activity
20242026
most citedAND: Audio Network Dissection for Interpreting Deep Acoustic Models

1 citations · 2 across the 10 of their papers we have counts for

collaborators

11 papers

cs.SD2026

What Does LALM Post-training Learn? Rethinking Audio Understanding and Reasoning Capabilities

Hua-Hsuan Chen, Xuanjun Chen, Wei-Chung Lu +5

Post-training often improves the performance of large audio-language models on audio understanding and reasoning benchmarks. However, these improvements may reflect adaptation to s…

cs.SD2026

Membership Inference Attacks against Large Audio Language Models

Jia-Kai Dong, Yu-Xiang Lin, Hung-Yi Lee

We present the first systematic Membership Inference Attack (MIA) evaluation of LALMs. Using Multi-modal Blind Baselines based on textual, spectral and prosodic features, we demons…

cs.CL2025

Style Amnesia: Investigating Speaking Style Degradation and Mitigation in Multi-Turn Spoken Language Models

Yu-Xiang Lin, Cheng-Han Chiang, Hung-yi Lee

In this paper, we show that when spoken language models (SLMs) are instructed to speak in a specific speaking style at the beginning of a multi-turn conversation, they cannot maint…

cs.SD2025

Hearing the Order: Investigating Position Bias in Large Audio-Language Models

Yu-Xiang Lin, Chen-An Li, Sheng-Lun Wei +3

Large audio-language models (LALMs) are often used in tasks that involve reasoning over ordered options. An open question is whether their predictions are influenced by the order o…

eess.AS2025

DeSTA2.5-Audio: Toward General-Purpose Large Audio Language Model with Self-Generated Cross-Modal Alignment

Ke-Han Lu, Zhehuai Chen, Szu-Wei Fu +25

We introduce DeSTA2.5-Audio, a general-purpose Large Audio Language Model (LALM) designed for robust auditory perception and instruction-following. Recent LALMs augment Large Langu…

eess.AS2025

SIFT-50M: A Large-Scale Multilingual Dataset for Speech Instruction Fine-Tuning

Prabhat Pandey, Rupak Vignesh Swaminathan, K V Vijay Girish +4

We introduce SIFT (Speech Instruction Fine-Tuning), a 50M-example dataset designed for instruction fine-tuning and pre-training of speech-text large language models (LLMs). SIFT-50…

cs.CL2025★ 1 cited

A Preliminary Exploration with GPT-4o Voice Mode

Yu-Xiang Lin, Chih-Kai Yang, Wei-Chih Chen +4

With the rise of multimodal large language models, GPT-4o stands out as a pioneering model, driving us to evaluate its capabilities. This report assesses GPT-4o across various task…

cs.CL2024

Building a Taiwanese Mandarin Spoken Language Model: A First Attempt

Chih-Kai Yang, Yu-Kuan Fu, Chen-An Li +18

This technical report presents our initial attempt to build a spoken large language model (LLM) for Taiwanese Mandarin, specifically tailored to enable real-time, speech-to-speech…

cs.CL2024

Dynamic-SUPERB Phase-2: A Collaboratively Expanding Benchmark for Measuring the Capabilities of Spoken Language Models with 180 Tasks

Chien-yu Huang, Wei-Chih Chen, Shu-wen Yang +77

Multimodal foundation models, such as Gemini and ChatGPT, have revolutionized human-machine interactions by seamlessly integrating various forms of data. Developing a universal spo…

cs.SD2024★ 1 cited

AND: Audio Network Dissection for Interpreting Deep Acoustic Models

Tung-Yu Wu, Yu-Xiang Lin, Tsui-Wei Weng

Neuron-level interpretations aim to explain network behaviors and properties by investigating neurons responsive to specific perceptual or structural input patterns. Although there…

cs.CL2024

Generating Attractive and Authentic Copywriting from Customer Reviews

Yu-Xiang Lin, Wei-Yun Ma

The goal of product copywriting is to capture the interest of potential buyers by emphasizing the features of products through text descriptions. As e-commerce platforms offer a wi…