From the 1 of 5 linked papers with an AI index.
5 papers
Verifiable Checks for Business Rule Consistency
Joseph Tafese, Milad Hooshyar, Sam Bayless +2
Maintaining consistency between natural language documentation of business rules and their evolving internal implementations is a significant challenge in large-scale systems. We p…
A Neurosymbolic Approach to Natural Language Formalization and Verification
Chenyang An, Sam Bayless, Stefano Buliani +27
The paper presents ARc, a system that combines large language models with automated reasoning to formally translate natural‑language policies and verify their logical correctness,…
VERGE: Formal Refinement and Guidance Engine for Verifiable LLM Reasoning
Vikash Singh, Darion Cassel, Nathaniel Weir +2
Despite the syntactic fluency of Large Language Models (LLMs), ensuring their logical correctness in high-stakes domains remains a fundamental challenge. We present a neurosymbolic…
ReSyn: Autonomously Scaling Synthetic Environments for Reasoning Models
Andre He, Nathaniel Weir, Kaj Bostrom +4
Reinforcement learning with verifiable rewards (RLVR) has emerged as a promising approach for training reasoning language models (RLMs) by leveraging supervision from verifiers. Al…
VeriCoT: Neuro-symbolic Chain-of-Thought Validation via Logical Consistency Checks
Yu Feng, Nathaniel Weir, Kaj Bostrom +5
LLMs can perform multi-step reasoning through Chain-of-Thought (CoT), but they cannot reliably verify their own logic. Even when they reach correct answers, the underlying reasonin…