DeltaLogic: Minimal Premise Edits Reveal Belief-Revision Failures in Logical Reasoning Models
Amit Dhanda

TL;DR
DeltaLogic introduces a benchmark to evaluate how well language models revise beliefs after minimal premise edits, revealing that strong initial reasoning does not guarantee reliable belief revision.
Contribution
The paper presents DeltaLogic, a new benchmark protocol for assessing belief revision in language models through minimal premise edits, highlighting limitations in current models' reasoning capabilities.
Findings
Stronger initial reasoning does not ensure better belief revision.
Qwen3-1.7B shows inertia in belief revision, with 0.600 inertia on episodes requiring change.
Phi-4-mini-instruct performs better but still exhibits control instability.
Abstract
Reasoning benchmarks typically evaluate whether a model derives the correct answer from a fixed premise set, but they under-measure a closely related capability that matters in dynamic environments: belief revision under minimal evidence change. We introduce DeltaLogic, a benchmark transformation protocol that converts natural-language reasoning examples into short revision episodes. Each episode first asks for an initial conclusion under premises P, then applies a minimal edit {\delta}(P), and finally asks whether the previous conclusion should remain stable or be revised. We instantiate DeltaLogic from FOLIO and ProofWriter and evaluate small causal language models with constrained label scoring. On a completed 30-episode Qwen evaluation subset, stronger initial reasoning still does not imply stronger revision behavior: Qwen3-1.7B reaches 0.667 initial accuracy but only 0.467 revision…
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