The authors built LogicTrack, which automatically formalizes each step in a chain-of-thought trajectory and checks its logical validity using automated theorem provers.
Formal logic solvers can audit and improve language-model reasoning chains
LogicTrack translates intermediate reasoning steps into symbolic form, verifies them with theorem provers, and uses the results to steer inference and fine-tuning.
Industry
Jingyu Hu · Shu Yang · Weiru Liu · Di Wang
University of Bristol · King Abdullah University of Science and Technology
Research Digest··2 min read
Thread:Agent Harness Optimization
Hu and colleagues introduce a neuro-symbolic framework for detecting logically invalid steps even when a model reaches the correct final answer.
Why this paper
From University of Bristol and King Abdullah University of Science and Technology · Part of Agent Harness Optimization, now 61 papers
In one line
LogicTrack audits reasoning trajectories with automated theorem provers, improving both verifiability and accuracy.
What we could check
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