Author

Hongjin Song

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#artificial intelligence Preprint Sep 2026

REVE: Efficient Hallucination Correction for Large Audio-Language Models via Reused Encoder States

Large audio-language models may mention acoustic events that are absent from the input. A separate audio event detector can verify these mentions, but doing so requires a second audio encoder and a separate forward pass. We propose Reused Encoder States for Verifying Events (REVE), a lightweight method that uses states...

Hong-Jin Song, Ji-Shen Kuang, Xin-Yu Yang et al. · 0 citations

Preprint Aug 2026

Likelihood-Constrained Acoustic Reranking for Training-Free Hallucination Mitigation in LLM-Based ASR

Large language model (LLM)-based automatic speech recognition (ASR) systems achieve strong performance on conventional speech data by leveraging powerful linguistic priors and multilingual capabilities. However, under challenging conditions, these priors can override acoustic evidence, resulting in unintended translati...

Ji-Shen Kuang, Lin-Ru Zheng, Hong-Jin Song et al. · 0 citations