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Research questionHow can language models perform complex logical reasoning without accumulating token-level errors?Autoregressive language models generate reasoning one token at a time, so early mistakes can compound and likely conclusions can be treated as necessary ones. This linear representation also makes complex inference structures difficult to maintain.
AI
Machine Learning
Natural Language Processing
Reasoning
Research Paper
Technology
Latest papersRecent research connected to this question, newest first.DODR: Deterministic Operator-Driven Reasoning in Latent SpaceThe source presents DODR, which represents semantic units as snapshot vectors and applies deterministic matrix operators for deduction, induction, and abduction in reasoning graphs. Evidence comes from 503 records, including 420 deduplicated samples, across dedicated and end-to-end experiments, with reported cross-domain deduction and abduction results.research paper · Sep 4, 2026
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