arXiv AI
Jun 24
Cryptographic certificates of validity for trustworthy AI
arXiv:2606. 23768v1 Announce Type: cross Abstract: We propose cryptographic certificates of validity for agentic AI systems.
IsabeLLM: Automated Theorem Proving Applied to Formally Verifying Consensus
arXiv:2606. 18098v1 Announce Type: new Abstract: Advances in Artificial Intelligence (AI) have led AI for Theorem Proving to become a promising means of formally verifying computer systems.
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arXiv Machine Learning
Jun 19
Pseudo-Formalization for Automatic Proof Verification
arXiv:2605. 20531v2 Announce Type: replace-cross Abstract: Reliable verification of proofs remains a bottleneck for training and evaluating AI systems on hard mathematical reasoning.
arXiv AI
Jul 13
OpenProver: Agentic and Interactive Theorem Proving with Lean 4
arXiv:2607. 09217v1 Announce Type: new Abstract: In this system paper, we present OpenProver, an open-source system for LLM-driven automated theorem proving (ATP) with integrated Lean 4 formal verification.
arXiv AI
5d ago
Vero: Can AI Agents Build Formally Verified Software Repositories?
arXiv:2608. 13522v1 Announce Type: cross Abstract: AI agents are increasingly used for programming, but do not provide any guarantee on the correctness of generated code.
Hugging Face Trending Papers
6d ago
Vero: Can AI Agents Build Formally Verified Software Repositories?
AI agents are increasingly used for programming, but do not provide any guarantee on the correctness of generated code. Verified code generation, in which an agent produces both an implementation and a machine-checked proof of its specification, offers a stronger path toward trustworthy AI-generated software.
arXiv AI
Jul 8
Harnessing Code Agents for Automatic Software Verification
arXiv:2607. 06341v1 Announce Type: cross Abstract: Formal verification offers the strongest guarantee of software correctness, but it does not scale: the proofs demanded by interactive theorem provers such as Coq require enormous expert effort.
arXiv Machine Learning
Jun 11
SEDULity: A Proof-of-Learning Framework for Distributed and Secure Blockchains with Efficient Useful Work
arXiv:2512. 13666v2 Announce Type: replace-cross Abstract: The security and decentralization of Proof-of-Work (PoW) have been well-tested in existing blockchain systems.
arXiv AI
Jun 16
Mask-Proof: An LLM-based Automated Data Curation Pipeline on Mathematical Proofs
arXiv:2606. 15258v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly capable of mathematical problem solving and can even assist with research-level proofs, yet we still lack a scalable and reproducible way to measure step-level reasoning in long proofs across diverse sources.
Hugging Face Trending Papers
Jul 7
Harnessing Code Agents for Automatic Software Verification
Formal verification offers the strongest guarantee of software correctness, but it does not scale: the proofs demanded by interactive theorem provers such as Coq require enormous expert effort. Large language models (LLMs) promise to generate these proofs automatically, yet existing approaches wire a fixed, human-designed proof strategy into the system and constrain the model to follow it (retrieving premises and predicting tactics one step at a time, or splitting goals by divide-and-conquer), and still prove only a fraction of their target theorems.
arXiv AI
Jun 16
SorryDB: Can AI Provers Complete Real-World Lean Theorems?
arXiv:2603. 02668v2 Announce Type: replace Abstract: We present SorryDB, a dynamically-updating benchmark of open Lean tasks drawn from 78 real world formalization projects on GitHub.
arXiv AI
Jun 2
Automated Conjecture Resolution with Formal Verification
arXiv:2604. 03789v2 Announce Type: replace-cross Abstract: Recent advances in large language models have significantly improved their ability to perform mathematical reasoning, extending from elementary problem solving to increasingly capable performance on research-level problems.
arXiv Machine Learning
Jun 26
Theory-Scale Auto-Formalization of Logics for Computer Science
arXiv:2606. 26525v1 Announce Type: new Abstract: Auto-formalization is critical for scalable formal verification, but existing progress largely focuses on isolated statements, while theory-scale auto-formalization, which coherently translates hundreds of interdependent definitions, lemmas, and theorems, remains open due to challenges in consistency, faithfulness, scalability, and correctness.