1 citations · 2 across the 8 of their papers we have counts for
8 papers
Ti-Audio: The First Multi-Dialectal End-to-End Speech LLM for Tibetan
Jialing Wang, Yue Zhao, Yuhao Zhang +5
Recent advances in Speech Large Language Models (Speech-LLMs) have made significant progress, greatly enhancing multimodal interaction capabilities.However, their application in lo…
ContextWeaver: Selective and Dependency-Structured Memory Construction for LLM Agents
Yating Wu, Yuhao Zhang, Sayan Ghosh +4
Large language model (LLM) agents often struggle in long-context interactions. As the history grows, sliding windows and prompt compression may drop earlier information that later…
EvA: An Evidence-First Audio Understanding Paradigm for LALMs
Xinyuan Xie, Shunian Chen, Zhiheng Liu +4
Large Audio Language Models (LALMs) still struggle in complex acoustic scenes because they often fail to preserve task-relevant acoustic evidence before reasoning begins. We identi…
EchoMind: An Interrelated Multi-level Benchmark for Evaluating Empathetic Speech Language Models
Li Zhou, Lutong Yu, You Lyu +6
Speech Language Models (SLMs) have made significant progress in spoken language understanding. Yet it remains unclear whether they can fully perceive non lexical vocal cues alongsi…
MTalk-Bench: Evaluating Speech-to-Speech Models in Multi-Turn Dialogues via Arena-style and Rubrics Protocols
Yuhao Du, Qianwei Huang, Guo Zhu +9
The rapid advancement of speech-to-speech (S2S) large language models (LLMs) has significantly improved real-time spoken interaction. However, current evaluation frameworks remain…
EchoX: Towards Mitigating Acoustic-Semantic Gap via Echo Training for Speech-to-Speech LLMs
Yuhao Zhang, Yuhao Du, Zhanchen Dai +4
Speech-to-speech large language models (SLLMs) are attracting increasing attention. Derived from text-based large language models (LLMs), SLLMs often exhibit degradation in knowled…
Soundwave: Less is More for Speech-Text Alignment in LLMs
Yuhao Zhang, Zhiheng Liu, Fan Bu +3
Existing end-to-end speech large language models (LLMs) usually rely on large-scale annotated data for training, while data-efficient training has not been discussed in depth. We f…
Roadmap towards Superhuman Speech Understanding using Large Language Models
Fan Bu, Yuhao Zhang, Xidong Wang +3
The success of large language models (LLMs) has prompted efforts to integrate speech and audio data, aiming to create general foundation models capable of processing both textual a…