30 citations · 51 across the 12 of their papers we have counts for
6 papers · 1 filter
LibriSQA: A Novel Dataset and Framework for Spoken Question Answering with Large Language Models
Zihan Zhao, Yiyang Jiang, Heyang Liu +2
While Large Language Models (LLMs) have demonstrated commendable performance across a myriad of domains and tasks, existing LLMs still exhibit a palpable deficit in handling multim…
Audio-aware Query-enhanced Transformer for Audio-Visual Segmentation
Jinxiang Liu, Chen Ju, Chaofan Ma +3
The goal of the audio-visual segmentation (AVS) task is to segment the sounding objects in the video frames using audio cues. However, current fusion-based methods have the perform…
Enhanced Multimodal Representation Learning with Cross-modal KD
Mengxi Chen, Linyu Xing, Yu Wang +1
This paper explores the tasks of leveraging auxiliary modalities which are only available at training to enhance multimodal representation learning through cross-modal Knowledge Di…
EqMotion: Equivariant Multi-agent Motion Prediction with Invariant Interaction Reasoning
Chenxin Xu, Robby T. Tan, Yuhong Tan +4
Learning to predict agent motions with relationship reasoning is important for many applications. In motion prediction tasks, maintaining motion equivariance under Euclidean geomet…
DiffusionSeg: Adapting Diffusion Towards Unsupervised Object Discovery
Chaofan Ma, Yuhuan Yang, Chen Ju +5
Learning from a large corpus of data, pre-trained models have achieved impressive progress nowadays. As popular generative pre-training, diffusion models capture both low-level vis…
Knowledge-aware Bayesian Co-attention for Multimodal Emotion Recognition
Zihan Zhao, Yu Wang, Yanfeng Wang
Multimodal emotion recognition is a challenging research area that aims to fuse different modalities to predict human emotion. However, most existing models that are based on atten…