[2607.20734] LLMs Get Lost in Evolving User Intent

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Computer Science > Machine Learning

arXiv:2607.20734 (cs)

[Submitted on 22 Jul 2026]

Title:LLMs Get Lost in Evolving User Intent

Authors:Jihoon Tack, Philippe Laban, Jennifer Neville<br>View a PDF of the paper titled LLMs Get Lost in Evolving User Intent, by Jihoon Tack and 2 other authors

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Abstract:As LLMs become more capable, they are increasingly deployed as collaborative agents, taking on user-delegated tasks through iterative interaction. Yet genuine interaction is inherently dynamic: users rarely specify their intent upfront, instead disclosing, revising, and reshaping it as the conversation unfolds. Despite this, LLMs are still predominantly evaluated or trained in single-turn, fully-specified settings, leaving open a fundamental question: how well do LLMs track and act on user intent as it evolves over the course of a conversation? To study this, we introduce a framework that transforms static, single-turn tasks into dynamic multi-turn conversations in which the user's intent evolves across turns--incrementally revealed, revised, and at times redirected mid-conversation--while preserving each task's original evaluation protocol, enabling existing benchmarks to be reused as controlled testbeds without new annotation. Across multiple tasks, we surface a consistent phenomenon: strong static-setting performance does not transfer to the evolving-intent setting, with substantial drops across model families. Our findings point to a fundamental gap: today's LLMs do not yet faithfully track and act on the user's evolving intent, a capability invisible to static evaluation yet critical for future collaborative agents.

Comments:<br>20 pages, 10 figures

Subjects:

Machine Learning (cs.LG)

Cite as:<br>arXiv:2607.20734 [cs.LG]

(or<br>arXiv:2607.20734v1 [cs.LG] for this version)

https://doi.org/10.48550/arXiv.2607.20734

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arXiv-issued DOI via DataCite (pending registration)

Submission history<br>From: Jihoon Tack [view email]<br>[v1]<br>Wed, 22 Jul 2026 21:14:44 UTC (1,802 KB)

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