VerifySteer selectively steers hidden states at paragraph boundaries using latent correctness signals to control verifier strictness and outperform baselines on ProcessBench and Hard2Verify with lower compute.
Hard2verify: A step-level verification benchmark for open-ended frontier math
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LLM proofs for hard math problems show large differences in quality metrics like conciseness and cognitive simplicity that correctness-only tests miss, along with trade-offs between quality and correctness.
An interactive AI workbench for mathematicians achieves 48% on FrontierMath Tier 4 and helped solve open problems in early tests.
Pseudo-Formalization decomposes natural language proofs into modular blocks for independent LLM verification via Block Verification, outperforming LLM-as-judge baselines on error detection in olympiad and research math benchmarks.
citing papers explorer
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The Hidden Signal of Verifier Strictness: Controlling and Improving Step-Wise Verification via Selective Latent Steering
VerifySteer selectively steers hidden states at paragraph boundaries using latent correctness signals to control verifier strictness and outperform baselines on ProcessBench and Hard2Verify with lower compute.
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Not All Proofs Are Equal: Evaluating LLM Proof Quality Beyond Correctness
LLM proofs for hard math problems show large differences in quality metrics like conciseness and cognitive simplicity that correctness-only tests miss, along with trade-offs between quality and correctness.
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AI co-mathematician: Accelerating mathematicians with agentic AI
An interactive AI workbench for mathematicians achieves 48% on FrontierMath Tier 4 and helped solve open problems in early tests.
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Pseudo-Formalization for Automatic Proof Verification
Pseudo-Formalization decomposes natural language proofs into modular blocks for independent LLM verification via Block Verification, outperforming LLM-as-judge baselines on error detection in olympiad and research math benchmarks.