activity
20222024
most citedUniversal Multimodal Representation for Language Understanding

35 citations · 45 across the 12 of their papers we have counts for

collaborators

12 papers

cs.SD2024

VHASR: A Multimodal Speech Recognition System With Vision Hotwords

Jiliang Hu, Zuchao Li, Ping Wang +3

The image-based multimodal automatic speech recognition (ASR) model enhances speech recognition performance by incorporating audio-related image. However, some works suggest that i…

cs.CV20241 cited

Enhancing Perception of Key Changes in Remote Sensing Image Change Captioning

Cong Yang, Zuchao Li, Hongzan Jiao +2

Recently, while significant progress has been made in remote sensing image change captioning, existing methods fail to filter out areas unrelated to actual changes, making models s…

cs.CL2024

A Coin Has Two Sides: A Novel Detector-Corrector Framework for Chinese Spelling Correction

Xiangke Zeng, Zuchao Li, Lefei Zhang +3

Chinese Spelling Correction (CSC) stands as a foundational Natural Language Processing (NLP) task, which primarily focuses on the correction of erroneous characters in Chinese text…

cs.LG20241 cited

BatGPT-Chem: A Foundation Large Model For Retrosynthesis Prediction

Yifei Yang, Runhan Shi, Zuchao Li +4

Retrosynthesis analysis is pivotal yet challenging in drug discovery and organic chemistry. Despite the proliferation of computational tools over the past decade, AI-based systems…

cs.CV2024

DSDRNet: Disentangling Representation and Reconstruct Network for Domain Generalization

Juncheng Yang, Zuchao Li, Shuai Xie +2

Domain generalization faces challenges due to the distribution shift between training and testing sets, and the presence of unseen target domains. Common solutions include domain a…

cs.CV2024

Cross-Modal Adapter: Parameter-Efficient Transfer Learning Approach for Vision-Language Models

Juncheng Yang, Zuchao Li, Shuai Xie +3

Adapter-based parameter-efficient transfer learning has achieved exciting results in vision-language models. Traditional adapter methods often require training or fine-tuning, faci…