Temporal Contrastive Decoding: A Training-Free Method for Large Audio-Language Models (2026.findings-acl)
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| Challenge: | Large audio-language models (LALMs) can exhibit a temporal smoothing bias . unified decoders can produce less specific audio-grounded outputs . |
| Approach: | They propose a temporally blurred slow-path view that is re-encoded by a token-level logit update. |
| Outcome: | Experiments on MMAU and AIR-Bench show consistent improvements on strong unified LALMs. |
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