arXiv:2606. 31878v1 Announce Type: cross Abstract: We investigate two approaches for extending CEGAR-tableaux with SAT-shortcuts using a previously known approach called RECAR but also a totally new approach using the modal resolution theorem prover KSP as an oracle.
arXiv:2509. 00930v2 Announce Type: replace Abstract: Large language models (LLMs) exhibit strong general reasoning, yet the community lacks controllable, scalable, and verifiable tools to analyze and improve these abilities.
arXiv:2607. 00815v1 Announce Type: cross Abstract: SAT solvers settle combinatorial problems beyond the reach of interactive theorem provers and produce LRAT certificates for independent verification.
arXiv:2606. 12594v1 Announce Type: new Abstract: Modern Lean theorem provers achieve strong performance only with substantial training and inference compute, driven in part by scarce verified proof data and the long reasoning traces of formal proof search, making both supervised fine-tuning (SFT) and sampling expensive.
The paper introduces LinguaArray, a framework that uses large language models (LLMs) to suggest a small set of focal ground terms or constraints—called a Semantic Focus Set—in quantified array SMT solving. The LLM’s suggestions are then verified by a conventional SMT solver, which remains the sole source of proof. Experiments on 1,015 SMT-LIB instances show that LinguaArray solves up to 69.1% of cases and increases the number of solved instances by 105%–397% compared to the backends alone.
arXiv:2606. 09450v1 Announce Type: new Abstract: LLMs have recently achieved strong results on formal proving benchmarks.
arXiv:2609.38409v1 Announce Type: new Abstract: Recent progress in large language model reasoning has been driven by benchmarks and reinforcement learning environments with automatically verifiable r...
arXiv:2608.28639v1 Announce Type: new Abstract: Formal theorem proving with large language models remains challenging due to the difficulty of navigating large proof search spaces efficiently. Existi...
arXiv:2606. 09278v1 Announce Type: cross Abstract: Large Language Models frequently hallucinate in precision-critical domains such as technical diagramming and mechanical design, where outputs must satisfy strict geometric constraints.
arXiv:2606. 06656v1 Announce Type: new Abstract: We study parallel Continuous Local Search (CLS) as a solution approach for Boolean satisfiability problems with symmetric pseudo-Boolean (PB) constraints.
NanoProof is the first factorized execution‑guided theorem prover in Lean 4 whose training data, tooling, pipeline, and weights are all publicly released, enabling end‑to‑end reproducibility with open‑source resources. The authors provide a dataset of structured proof trees and a programmatic interaction tool for Lean 4, emphasizing compute efficiency to make training and evaluation more accessible. NanoProof achieves a 50.8% pass@16 on MiniF2F‑Test, outperforming comparable systems while using far less compute, demonstrating that such provers can be rebuilt from scratch with modest resources.
arXiv:2607. 17047v1 Announce Type: cross Abstract: LLM constraint reasoners are often evaluated near the random-SAT phase transition, confounding density and solver hardness.