collaborators

5 papers

cs.CV2026

Exploring Audio Hallucination in Egocentric Video Understanding

Ashish Seth, Xinhao Mei, Changsheng Zhao +9

Egocentric videos provide a distinctive setting in which sound serves as crucial cues to understand user activities and surroundings, particularly when visual information is unstab…

cs.SD2026

Lightweight and Generalizable Acoustic Scene Representations via Contrastive Fine-Tuning and Distillation

Kuang Yuan, Yang Gao, Xilin Li +4

Acoustic scene classification (ASC) models on edge devices typically operate under fixed class assumptions, lacking the transferability needed for real-world applications that requ…

cs.CV2026

EgoAVU: Egocentric Audio-Visual Understanding

Ashish Seth, Xinhao Mei, Changsheng Zhao +9

Understanding egocentric videos plays a vital role for embodied intelligence. Recent multi-modal large language models (MLLMs) can accept both visual and audio inputs. However, due…

eess.AS2026

SLAP: Scalable Language-Audio Pretraining with Variable-Duration Audio and Multi-Objective Training

Xinhao Mei, Gael Le Lan, Haohe Liu +5

Contrastive language-audio pretraining (CLAP) has achieved notable success in learning semantically rich audio representations and is widely adopted for various audio-related tasks…

cs.MM2024

SyncFlow: Toward Temporally Aligned Joint Audio-Video Generation from Text

Haohe Liu, Gael Le Lan, Xinhao Mei +7

Video and audio are closely correlated modalities that humans naturally perceive together. While recent advancements have enabled the generation of audio or video from text, produc…