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Home » [2505.15957] Towards Holistic Evaluation of Large Audio-Language Models: A Comprehensive Survey
arXiv AI

[2505.15957] Towards Holistic Evaluation of Large Audio-Language Models: A Comprehensive Survey

Advanced AI BotBy Advanced AI BotMay 26, 2025No Comments2 Mins Read
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[Submitted on 21 May 2025 (v1), last revised 23 May 2025 (this version, v2)]

View a PDF of the paper titled Towards Holistic Evaluation of Large Audio-Language Models: A Comprehensive Survey, by Chih-Kai Yang and 2 other authors

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Abstract:With advancements in large audio-language models (LALMs), which enhance large language models (LLMs) with auditory capabilities, these models are expected to demonstrate universal proficiency across various auditory tasks. While numerous benchmarks have emerged to assess LALMs’ performance, they remain fragmented and lack a structured taxonomy. To bridge this gap, we conduct a comprehensive survey and propose a systematic taxonomy for LALM evaluations, categorizing them into four dimensions based on their objectives: (1) General Auditory Awareness and Processing, (2) Knowledge and Reasoning, (3) Dialogue-oriented Ability, and (4) Fairness, Safety, and Trustworthiness. We provide detailed overviews within each category and highlight challenges in this field, offering insights into promising future directions. To the best of our knowledge, this is the first survey specifically focused on the evaluations of LALMs, providing clear guidelines for the community. We will release the collection of the surveyed papers and actively maintain it to support ongoing advancements in the field.

Submission history

From: Chih-Kai Yang [view email]
[v1]
Wed, 21 May 2025 19:17:29 UTC (823 KB)
[v2]
Fri, 23 May 2025 07:36:27 UTC (823 KB)



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