activity
20232026
most citedDeSTA2: Developing Instruction-Following Speech Language Model Without Speech Instruction-Tuning Data

15 citations · 23 across the 29 of their papers we have counts for

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Showing cs.SDShow all

7 papers · 1 filter

cs.SD2026

Encoder-Side Neuron Identification and Amplification for Acoustic Perception in Large Audio-Language Models

Yu-Han Huang, Chih-Kai Yang, Ke-Han Lu +2

Large audio-language models (LALMs) often underperform on fine-grained, non-semantic attributes of speech, such as a speaker's emotion, despite strong performance on speech content…

cs.SD2026

Escaping the Procrustean Bed: Groupwise Orthogonal Connectors for Audio-Language Models

Ho-Lam Chung, Ke-Han Lu, Yi-Cheng Lin +3

Audio-language models compress a speech encoder's output through a Querying Transformer (Q-Former) connector before feeding it to a large language model. We identify two failures i…

cs.SD2026

All That Glitters Is Not Audio: Rethinking Text Priors and Audio Reliance in Audio-Language Evaluation

Leonardo Haw-Yang Foo, Chih-Kai Yang, Chen-An Li +2

Large Audio-Language Models show consistent performance gains across speech and audio benchmarks, yet high scores may not reflect true auditory perception. If a model can answer qu…

cs.SD2026

MUGEN: Evaluating and Improving Multi-audio Understanding of Large Audio-Language Models

Chih-Kai Yang, Yun-Shao Tsai, Yu-Kai Guo +7

While multi-audio understanding is critical for large audio-language models (LALMs), it remains underexplored. We introduce MUGEN, a comprehensive benchmark evaluating this capabil…

cs.SD2026

TW-Sound580K: A Regional Audio-Text Dataset with Verification-Guided Curation for Localized Audio-Language Modeling

Hao-Hui Xie, Ho-Lam Chung, Yi-Cheng Lin +4

Large Audio-Language Models (LALMs) typically struggle with localized dialectal prosody due to the scarcity of specialized corpora. We present TW-Sound580K, a Taiwanese audio-text…

cs.SD2025

Investigating Safety Vulnerabilities of Large Audio-Language Models Under Speaker Emotional Variations

Bo-Han Feng, Chien-Feng Liu, Yu-Hsuan Li Liang +9

Large audio-language models (LALMs) extend text-based LLMs with auditory understanding, offering new opportunities for multimodal applications. While their perception, reasoning, a…

cs.SD2025

SAKE: Towards Editing Auditory Attribute Knowledge of Large Audio-Language Models

Chih-Kai Yang, Yen-Ting Piao, Tzu-Wen Hsu +8

Knowledge editing enables targeted updates without retraining, but prior work focuses on textual or visual facts, leaving abstract auditory perceptual knowledge underexplored. We i…