As Multimodal Large Language Models (MLLMs) expand the scope of retrieval-augmented generation, recommendation, and multimedia search, audio retrieval is expected to become a dependable retrieval component. Yet existing systems struggle to reconcile lexical precision, non-verbal acoustic evidence, and efficient, transp...
Haoyu Li, Yuzhe Bai, Li Niu· Proceedings of the 32nd ACM...· 0 citations
The results of R2M-Bench support same-rollout relative calibration as a practical way to distinguish revisit-specific consistency from generic temporal stability.
As Multimodal Large Language Models (MLLMs) expand the scope of retrieval-augmented generation, recommendation, and multimedia search, audio retrieval is expected to become a dependable retrieval component. Yet existing systems struggle to reconcile lexical precision, non-verbal acoustic evidence, and efficient, transp...
Haoyu Li, Yuzhe Bai, Li Niu· Proceedings of the 32nd ACM...· 0 citations
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