11-11.

License: this note is CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Summary by iinventedlight (AI-assisted). Paper is CC BY 4.0.

---

Agents: [/agents.md](/agents.md) | [/.well-known/agent-library.json](/.well-known/agent-library.json).