Entity · technique

symbolic verifier outputs

techniqueactivesymbolic-verifier-outputs-57e7b26e·1 events·first seen May 28, 2026

Aliases: symbolic verifier outputs

Co-occurring entities

Multimodal Large Language Models multimodal meta-verification decoupled reinforcement learning M1-TTS symbolic meta-verification bounding box symbolic rationales rule-based reinforcement learning rewards OmniVerifier-M1

More like this (12)

symbolic meta-verification verifiers reinforcement learning from verifier feedback Prover-Verifier Games Verilog-Eval Self-Trained Verification (STV)execution-based verification multimodal meta-verification LLM-as-a-Verifier selective-verification layer token-wise self-certainty Partially Correlated Verifier Cascades in LLM Harnesses: Concave Log-Odds, Polynomial Reliability, and Blind-Spot Ceilings

Recent events (1)

6arXiv · cs.AI·May 28, 2026·source ↗

OmniVerifier-M1: Multimodal Meta-Verifier with Explicit Structured Recalibration

OmniVerifier-M1 is a generalist visual verifier trained using symbolic meta-verification rationales (e.g., bounding boxes) and decoupled reinforcement learning objectives for binary judgment versus meta-verification. The paper finds that symbolic verifier outputs outperform textual explanations as rationales, enabling rule-based RL rewards without auxiliary judge models, and that decoupling RL objectives substantially improves performance over joint optimization. The system further enables M1-TTS, a verifier-driven agentic generation pipeline supporting dynamic region-level self-correction in multimodal outputs.

Evaluation and Benchmarking Agent and Tool Ecosystem Multimodal Large Language Models multimodal meta-verification decoupled reinforcement learning +8 more