7 citations · 21 across the 17 of their papers we have counts for
5 papers · 1 filter
Generative error correction for code-switching speech recognition using large language models
Chen Chen, Yuchen Hu, Chao-Han Huck Yang +3
Code-switching (CS) speech refers to the phenomenon of mixing two or more languages within the same sentence. Despite the recent advances in automatic speech recognition (ASR), CS-…
Less is More: Removing Text-regions Improves CLIP Training Efficiency and Robustness
Liangliang Cao, Bowen Zhang, Chen Chen +5
The CLIP (Contrastive Language-Image Pre-training) model and its variants are becoming the de facto backbone in many applications. However, training a CLIP model from hundreds of m…
Edit Everything: A Text-Guided Generative System for Images Editing
Defeng Xie, Ruichen Wang, Jian Ma +5
We introduce a new generative system called Edit Everything, which can take image and text inputs and produce image outputs. Edit Everything allows users to edit images using simpl…
GlyphDraw: Seamlessly Rendering Text with Intricate Spatial Structures in Text-to-Image Generation
Jian Ma, Mingjun Zhao, Chen Chen +4
Recent breakthroughs in the field of language-guided image generation have yielded impressive achievements, enabling the creation of high-quality and diverse images based on user i…
STAIR: Learning Sparse Text and Image Representation in Grounded Tokens
Chen Chen, Bowen Zhang, Liangliang Cao +7
Image and text retrieval is one of the foundational tasks in the vision and language domain with multiple real-world applications. State-of-the-art approaches, e.g. CLIP, ALIGN, re…