VLP adds an NL documentation layer with trace-linked mismatch detection and derived formal checks to make human validation of LLM code feasible, lifting pass@1 from 28.7-73.2% to 65.4-93.5%.
Fewer hallucinations, more verification: A three-stage llm-based framework for asr error correction,
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2026 2verdicts
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G-SPIN uses a GNN to restrict ASR correction search to phonetic neighbors, then applies MLM local scoring and LLM re-ranking for context-aware fixes at inference time.
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Graph-Based Phonetic Error Correction of Noisy ASR
G-SPIN uses a GNN to restrict ASR correction search to phonetic neighbors, then applies MLM local scoring and LLM re-ranking for context-aware fixes at inference time.