Answering the Wrong Question: Reasoning Trace Inversion for Abstention in LLMs

Answering the Wrong Question: Reasoning Trace Inversion for Abstention in LLMs | Signal Canvas | ScienceToStartup

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Canonical route: /signal-canvas/answering-the-wrong-question-reasoning-trace-inversion-for-abstention-in-llms

stale

Proof freshness: stale
Proof status: unverified
Display score: 7/10
Last proof check: 2026-04-03
Score updated: 2026-04-03
Score fresh until: 2026-05-03
References: 0
Source count: 0
Coverage: 33%

This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.

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Canonical ID answering-the-wrong-question-reasoning-trace-inversion-for-abstention-in-llms | Route /signal-canvas/answering-the-wrong-question-reasoning-trace-inversion-for-abstention-in-llms

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curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/answering-the-wrong-question-reasoning-trace-inversion-for-abstention-in-llms

MCP example

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source_context

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  "query": "Answering the Wrong Question: Reasoning Trace Inversion for Abstention in LLMs",
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  "paper_ref": "answering-the-wrong-question-reasoning-trace-inversion-for-abstention-in-llms",
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  "benchmark_ref": null,
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Evidence Receipt

Route status: building

Claims: 7

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: Answering the Wrong Question: Reasoning Trace Inversion for Abstention in LLMs

PDF: https://arxiv.org/pdf/2604.02230v1

Source count: Pending verification

Coverage: 33%

Last proof check: 2026-04-03T20:50:40.241Z

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Watch and verify: Answering the Wrong Question: Reasoning Trace Inversion for Abstention in LLMs

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Subject: Answering the Wrong Question: Reasoning Trace Inversion for Abstention in LLMs

Verdict

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Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.

Preparing verified analysis

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Claim map

Strong 7Mixed 0Weak 0

Evidencepartial
reasoning models have been shown to have worse abstention abilities
Implicationpartial
Directly stated in abstract as a known vulnerability of reasoning models
Verificationpartial
partial
Evidencepartial
Hallucinations resulting in failed abstention can be reinterpreted as LLMs answering the wrong question (rather than answering a question incorrectly)
Implicationpartial
Explicitly stated in abstract as the core conceptual framework
Verificationpartial
partial
Evidencepartial
we develop a new class of state-of-the-art abstention methods called Trace Inversion
Implicationpartial
Directly stated in abstract with strong performance claims
Verificationpartial
partial
Evidencepartial
First, we generate the reasoning trace of a model. Based on only the trace, we then reconstruct the most likely query that the model responded to. Finally, we compare the initial query with the reconstructed query.
Implicationpartial
Explicitly described step-by-step in abstract with clear methodology
Verificationpartial
partial
Evidencepartial
Low similarity score between the initial query and reconstructed query suggests that the model likely answered the question incorrectly and is flagged to abstain
Implicationpartial
Directly stated as the core mechanism of the method
Verificationpartial
partial
Evidencepartial
Extensive experiments demonstrate that Trace Inversion effectively boosts abstention performance in four frontier LLMs across nine abstention QA datasets
Implicationpartial
Directly stated in abstract with specific scope and positive results
Verificationpartial
partial
Evidencepartial
beating competitive baselines in 33 out of 36 settings
Implicationpartial
Explicit numeric result stated in abstract with clear superiority claim
Verificationpartial
partial

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Answering the Wrong Question: Reasoning Trace Inversion for Abstention in LLMs

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