Discover and Prove: An Open-source Agentic Framework for Hard Mode Automated The

arXiv:2603.19828v1 Announce Type: new Abstract: Autoformalization aims to translate natural-language mathematics into compilable, machine-checkable statements. However, semantic

arXiv:2603.19715v1 Announce Type: new Abstract: Formal verification via interactive theorem proving is increasingly used to ensure the correctness of critical systems, yet

arXiv:2604.08590v1 Announce Type: cross Abstract: We present AlphaLab, an autonomous research harness that leverages frontier LLM agentic capabilities to automate the full

arXiv:2605.15871v1 Announce Type: new Abstract: Toward recursive self-improvement, we investigate LLM agents autonomously designing foundation models beyond standard Transformers.

arXiv:2610.21581v1 Announce Type: new Abstract: Mathematical agents are commonly evaluated by answer accuracy or proof acceptance. We introduce ClaimScope, a 72-task benchmark for

arXiv:2605.23772v1 Announce Type: new Abstract: Agentic systems have recently emerged as state-of-the-art approaches for automated theorem proving in formal mathematics. To assess

arXiv:2608.28433v2 Announce Type: new Abstract: Proof assistants such as Lean 4 promise the paradigm of formally verified mathematics, but large-scale formalization projects have

arXiv:2609.25575v1 Announce Type: new Abstract: Fine-tuned Large Language Models (LLMs) significantly advance Automated Theorem Proving (ATP), but are often deployed as guiding