collaborators

8 papers

cs.LG2026

Semantic DLM+: Improving Diffusion Language Models through Bias-variance Trade-off in Transition Kernel Design

Keyue Jiang, Yuxiang Wang, Yanan Zhao +7

Diffusion Language Models (DLMs) have demonstrated strong scaling capacity as alternatives to autoregressive language models. However, their performance is highly sensitive to the…

eess.AS2026

VoxWatermark: A Large-Scale Benchmark for Audio Watermark Detection under Perturbations

Farnaz Sedaghati, Yuxi Wang, Zicheng Weng +1

With the rapid deployment of speech generation systems in open environments, providing verifiable source attribution and copyright accountability for audio content has become criti…

cs.CL2026

Schützen: Evaluating LLM Safety in Bulgarian and German Contexts

Kiril Georgiev, Yuxia Wang, Dimitar Iliyanov Dimitrov +2

Large language models are increasingly deployed across professional domains, bringing hard-to-predict risks, including the generation of harmful or disrespectful content. Although…

eess.AS2026

Spatial-Omni: Spatial Audio Understanding Integration in Multimodal LLMs via FOA Encoding

Zhiyuan Zhu, Yixuan Chen, Yiwen Shao +13

Recent multimodal large language models mainly process audio as monaural signals, thereby discarding the spatial cues contained in spatial audio for sound localization, spatial rel…

cs.CL2026

ParaBridge: Bridging Paralinguistic Perception and Dialogue Behavior in Speech Language Models

Yuxiang Wang, Qinke Ni, Shengbo Cai +3

Speech carries more information than just words: a child's voice, a fearful tone, or a noisy background should all lead a sufficiently competent spoken-dialogue assistant to differ…

cs.CL2026

TinyJudge: Unverifiable Constraint Alignment via Lightweight Specialist Ensembles

Yirong Zeng, Yufei Liu, Xiao Ding +9

Instruction Following (IF) is a core capability of LLMs, requiring strict adherence to diverse constraints, ranging from verifiable ones (e.g., output length) to unverifiable ones…