most citedFireRedChat: A Pluggable, Full-Duplex Voice Interaction System with Cascaded and Semi-Cascaded Implementations

2 citations · 2 across the 4 of their papers we have counts for

collaborators

5 papers

cs.SD20252 cited

FireRedChat: A Pluggable, Full-Duplex Voice Interaction System with Cascaded and Semi-Cascaded Implementations

Junjie Chen, Yao Hu, Junjie Li +12

Full-duplex voice interaction allows users and agents to speak simultaneously with controllable barge-in, enabling lifelike assistants and customer service. Existing solutions are…

cs.LG2025

CMPhysBench: A Benchmark for Evaluating Large Language Models in Condensed Matter Physics

Weida Wang, Dongchen Huang, Jiatong Li +32

We introduce CMPhysBench, designed to assess the proficiency of Large Language Models (LLMs) in Condensed Matter Physics, as a novel Benchmark. CMPhysBench is composed of more than…

cs.CL2025

From Macro to Micro: Probing Dataset Diversity in Language Model Fine-Tuning

Haoyu Li, Xuhong Li, Yiming Dong +1

Dataset diversity plays a pivotal role for the successful training of many machine learning models, particularly in the supervised fine-tuning (SFT) stage of large language model (…

cs.CV2025

SurveillanceVQA-589K: A Benchmark for Comprehensive Surveillance Video-Language Understanding with Large Models

Bo Liu, Pengfei Qiao, Minhan Ma +5

Understanding surveillance video content remains a critical yet underexplored challenge in vision-language research, particularly due to its real-world complexity, irregular event…

cs.SD2025

Exploring the Potential of Large Multimodal Models as Effective Alternatives for Pronunciation Assessment

Ke Wang, Lei He, Kun Liu +3

Large Multimodal Models (LMMs) have demonstrated exceptional performance across a wide range of domains. This paper explores their potential in pronunciation assessment tasks, with…