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标题: "Decomposition-Induced Context-Memory Conflict: When Fact-Checking Pipelines Contradict Their Own Source Text"
原文链接: "https://arxiv.org/abs/2608.10627"
发布日期: "2026-08-11"
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---

## Computer Science > Computation and Language

## Title:Decomposition-Induced Context-Memory Conflict: When Fact-Checking Pipelines Contradict Their Own Source Text

Authors:[Yu-Feng Yen](https://arxiv.org/search/cs?searchtype=author&query=Yen,+Y)

[View PDF](https://arxiv.org/pdf/2608.10627) [HTML (experimental)](https://arxiv.org/html/2608.10627v1)

> Abstract:Decompose-then-verify pipelines, including FActScore-style fact-checkers and long-form factuality evaluators, first split a passage into atomic claims before checking each one. Decomposition itself is treated as a neutral preprocessing step. We show it is not: a decomposer can be induced to substitute its own parametric belief for what the source passage says, producing a claim that contradicts the text it was supposed to summarize faithfully. We call this Decomposition-Induced Context-Memory Conflict (DI-CC) and show it is mechanistically the same phenomenon as classical context-memory conflict, occurring inside a different pipeline stage than prior work has examined. A linear probe trained only on classical context-memory conflict data (NQ-Swap), never exposed to any decomposition output, significantly separates decomposition positions that produce DI-CC from faithful decompositions (AUC = 0.86-0.88, permutation p < 0.0005). An existing reference-free baseline, SelfCheckGPT-style self-consistency sampling, fails to detect DI-CC at all (AUC 0.51, chance-level), because DI-CC content is stably recoverable and recurs across resamples, unlike the variability self-consistency methods rely on. Context-aware decoding, a training-free mitigation from the classical setting, transfers to decomposition and suppresses DI-CC, but at a severe cost: many decompositions under coreference-heavy conditions fail to parse, often because the decomposer fabricates a different identity. We do not consider this mitigation deployment-ready. We further characterize the mechanism's boundaries: its natural occurrence rate is too sparss not manifest on naturally-occurring hallucinatedtext, and it requires a minimum model scale to detecablish DI-CC as a real, mechanistically grounded, andpartially treatable failure mode, with a scope we chhan overstate.

| Comments: |  |
| --- | --- |
| Subjects: | Computation and Language (cs.CL) |
| ACM classes: | I.2.7 |
| Cite as: | [arXiv:2608.10627](https://arxiv.org/abs/2608.10627) \[cs.CL\] |
|  | (or [arXiv:2608.10627v1](https://arxiv.org/abs/2608.10627v1) \[cs.CL\] for this version) |
|  | [https://doi.org/10.48550/arXiv.2608.10627](https://doi.org/10.48550/arXiv.2608.10627) |

## Submission history

From: Yu-Feng Yen \[[view email](https://arxiv.org/show-email/f680e4e1/2608.10627)\]  
**\[v1\]** Tue, 11 Aug 2026 08:15:05 UTC (51 KB)

[Which authors of this paper are endorsers?](https://arxiv.org/auth/show-endorsers/2608.10627) | Disable MathJax ([What is MathJax?](https://info.arxiv.org/help/mathjax.html))
