activity
20242026
most citedRecent Advances in Speech Language Models: A Survey

5 citations · 10 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CL2026

SpeechSense: A Paralinguistic-Focused Dataset for Fine-Grained Speech Sentiment Analysis

Shicheng Ma, Wenqian Cui, Irwin King

Recent advances in AI have revolutionized speech processing, yet effective speech understanding requires discerning not just what is said, but how it is said. Speech Sentiment Anal…

eess.AS2026

A Survey of Audio Reasoning in Multimodal Foundation Models

Zhihan Guo, Wenqian Cui, Guan-Ting Lin +8

Reasoning has become a defining capability of modern foundation models, yet its development in the audio modality remains limited. Audio poses challenges that are distinct from tho…

cs.AI2026★ 3 cited

Towards trustworthy agentic AI: a comprehensive survey of safety, robustness, privacy, and system security

Jinhu Qi, Muzhi Li, Jiahong Liu +9

Agentic AI systems -- Large Language Models (LLMs) augmented with planning, tool use, memory, and long-horizon interactions -- can execute complex tasks autonomously, but their mul…

cs.CL2026

Minimizing Modality Gap from the Input Side: Your Speech LLM Can Be a Prosody-Aware Text LLM

Wenqian Cui, Xiao-Hui Li, Daxin Tan +2

Speech large language models (SLMs) are typically built from text large language model (TLM) checkpoints, yet they still suffer from a substantial modality gap. Prior work has main…

cs.CL2025★ 1 cited

MTR-DuplexBench: Towards a Comprehensive Evaluation of Multi-Round Conversations for Full-Duplex Speech Language Models

He Zhang, Wenqian Cui, Haoning Xu +5

Full-Duplex Speech Language Models (FD-SLMs) enable real-time, overlapping conversational interactions, offering a more dynamic user experience compared to traditional half-duplex…

cs.LG2025

ConSurv: Multimodal Continual Learning for Survival Analysis

Dianzhi Yu, Conghao Xiong, Yankai Chen +6

Survival prediction of cancers is crucial for clinical practice, as it informs mortality risks and influences treatment plans. However, a static model trained on a single dataset f…

cs.CL2025

TurnGuide: Enhancing Meaningful Full Duplex Spoken Interactions via Dynamic Turn-Level Text-Speech Interleaving

Wenqian Cui, Lei Zhu, Xiaohui Li +4

Full-Duplex Speech Language Models (FD-SLMs) are specialized foundation models designed to enable natural, real-time spoken interactions by modeling complex conversational turn-tak…

cs.CL2025

From General to Targeted Rewards: Surpassing GPT-4 in Open-Ended Long-Context Generation

Zhihan Guo, Jiele Wu, Wenqian Cui +4

Current research on long-form context in Large Language Models (LLMs) primarily focuses on the understanding of long-contexts, the Open-ended Long Text Generation (Open-LTG) remain…

cs.CL2025

NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction

Qichao Wang, Ziqiao Meng, Wenqian Cui +6

Inspired by the impressive capabilities of GPT-4o, there is growing interest in enabling speech language models (SLMs) to engage in natural, fluid spoken interactions with humans.…

cs.CL2025

Data Augmentation Techniques for Chinese Disease Name Normalization

Wenqian Cui, Xiangling Fu, Shaohui Liu +4

Disease name normalization is an important task in the medical domain. It classifies disease names written in various formats into standardized names, serving as a fundamental comp…

cs.CL2025★ 1 cited

VoxEval: Benchmarking the Knowledge Understanding Capabilities of End-to-End Spoken Language Models

Wenqian Cui, Xiaoqi Jiao, Ziqiao Meng +1

With the rising need for speech-based interaction models, end-to-end Spoken Language Models (SLMs) have emerged as a promising solution. While these models require comprehensive wo…

cs.CL2024★ 5 cited

Recent Advances in Speech Language Models: A Survey

Wenqian Cui, Dianzhi Yu, Xiaoqi Jiao +5

Large Language Models (LLMs) have recently garnered significant attention, primarily for their capabilities in text-based interactions. However, natural human interaction often rel…

cs.SD2024

MoodLoopGP: Generating Emotion-Conditioned Loop Tablature Music with Multi-Granular Features

Wenqian Cui, Pedro Sarmento, Mathieu Barthet

Loopable music generation systems enable diverse applications, but they often lack controllability and customization capabilities. We argue that enhancing controllability can enric…