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20242026
most citedA Survey on Speech Large Language Models for Understanding

6 citations · 6 across the 17 of their papers we have counts for

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11 papers · 1 filter

eess.AS2026

SURE-EVAL: A Systematic and Unified Agentic Framework for Reproducible Evaluation

Jing Peng, Junhao Du, Yixuan Wang +21

Audio and speech models are released rapidly, but reported scores often conflate model capability with deployment and evaluation choices. The same checkpoint can produce different…

cs.SD2026

dots.tts.edit: Precisely Controlled Speech Editing with a Continuous Autoregressive Model

Hankun Wang, Bohan Li, Shi Lian +7

Speech editing for content creation requires precise control over both what an edit should do and where it should apply. Free-form natural language provides a flexible interface fo…

cs.AI2026

Making AI Scientists Auditable from Evidence to Claim

Zijian Wang, Hanqi Li, Ziyue Yang +17

AI research systems can report improved results without establishing that the tested implementation matches the method described in their conclusions. We introduce Xcientist, a res…

cs.PL2026

XFlow: An Executable Protocol Programming System for Reliable Multi-Agent Workflows

Hanqi Li, Jing Peng, Zijian Wang +2

LLM-based multi-agent systems increasingly coordinate planning, reasoning, tool use, and human interaction, yet their reliability remains limited. A central source of this limitati…

eess.AS2026

VISA: A Visual Information Strengthened Audio-Reasoning System for the Interspeech 2026 ARC Agent Track

Wenming Tu, Jian Gao, Yanru Huo +9

Audio reasoning requires multi-step, evidence-grounded inference over temporally dynamic and acoustically mixed signals, exceeding conventional perception tasks such as ASR or capt…

eess.AS2026

A Unified and Reproducible Experimentation Framework for Speech Understanding

Jing Peng, Junhao Du, Chenghao Wang +21

Speech foundation models and Speech LLMs have advanced speech understanding, yet deployment-oriented model selection is hindered by non-comparable evaluations caused by mismatched…

eess.AS2026

Audio-Mind: An Auditable Agentic Framework for Audio Understanding

Yucheng Wang, Jing Peng, Hanqi Li +6

Audio agents extend large audio-language models (LALMs) by decomposing audio questions into tool calls, intermediate evidence, and iterative reasoning steps. However, as LALMs beco…

eess.AS2026

TASU2: Controllable CTC Simulation for Alignment and Low-Resource Adaptation of Speech LLMs

Jing Peng, Chenghao Wang, Yi Yang +5

Speech LLM post-training increasingly relies on efficient cross-modal alignment and robust low-resource adaptation, yet collecting large-scale audio-text pairs remains costly. Text…

cs.SD2026

RAS: a Reliability Oriented Metric for Automatic Speech Recognition

Wenbin Huang, Yuhang Qiu, Bohan Li +5

Automatic speech recognition systems often produce confident yet incorrect transcriptions under noisy or ambiguous conditions, which can be misleading for both users and downstream…

eess.AS2026

G-STAR: End-to-End Global Speaker-Tracking Attributed Recognition

Jing Peng, Ziyi Chen, Haoyu Li +7

We study timestamped speaker-attributed automatic speech recognition (SA-ASR) for long-form, multi-party speech with overlap. In this setting, chunk-wise inference must preserve me…

eess.AS2026

TC-BiMamba: Trans-Chunk bidirectionally within BiMamba for unified streaming and non-streaming ASR

Qingshun She, Jing Peng, Yangui Fang +2

This work investigates bidirectional Mamba (BiMamba) for unified streaming and non-streaming automatic speech recognition (ASR). Dynamic chunk size training enables a single model…