Research / Inside the model

Binary Context Sufficiency in Hidden States: Dissociating Sufficiency from Correctness in Fixed-Question, Changed-Context Multi-Hop QA

Shows that Qwen2.5-7B-Instruct hidden states linearly encode binary context sufficiency in multi-hop QA, separating sufficient from insufficient context at 0.952 AUROC on closed-book-negative examples, a signal that stays strong when correctness is held fixed.

Published
9 March 2026
Author
Ali Uyar
DOI
10.5281/zenodo.18921976
Code
github.com/aliuyar1234/binary-evidence-sufficiency-dissociation

Abstract

Context-grounded QA failures conflate at least two cases: the model may misuse evidence that is present, or the provided context may itself be insufficient. We study this distinction in fixed-question, changed-context multi-hop QA. Each HotpotQA question is converted into four controlled context variants (sufficient, sufficient-noisy, missing, misleading), and we probe hidden states at prompt end and after a short two-step reasoning prefix. The strongest supported result is binary rather than three-way. On the primary Qwen2.5-7B-Instruct run, a linear probe separates sufficient from insufficient context with 0.952 AUROC on closed-book-negative examples, and the signal remains strong when final correctness is held fixed (0.979 AUROC on correct-only and 0.939 on wrong-only closed-book-negative subsets). Title masking preserves the effect (0.936 AUROC). At the same time, prompt-end representations are at least as informative as end-of-step-2 representations, missing-vs-misleading separation remains near chance in the original three-way analysis (0.505 AUROC), and a DeepSeek-R1-Distill-Qwen-7B replication is mixed rather than confirmatory (0.803 AUROC, effectively tied with prompt end and slightly below the strongest lexical baseline). We therefore make a narrow claim: hidden states encode a coarse, correctness-dissociated context-sufficiency signal, but the current evidence does not support a richer three-way evidence-state representation or a claim that the short reasoning prefix creates the signal.

Why it matters

Context-grounded QA failures conflate evidence that is present but misused with context that is insufficient. The sufficiency signal holds on wrong answers alone (0.939 AUROC on the wrong-only closed-book-negative subset), so a probe can separate the two cases from the hidden states.

Cite

@misc{uyar2026binary,
  title     = {Binary Context Sufficiency in Hidden States: Dissociating Sufficiency from Correctness in Fixed-Question, Changed-Context Multi-Hop QA},
  author    = {Uyar, Ali},
  year      = {2026},
  doi       = {10.5281/zenodo.18921976},
  publisher = {Zenodo},
  url       = {https://doi.org/10.5281/zenodo.18921976}
}
AU-11
Cuvette in the beam: one context of the questionBeam: the HotpotQA question, held fixedTarget sufficient: cells 1, 2 (clean, harder distractors)Target insufficient: cells 3, 4 (missing, misleading)Detector: linear probe on Qwen2.5-7B-Instruct hidden statesDrum: read point · lever: CBN, correct-only, wrong-only (n/r: not reported)Mask spider: page titles masked in all four contextsThe paper holds each HotpotQA question fixed and swaps its context among four variants: sufficient, sufficient with harder distractors, one supporting paragraph removed, or one replaced by a high-overlap near-miss. On closed-book-negative (CBN) test questions, which the model cannot answer from the question alone, a linear probe on Qwen2.5-7B-Instruct hidden states separates sufficient from insufficient context with AUROC 0.958 at prompt end and 0.952 after a two-step reasoning prefix, against 0.815 for a TF-IDF lexical baseline, 0.809 for a correctness probe and 0.500 for a question-only control. The separation holds with answer correctness fixed (0.979 correct-only, 0.939 wrong-only at step 2) and with page titles masked (0.936 at step 2).