Imagine to Hear: Auditory Knowledge Generation can be an Effective Assistant for Language Models (2025.findings-acl)
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| Challenge: | Existing approaches to augment language models with audio databases lack the ability to understand auditory signals like humans. |
| Approach: | They propose a method that augments language models with audio databases to generate auditory knowledge . their framework detects multiple audio-related textual spans from the given prompt . |
| Outcome: | The proposed approach achieves state-of-the-art performance on AuditoryBench without external databases. |
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