activity
20192026
most citedGraph Star Net for Generalized Multi-Task Learning

32 citations · 97 across the 33 of their papers we have counts for

collaborators
Showing 2024Show all

8 papers · 1 filter

cs.SE2024

GenX: Mastering Code and Test Generation with Execution Feedback

Nan Wang, Yafei Liu, Chen Chen +1

Recent advancements in language modeling have enabled the translation of natural language into code, and the use of execution feedback to improve code generation. However, these me…

cs.CV2024

PainterNet: Adaptive Image Inpainting with Actual-Token Attention and Diverse Mask Control

Ruichen Wang, Junliang Zhang, Qingsong Xie +2

Recently, diffusion models have exhibited superior performance in the area of image inpainting. Inpainting methods based on diffusion models can usually generate realistic, high-qu…

cs.CV2024

GlyphDraw2: Automatic Generation of Complex Glyph Posters with Diffusion Models and Large Language Models

Jian Ma, Yonglin Deng, Chen Chen +3

Posters play a crucial role in marketing and advertising by enhancing visual communication and brand visibility, making significant contributions to industrial design. With the lat…

cs.CV2024

TLCM: Training-efficient Latent Consistency Model for Image Generation with 2-8 Steps

Qingsong Xie, Zhenyi Liao, Zhijie Deng +2

Distilling latent diffusion models (LDMs) into ones that are fast to sample from is attracting growing research interest. However, the majority of existing methods face two critica…

cs.CV2024★ 1 cited

LAPTOP-Diff: Layer Pruning and Normalized Distillation for Compressing Diffusion Models

Dingkun Zhang, Sijia Li, Chen Chen +2

In the era of AIGC, the demand for low-budget or even on-device applications of diffusion models emerged. In terms of compressing the Stable Diffusion models (SDMs), several approa…

cs.CL2024★ 1 cited

InsCL: A Data-efficient Continual Learning Paradigm for Fine-tuning Large Language Models with Instructions

Yifan Wang, Yafei Liu, Chufan Shi +4

Instruction tuning effectively optimizes Large Language Models (LLMs) for downstream tasks. Due to the changing environment in real-life applications, LLMs necessitate continual ta…

cs.CV2024

SCott: Accelerating Diffusion Models with Stochastic Consistency Distillation

Hongjian Liu, Qingsong Xie, TianXiang Ye +6

The iterative sampling procedure employed by diffusion models (DMs) often leads to significant inference latency. To address this, we propose Stochastic Consistency Distillation (S…

cs.CV2024

Dream360: Diverse and Immersive Outdoor Virtual Scene Creation via Transformer-Based 360 Image Outpainting

Hao Ai, Zidong Cao, Haonan Lu +6

360 images, with a field-of-view (FoV) of 180x360, provide immersive and realistic environments for emerging virtual reality (VR) applications, such as virtual tourism, where users…