AIBullisharXiv – CS AI · Jun 257/10
🧠Researchers have developed the first formal convergence theorem for LLM-Verifier systems, proving that multi-stage software verification pipelines will reach completion with guaranteed termination. The 4/δ bound provides a precise latency prediction model validated across 90,000+ empirical trials, replacing heuristic approaches with mathematically rigorous resource planning for safety-critical applications.
AIBullisharXiv – CS AI · Jun 237/10
🧠Researchers propose ARTS (Agentic Reasoning for Tree Search), a novel approach using language models to automate scientific discovery by intelligently navigating hypothesis and experiment spaces. The method outperforms existing algorithms by 15.3% and enables smaller models like Qwen3-4B to match frontier AI systems at a fraction of the computational cost.
🧠 Gemini
AIBullisharXiv – CS AI · May 297/10
🧠Researchers used large language models and evolutionary search to create the first domain-independent heuristics for symbolic AI planning that surpass hand-engineered baselines. These evolved heuristics, written in C++, solve more planning tasks than existing state-of-the-art approaches and maintain the soundness guarantees of traditional planners.
AIBullishOpenAI News · Feb 27/105
🧠Researchers have developed a neural theorem prover for Lean that successfully solved challenging high-school mathematics olympiad problems, including those from AMC12, AIME competitions, and two problems adapted from the International Mathematical Olympiad (IMO). This represents a significant advancement in AI's ability to handle formal mathematical reasoning and proof generation.
AINeutralarXiv – CS AI · Jun 235/10
🧠This paper addresses ABox abduction in description logic EL_bot by investigating hypotheses that satisfy multiple desired properties simultaneously under repair semantics. The research demonstrates that combining signature restrictions with optimality criteria often does not increase computational complexity, advancing the theoretical foundations of knowledge base repair.
AINeutralarXiv – CS AI · Jun 56/10
🧠LeanMarathon introduces a multi-agent system that automates the formalization of research mathematics in Lean, solving long-horizon verification challenges through an evolving blueprint architecture. The system successfully formalized seven theorems across recent research papers spanning four Erdős problems without requiring manual verification shortcuts, demonstrating progress toward reliable AI co-mathematics.
AINeutralarXiv – CS AI · Jun 26/10
🧠Researchers have developed a novel method using large language models and evolutionary algorithms to automatically generate admissible heuristics for optimal classical planning problems. Unlike existing learned heuristics that improve search speed but cannot guarantee optimal solutions, this approach preserves A* optimality guarantees while matching or exceeding the performance of traditional domain-independent methods.
AINeutralarXiv – CS AI · May 276/10
🧠Researchers have introduced ORCA, an AI copilot system designed to make causal analysis accessible to domain experts across manufacturing, medicine, and social science. The tool automates root cause analysis workflows while allowing users to control the level of automation, from fully automatic to highly guided execution, addressing a significant accessibility gap in complex analytical methods.
🏢 Microsoft
AINeutralarXiv – CS AI · May 276/10
🧠A academic position paper advocates for logical pluralism in formal reasoning systems, arguing that multiple non-classical logics should coexist within unified meta-logical frameworks like LogiKEy rather than relying on single foundational logics. The research draws from two decades of work embedding diverse logics in classical higher-order logic, positioning logical pluralism as essential for interdisciplinary knowledge representation and reasoning in computational systems.
AINeutralarXiv – CS AI · May 125/10
🧠Cplus2ASP Version 2 is a new system that translates action language C+ into answer set programming, offering significant performance improvements over the Causal Calculator through modern ASP solving techniques. The tool supports incremental execution, external atoms via Lua integration, and extensible translations for other action languages, making it relevant for automated reasoning and planning applications.
AIBullisharXiv – CS AI · May 116/10
🧠Researchers present an end-to-end framework that uses Large Language Models to convert natural language specifications into PDDL planning models, with iterative refinement through hardcoded and dynamic agents, then generates executable plans. The system demonstrates strong performance across multiple domains including classic planning problems where LLMs typically struggle, and integrates with established planning engines.
🧠 Gemini
AINeutralarXiv – CS AI · Apr 206/10
🧠Researchers propose DeepInsightTheorem, a framework that teaches large language models to improve informal theorem proving by explicitly extracting and learning core mathematical techniques. The hierarchical dataset combined with a multi-stage training strategy enables LLMs to perform more insightful mathematical reasoning, outperforming existing baseline approaches on challenging benchmarks.
AIBullisharXiv – CS AI · Mar 176/10
🧠Researchers propose a new framework that uses LLMs as code generators rather than per-instance evaluators for high-stakes decision-making, creating interpretable and reproducible AI systems. The approach generates executable decision logic once instead of querying LLMs for each prediction, demonstrated through venture capital founder screening with competitive performance while maintaining full transparency.
🧠 GPT-4
AIBullisharXiv – CS AI · Mar 166/10
🧠Researchers introduce Delta1, a framework that integrates automated theorem generation with large language models to create explainable AI reasoning. The system combines formal logic rigor with natural language explanations, demonstrating applications across healthcare, compliance, and regulatory domains.
AIBullishOpenAI News · Sep 76/105
🧠The article discusses the application of generative language models to automated theorem proving, representing an advancement in AI's ability to generate mathematical proofs. This development could enhance AI systems' reasoning capabilities and formal verification processes.
AINeutralarXiv – CS AI · Mar 54/10
🧠Researchers developed a new self-supervised Inductive Logic Programming approach called Poker that can learn recursive logic programs without requiring expert-crafted negative examples or problem-specific background theories. The system automatically generates and labels new training examples during learning, showing improved performance over existing methods when negative examples are unavailable.
AINeutralarXiv – CS AI · Mar 24/106
🧠Researchers introduce pact, a new SMT model counter that can handle hybrid formulas containing both discrete and continuous variables using hashing-based approximate counting. The tool significantly outperforms existing baselines, successfully processing 456 out of 3119 test instances compared to only 83 for the baseline method.
AINeutralarXiv – CS AI · Mar 24/107
🧠Researchers have developed an automation approach for Input/Output (I/O) Logics, a type of deontic logic used for reasoning about norms and obligations, by reducing them to propositional satisfiability problems. A prototype implementation called 'rio' (reasoner for input/output logics) has been created to demonstrate these procedures with practical examples.
