36 citations · 42 across the 14 of their papers we have counts for
15 papers
ARGUS: An Agenda-Driven Framework for Reliable User Simulation
Hang Zheng, Nan Jiang, Zichen Zhu +6
High-fidelity user simulators are essential for evaluating and training agents in interactive environments. However, current LLM-based simulators struggle with reliability issues,…
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…
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…
DiSRouter: Distributed Self-Routing for LLM Selections
Hang Zheng, Hongshen Xu, Yongkai Lin +3
The proliferation of Large Language Models (LLMs) has created a diverse ecosystem of models with highly varying performance and costs, necessitating effective query routing to bala…
NeuSym-RAG: Hybrid Neural Symbolic Retrieval with Multiview Structuring for PDF Question Answering
Ruisheng Cao, Hanchong Zhang, Tiancheng Huang +8
The increasing number of academic papers poses significant challenges for researchers to efficiently acquire key details. While retrieval augmented generation (RAG) shows great pro…
NotaGen: Advancing Musicality in Symbolic Music Generation with Large Language Model Training Paradigms
Yashan Wang, Shangda Wu, Jianhuai Hu +7
We introduce NotaGen, a symbolic music generation model aiming to explore the potential of producing high-quality classical sheet music. Inspired by the success of Large Language M…
VQTalker: Towards Multilingual Talking Avatars through Facial Motion Tokenization
Tao Liu, Ziyang Ma, Qi Chen +4
We present VQTalker, a Vector Quantization-based framework for multilingual talking head generation that addresses the challenges of lip synchronization and natural motion across d…
Sparsity-Accelerated Training for Large Language Models
Da Ma, Lu Chen, Pengyu Wang +6
Large language models (LLMs) have demonstrated proficiency across various natural language processing (NLP) tasks but often require additional training, such as continual pre-train…
GigaSpeech 2: An Evolving, Large-Scale and Multi-domain ASR Corpus for Low-Resource Languages with Automated Crawling, Transcription and Refinement
Yifan Yang, Zheshu Song, Jianheng Zhuo +13
The evolution of speech technology has been spurred by the rapid increase in dataset sizes. Traditional speech models generally depend on a large amount of labeled training data, w…
AniTalker: Animate Vivid and Diverse Talking Faces through Identity-Decoupled Facial Motion Encoding
Tao Liu, Feilong Chen, Shuai Fan +4
The paper introduces AniTalker, an innovative framework designed to generate lifelike talking faces from a single portrait. Unlike existing models that primarily focus on verbal cu…
The X-LANCE Technical Report for Interspeech 2024 Speech Processing Using Discrete Speech Unit Challenge
Yiwei Guo, Chenrun Wang, Yifan Yang +9
Discrete speech tokens have been more and more popular in multiple speech processing fields, including automatic speech recognition (ASR), text-to-speech (TTS) and singing voice sy…
Rejection Improves Reliability: Training LLMs to Refuse Unknown Questions Using RL from Knowledge Feedback
Hongshen Xu, Zichen Zhu, Situo Zhang +4
Large Language Models (LLMs) often generate erroneous outputs, known as hallucinations, due to their limitations in discerning questions beyond their knowledge scope. While address…
Developing ChemDFM as a large language foundation model for chemistry
Zihan Zhao, Da Ma, Lu Chen +11
Artificial intelligence (AI) has played an increasingly important role in chemical research. However, most models currently used in chemistry are specialist models that require tra…
DiffDub: Person-generic Visual Dubbing Using Inpainting Renderer with Diffusion Auto-encoder
Tao Liu, Chenpeng Du, Shuai Fan +2
Generating high-quality and person-generic visual dubbing remains a challenge. Recent innovation has seen the advent of a two-stage paradigm, decoupling the rendering and lip synch…
DFM: Dialogue Foundation Model for Universal Large-Scale Dialogue-Oriented Task Learning
Zhi Chen, Jijia Bao, Lu Chen +10
Building a universal conversational agent has been a long-standing goal of the dialogue research community. Most previous works only focus on a small set of dialogue tasks. In this…