32 citations · 97 across the 33 of their papers we have counts for
33 papers
MMLDSum-LLM: Multimodal Long-Document Summarization with Visual-Alignment and Keyword-Aware
Xianpeng Zhang, Jiahua Yang, Dongyu Chen +7
Multimodal long documents are core carriers of professional knowledge, where critical evidence is sparsely distributed across paragraphs and modalities. This easily causes key info…
Stabilizing On-Policy Distillation for MLLM Reasoning with Global Normalization
Dongze Hao, Zhiwei Jin, Chen Chen +1
On-policy distillation (OPD) has recently emerged as an important post-training paradigm. By using a stronger teacher model to provide dense, fine-grained supervision for sampled t…
expo: Exploration-prioritized policy optimization via adaptive kl regulation and gaussian curriculum sampling
Mingxiong Lin, Zhangquan Gong, Maowen Tang +6
Reinforcement Learning with Verifiable Rewards (RLVR) has become the standard paradigm for LLM mathematical reasoning, where Group Relative Policy Optimization (GRPO) serves as the…
fg-expo: Frontier-guided exploration-prioritized policy optimization via adaptive kl and gaussian curriculum
Mingxiong Lin, Zhangquan Gong, Maowen Tang +6
Reinforcement Learning with Verifiable Rewards (RLVR) has become the standard paradigm for LLM mathematical reasoning, with Group Relative Policy Optimization (GRPO) serving as the…
PixelPrune: Pixel-Level Adaptive Visual Token Reduction via Predictive Coding
Nan Wang, Zhiwei Jin, Chen Chen +1
Document understanding and GUI interaction are among the highest-value applications of Vision-Language Models (VLMs), yet they impose exceptionally heavy computational burden: fine…
Learning from Prompt itself: the Hierarchical Attribution Prompt Optimization
Dongyu Chen, Jian Ma, Xianpeng Zhang +5
Optimization is fundamental across numerous disciplines, typically following an iterative process of refining an initial solution to enhance performance. This principle is equally…
Pluggable Pruning with Contiguous Layer Distillation for Diffusion Transformers
Jian Ma, Qirong Peng, Xujie Zhu +3
Diffusion Transformers (DiTs) have shown exceptional performance in image generation, yet their large parameter counts incur high computational costs, impeding deployment in resour…
X2Edit: Revisiting Arbitrary-Instruction Image Editing through Self-Constructed Data and Task-Aware Representation Learning
Jian Ma, Xujie Zhu, Zihao Pan +4
Existing open-source datasets for arbitrary-instruction image editing remain suboptimal, while a plug-and-play editing module compatible with community-prevalent generative models…
X2I: Seamless Integration of Multimodal Understanding into Diffusion Transformer via Attention Distillation
Jian Ma, Qirong Peng, Xu Guo +3
Text-to-image (T2I) models are well known for their ability to produce highly realistic images, while multimodal large language models (MLLMs) are renowned for their proficiency in…
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…
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…
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…
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…
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…
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…
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…
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…
PEA-Diffusion: Parameter-Efficient Adapter with Knowledge Distillation in non-English Text-to-Image Generation
Jian Ma, Chen Chen, Qingsong Xie +1
Text-to-image diffusion models are well-known for their ability to generate realistic images based on textual prompts. However, the existing works have predominantly focused on Eng…
Interactive Interior Design Recommendation via Coarse-to-fine Multimodal Reinforcement Learning
He Zhang, Ying Sun, Weiyu Guo +4
Personalized interior decoration design often incurs high labor costs. Recent efforts in developing intelligent interior design systems have focused on generating textual requireme…
MCAD: Multi-teacher Cross-modal Alignment Distillation for efficient image-text retrieval
Youbo Lei, Feifei He, Chen Chen +4
Due to the success of large-scale visual-language pretraining (VLP) models and the widespread use of image-text retrieval in industry areas, it is now critically necessary to reduc…
MoEController: Instruction-based Arbitrary Image Manipulation with Mixture-of-Expert Controllers
Sijia Li, Chen Chen, Haonan Lu
Diffusion-model-based text-guided image generation has recently made astounding progress, producing fascinating results in open-domain image manipulation tasks. Few models, however…
Subject-Diffusion:Open Domain Personalized Text-to-Image Generation without Test-time Fine-tuning
Jian Ma, Junhao Liang, Chen Chen +1
Recent progress in personalized image generation using diffusion models has been significant. However, development in the area of open-domain and non-fine-tuning personalized image…
Prompt Space Optimizing Few-shot Reasoning Success with Large Language Models
Fobo Shi, Peijun Qing, Dong Yang +5
Prompt engineering is an essential technique for enhancing the abilities of large language models (LLMs) by providing explicit and specific instructions. It enables LLMs to excel i…
Towards Language-guided Interactive 3D Generation: LLMs as Layout Interpreter with Generative Feedback
Yiqi Lin, Hao Wu, Ruichen Wang +4
Generating and editing a 3D scene guided by natural language poses a challenge, primarily due to the complexity of specifying the positional relations and volumetric changes within…