3 citations · 8 across the 16 of their papers we have counts for
19 papers
Reinforcement Learning-driven Diffusion Models: Language, Vision, and Beyond
Zhiyuan Ma, Jiabao Wei, Tianyu Wang +21
Diffusion models (DMs) have steadily demonstrated outstanding performance in high-fidelity, controllable generation across diverse scenarios, following the "pretraining-finetuning"…
Unified Trajectory Matching Policy Optimization: Diverse T2I Generation and VLA Generalization
Zhiyuan Ma, Jiaming Li, Lingzhen Li +7
Reward-maximizing reinforcement learning (RL) is widely used to post-train stochastic diffusion and flow policies for text-to-image (T2I) generation. However, reward-maximizing RL…
DynaPPI: A Large-scale Dynamic Protein Dataset for AI-driven Advances in Protein Interactomics
Jiabao Wei, Zilong Geng, Yuze Wang +5
Diffusion models have been widely explored in protein backbone generation due to their powerful generation capabilities.However, in today's AI-driven biological research, predictin…
Distilling Physical Priors into Streaming World Models
Liangliang Zhao, Junying Wang, Danni Yang +5
Streaming world models predict future visual states online while maintaining physically coherent dynamics over long horizons. However, their rollouts often violate basic physical c…
SciIR: A Large-scale Training Dataset and Benchmark for Scientific Image Reasoning Generation
Zhiyuan Ma, Zhengfeng Shi, Yuning An +6
While Text-to-Image (T2I) models have shown remarkable success in generating photorealistic visual content, they still struggle with the rigorous semantic alignment and logical rea…
TMPO: Trajectory Matching Policy Optimization for Diverse and Efficient Diffusion Alignment
Jiaming Li, Chenyu Zhu, Nanxi Yi +9
Reinforcement learning (RL) has shown extraordinary potential in aligning diffusion models to downstream tasks, yet most of them still suffer from significant reward hacking, which…
Achieving Gold-Medal-Level Olympiad Reasoning via Simple and Unified Scaling
Yafu Li, Runzhe Zhan, Haoran Zhang +25
Recent progress in reasoning models has substantially advanced long-horizon mathematical and scientific problem solving, with several systems now reaching gold-medal-level performa…
Spatio-Temporal Token Pruning for Efficient High-Resolution GUI Agents
Zhou Xu, Bowen Zhou, Qi Wang +2
Pure-vision GUI agents provide universal interaction capabilities but suffer from severe efficiency bottlenecks due to the massive spatiotemporal redundancy inherent in high-resolu…
PRISMA: Reinforcement Learning Guided Two-Stage Policy Optimization in Multi-Agent Architecture for Open-Domain Multi-Hop Question Answering
Yu Liu, Wenxiao Zhang, Cong Cao +10
Answering real-world open-domain multi-hop questions over massive corpora is a critical challenge in Retrieval-Augmented Generation (RAG) systems. Recent research employs reinforce…
I2E: From Image Pixels to Actionable Interactive Environments for Text-Guided Image Editing
Jinghan Yu, Junhao Xiao, Chenyu Zhu +9
Existing text-guided image editing methods primarily rely on end-to-end pixel-level inpainting paradigm. Despite its success in simple scenarios, this paradigm still significantly…
Emotion-Director: Bridging Affective Shortcut in Emotion-Oriented Image Generation
Guoli Jia, Junyao Hu, Xinwei Long +5
Image generation based on diffusion models has demonstrated impressive capability, motivating exploration into diverse and specialized applications. Owing to the importance of emot…
Flow Diverse and Efficient: Learning Momentum Flow Matching via Stochastic Velocity Field Sampling
Zhiyuan Ma, Ruixun Liu, Sixian Liu +2
Recently, the rectified flow (RF) has emerged as the new state-of-the-art among flow-based diffusion models due to its high efficiency advantage in straight path sampling, especial…
Context-Aware Autoregressive Models for Multi-Conditional Image Generation
Yixiao Chen, Zhiyuan Ma, Guoli Jia +3
Autoregressive transformers have recently shown impressive image generation quality and efficiency on par with state-of-the-art diffusion models. Unlike diffusion architectures, au…
Retrieval-Augmented Visual Question Answering via Built-in Autoregressive Search Engines
Xinwei Long, Zhiyuan Ma, Ermo Hua +3
Retrieval-augmented generation (RAG) has emerged to address the knowledge-intensive visual question answering (VQA) task. Current methods mainly employ separate retrieval and gener…
Efficient Diffusion Models: A Comprehensive Survey from Principles to Practices
Zhiyuan Ma, Yuzhu Zhang, Guoli Jia +7
As one of the most popular and sought-after generative models in the recent years, diffusion models have sparked the interests of many researchers and steadily shown excellent adva…
Safe-SD: Safe and Traceable Stable Diffusion with Text Prompt Trigger for Invisible Generative Watermarking
Zhiyuan Ma, Guoli Jia, Biqing Qi +1
Recently, stable diffusion (SD) models have typically flourished in the field of image synthesis and personalized editing, with a range of photorealistic and unprecedented images b…
Generative Multi-Modal Knowledge Retrieval with Large Language Models
Xinwei Long, Jiali Zeng, Fandong Meng +4
Knowledge retrieval with multi-modal queries plays a crucial role in supporting knowledge-intensive multi-modal applications. However, existing methods face challenges in terms of…
AdapEdit: Spatio-Temporal Guided Adaptive Editing Algorithm for Text-Based Continuity-Sensitive Image Editing
Zhiyuan Ma, Guoli Jia, Bowen Zhou
With the great success of text-conditioned diffusion models in creative text-to-image generation, various text-driven image editing approaches have attracted the attentions of many…
LMD: Faster Image Reconstruction with Latent Masking Diffusion
Zhiyuan Ma, zhihuan yu, Jianjun Li +1
As a class of fruitful approaches, diffusion probabilistic models (DPMs) have shown excellent advantages in high-resolution image reconstruction. On the other hand, masked autoenco…