collaborators

9 papers

cs.CL2026

Alignment Is All You Need: Instruction-Free Training for General Audio-Language Models

Xuanru Zhou, Yiwen Shao, Jiahong Li +1

Multimodal large language models (MLLMs) are typically built through a multi-stage pipeline consisting of cross-modal alignment, supervised fine-tuning (SFT), and preference optimi…

quant-ph2026

Optimal physical approximations of pure-state cloning and transposition are complementary channels

Vanessa Brzić, Dmitry Grinko, Michał Studziński +1

State cloning and state transposition are fundamental transformations that, despite being desirable, cannot be perfectly realised as a consequence of two distinct requirements of q…

cs.CL2026

Towards Comprehensive Semantic Speech Embeddings for Chinese Dialects

Kalvin Chang, Yiwen Shao, Jiahong Li +1

Despite having hundreds of millions of speakers, Chinese dialects lag behind Mandarin in speech and language technologies. Most varieties are primarily spoken, making dialect-to-Ma…

cs.CL2025

AzeroS: Extending LLM to Speech with Self-Generated Instruction-Free Tuning

Yiwen Shao, Wei Liu, Jiahong Li +4

Extending large language models (LLMs) to the speech domain has recently gained significant attention. A typical approach connects a pretrained LLM with an audio encoder through a…

eess.AS2025

Auden-Voice: General-Purpose Voice Encoder for Speech and Language Understanding

Mingyue Huo, Wei-Cheng Tseng, Yiwen Shao +2

Human voice encodes both identity and paralinguistic cues, yet encoders in large audio-language models (LALMs) rarely balance both aspects. In this work, we present a study toward…

eess.AS2025

Revisiting Audio-language Pretraining for Learning General-purpose Audio Representation

Wei-Cheng Tseng, Xuanru Zhou, Mingyue Huo +3

Audio-language pretraining (ALP) holds promise for learning general-purpose audio representation, yet remains underexplored. Crucially, there is no consensus on whether audio-langu…

eess.AS2025

TTA: Transcribe, Translate and Alignment for Cross-lingual Speech Representation

Wei Liu, Jiahong Li, Yiwen Shao +1

Speech-LLM models have demonstrated great performance in multi-modal and multi-task speech understanding. A typical speech-LLM paradigm is integrating speech modality with a large…

cs.SD2025

Efficient Scaling for LLM-based ASR

Bingshen Mu, Yiwen Shao, Kun Wei +2

Large language model (LLM)-based automatic speech recognition (ASR) achieves strong performance but often incurs high computational costs. This work investigates how to obtain the…

cs.CL2025

Efficient Multilingual ASR Finetuning via LoRA Language Experts

Jiahong Li, Yiwen Shao, Jianheng Zhuo +4

Recent advancements in deep learning have significantly enhanced multilingual automatic speech recognition (ASR) due to the development of advanced model architectures and availabl…