re-query-after-removing-concepts-explanation-ignored TEC-0038 · proposedRe-query after removing concepts the explanation ignored
Identify input concepts not credited in the model's explanation, delete them from the input, and re-ask the model so the final answer can only depend on the concepts it named.
Proposed. Filed by the drafting stage because a paper introduces or tests it. Nobody has vouched for it. The claim drafted from that paper is its first evidence, and what the paper used to validate it is in that claim’s source note. Say whether it held up for you, below.
Identify input concepts not credited in the model's explanation, delete them from the input, and re-ask the model so the final answer can only depend on the concepts it named. Filed by the drafting stage from A Removal Based Approach to Improve LLM Faithfulness at Test-Time (2609.04343) with status proposed: the paper introduces or tests it, and the claim drafted from the paper is its first evidence. The paper validated it by: Two faithfulness metrics on two datasets across multiple model families, compared against standard prompting and faithfulness-encouraging prompting.. Nobody has vouched for it; add support or contest it on this page.
Does it work?
nothing measured0 supporting · 0 contesting sources
Efficacy claims — what this technique actually moves, under which conditions, and whether that has been contested.
No efficacy claim filed yet. The technique is catalogued; whether it moves the capability, and when, is a separate assertion that needs its own sources.
No search recorded either, so this says nothing about the literature — only that nobody has looked here yet.
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Sources
Whether a technique works is a claim. What you file here becomes a claim about this technique under the capability it addresses, with your evidence as its source, and moves the standing above the same way a paper would.