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Notes on verification
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Cogentic: Multi-Agent Orchestration for Automated Proof Discovery
The preprint describes an orchestrator that assigns independent provers to competing proof directions, uses specialized adversarial verification components, and promotes confirmed intermediate results into a persistent…
NNV3: Expanding Neural Network Verification to New Architectures and Domains
The preprint presents NNV3, a MATLAB framework for formal verification of neural networks. It describes ModelStar for weight perturbation, VolumeStar for video and 3D inputs, GraphStar for graph neural networks…
How Do Agent Harnesses Create Value? Planning Information and Release Control in Stateful LLM Agents
Across 265 matched cells in Retail experiments and an Airline pilot in τ²-bench, the paper compares task-specific plans with shuffled text, and evaluates a read-only terminal verifier. It reports a 7.17-point…
Falsifiable Commitment Planning for Self-Correcting Web Agents
Researchers propose a new framework called FCPAgent for web agents to ensure they stay on track during long-term planning. The framework represents each plan step as a Falsifiable Commitment Unit (FCU) that includes…
Partially Correlated Verifier Cascades in LLM Harnesses: Concave Log-Odds, Polynomial Reliability, and Blind-Spot Ceilings
The text presents a new theory for partially correlated verifier cascades in LLM harnesses (a system used to verify candidate answers). The theory provides insights into the growth and decay of failure rates, the…
Evidence-Grounded Verified Agentic Reasoning: A Path Toward Eliminating LLM Hallucination in Empirical Inference via Tool-Attested Kernel Proofs
The paper introduces EG-VAR, a tool-calling architecture that aims to make the reasoning of a large language model (LLM) more trustworthy by verifying all outputs through tool-attestation axioms and kernel checks. The…
Physics-Audited Agentic Discovery in Scientific Machine Learning
The paper introduces Physics-Audited Agentic Scientific Machine Learning (PA-SciML), a new workflow that verifies the accuracy of surrogate models discovered by large language model agents in scientific machine…
Harnessing Code Agents for Automatic Software Verification
The authors propose a new method for automatic software verification using large language models (LLMs) in the form of 'code agents'. Instead of wireting a fixed proof strategy, they allow the code agent to choose its…
LLM-as-a-Verifier: A General-Purpose Verification Framework
The paper introduces LLM-as-a-Verifier, a general-purpose verification framework that provides fine-grained feedback to improve the accuracy of agentic tasks. The framework scales across multiple dimensions for better…
LLM-as-a-Verifier: A General-Purpose Verification Framework
In this research, a general-purpose verification framework called LLM-as-a-Verifier is introduced. This framework provides detailed feedback for agentic tasks without requiring additional training. The framework…
Theoria: Rewrite-Acceptability Verification over Informal Reasoning States
Theoria is a verification architecture proposed by Ben Slivinski and Michael Saldivar that aims to close the gap between formal proof assistants and scalar LLM judges in determining when an AI system's answer can be…
AxDafny: Agentic Verified Code Generation in Dafny
Researchers present AxDafny, a framework for generating executable code and proof artifacts in Dafny using a verifier-guided repair method. The study uses a benchmark called LiveCodeBench-Pro-Dafny with 250 programming…
Bayesian control for coding agents
The paper proposes a Bayesian controller for coding agents that make decisions based on a belief over candidate correctness, rather than fixed rules. This method is found to be most useful when verification is costly…
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