# When Models Decide and When They Bind: A Two-Stage Computation for Multiple-Choice Question-Answering

Source: [When Models Decide and When They Bind: A Two-Stage Computation for Multiple-Choice Question-Answering](<https://www.sota2.com/research/paper/695f39ea53fdd5c361743ec1>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2026-01-09T05:00:05.326Z

Authors: Hugh Mee Wong, Rick Nouwen, Albert Gatt

Published: 2026-01-07T13:27:48.000Z

## Abstract

Multiple-choice question answering (MCQA) is easy to evaluate but adds a meta-task: models must both solve the problem and output the symbol that \*represents\* the answer, conflating reasoning errors with symbol-binding failures. We study how language models implement MCQA internally using representational analyses (PCA, linear probes) as well as causal interventions. We find that option-boundary (newline) residual states often contain strong linearly decodable signals related to per-option correctness. Winner-identity probing reveals a two-stage progression: the winning \*content position\* becomes decodable immediately after the final option is processed, while the \*output symbol\* is represented closer to the answer emission position. Tests under symbol and content permutations support a two-stage mechanism in which models first select a winner in content space and then bind or route that winner to the appropriate symbol to emit.

## Recorded benchmark results

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## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2601.03914>)

[PDF](<https://arxiv.org/pdf/2601.03914.pdf>)