30 citations · 148 across the 82 of their papers we have counts for
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A Contrastive Compositional Benchmark for Text-to-Image Synthesis: A Study with Unified Text-to-Image Fidelity Metrics
Xiangru Zhu, Penglei Sun, Chengyu Wang +4
Text-to-image (T2I) synthesis has recently achieved significant advancements. However, challenges remain in the model's compositionality, which is the ability to create new combina…
A Dual-way Enhanced Framework from Text Matching Point of View for Multimodal Entity Linking
Shezheng Song, Shan Zhao, Chengyu Wang +4
Multimodal Entity Linking (MEL) aims at linking ambiguous mentions with multimodal information to entity in Knowledge Graph (KG) such as Wikipedia, which plays a key role in many a…
Towards Better Parameter-Efficient Fine-Tuning for Large Language Models: A Position Paper
Chengyu Wang, Junbing Yan, Wei Zhang +1
This paper delves into the pressing need in Parameter-Efficient Fine-Tuning (PEFT) for Large Language Models (LLMs). While LLMs possess remarkable capabilities, their extensive par…
FastBlend: a Powerful Model-Free Toolkit Making Video Stylization Easier
Zhongjie Duan, Chengyu Wang, Cen Chen +3
With the emergence of diffusion models and rapid development in image processing, it has become effortless to generate fancy images in tasks such as style transfer and image editin…
Learning Knowledge-Enhanced Contextual Language Representations for Domain Natural Language Understanding
Ruyao Xu, Taolin Zhang, Chengyu Wang +6
Knowledge-Enhanced Pre-trained Language Models (KEPLMs) improve the performance of various downstream NLP tasks by injecting knowledge facts from large-scale Knowledge Graphs (KGs)…
Sharing, Teaching and Aligning: Knowledgeable Transfer Learning for Cross-Lingual Machine Reading Comprehension
Tingfeng Cao, Chengyu Wang, Chuanqi Tan +2
In cross-lingual language understanding, machine translation is often utilized to enhance the transferability of models across languages, either by translating the training data fr…
From Complex to Simple: Unraveling the Cognitive Tree for Reasoning with Small Language Models
Junbing Yan, Chengyu Wang, Taolin Zhang +3
Reasoning is a distinctive human capacity, enabling us to address complex problems by breaking them down into a series of manageable cognitive steps. Yet, complex logical reasoning…
BeautifulPrompt: Towards Automatic Prompt Engineering for Text-to-Image Synthesis
Tingfeng Cao, Chengyu Wang, Bingyan Liu +3
Recently, diffusion-based deep generative models (e.g., Stable Diffusion) have shown impressive results in text-to-image synthesis. However, current text-to-image models often requ…
Uncertainty-aware Parameter-Efficient Self-training for Semi-supervised Language Understanding
Jianing Wang, Qiushi Sun, Nuo Chen +4
The recent success of large pre-trained language models (PLMs) heavily hinges on massive labeled data, which typically produces inferior performance in low-resource scenarios. To r…
DualToken-ViT: Position-aware Efficient Vision Transformer with Dual Token Fusion
Zhenzhen Chu, Jiayu Chen, Cen Chen +4
Self-attention-based vision transformers (ViTs) have emerged as a highly competitive architecture in computer vision. Unlike convolutional neural networks (CNNs), ViTs are capable…
Making Small Language Models Better Multi-task Learners with Mixture-of-Task-Adapters
Yukang Xie, Chengyu Wang, Junbing Yan +3
Recently, Large Language Models (LLMs) have achieved amazing zero-shot learning performance over a variety of Natural Language Processing (NLP) tasks, especially for text generativ…
PAI-Diffusion: Constructing and Serving a Family of Open Chinese Diffusion Models for Text-to-image Synthesis on the Cloud
Chengyu Wang, Zhongjie Duan, Bingyan Liu +4
Text-to-image synthesis for the Chinese language poses unique challenges due to its large vocabulary size, and intricate character relationships. While existing diffusion models ha…
TransPrompt v2: A Transferable Prompting Framework for Cross-task Text Classification
Jianing Wang, Chengyu Wang, Cen Chen +3
Text classification is one of the most imperative tasks in natural language processing (NLP). Recent advances with pre-trained language models (PLMs) have shown remarkable success…
DiffSynth: Latent In-Iteration Deflickering for Realistic Video Synthesis
Zhongjie Duan, Lizhou You, Chengyu Wang +4
In recent years, diffusion models have emerged as the most powerful approach in image synthesis. However, applying these models directly to video synthesis presents challenges, as…
On the Robustness of Split Learning against Adversarial Attacks
Mingyuan Fan, Cen Chen, Chengyu Wang +2
Split learning enables collaborative deep learning model training while preserving data privacy and model security by avoiding direct sharing of raw data and model details (i.e., s…
On the Trustworthiness Landscape of State-of-the-art Generative Models: A Survey and Outlook
Mingyuan Fan, Chengyu Wang, Cen Chen +2
Diffusion models and large language models have emerged as leading-edge generative models, revolutionizing various aspects of human life. However, the practical implementations of…
ConaCLIP: Exploring Distillation of Fully-Connected Knowledge Interaction Graph for Lightweight Text-Image Retrieval
Jiapeng Wang, Chengyu Wang, Xiaodan Wang +2
Large-scale pre-trained text-image models with dual-encoder architectures (such as CLIP) are typically adopted for various vision-language applications, including text-image retrie…
Towards Adaptive Prefix Tuning for Parameter-Efficient Language Model Fine-tuning
Zhen-Ru Zhang, Chuanqi Tan, Haiyang Xu +3
Fine-tuning large pre-trained language models on various downstream tasks with whole parameters is prohibitively expensive. Hence, Parameter-efficient fine-tuning has attracted att…
Optimal Linear Subspace Search: Learning to Construct Fast and High-Quality Schedulers for Diffusion Models
Zhongjie Duan, Chengyu Wang, Cen Chen +2
In recent years, diffusion models have become the most popular and powerful methods in the field of image synthesis, even rivaling human artists in artistic creativity. However, th…