Diffusion and generative media

Image, video and audio generation — diffusion models, flow matching and the systems built on top of them.

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arXiv Machine Learning

Jul 28

Where Quality Breaks in Compressed Short-Text Generation: Staged Bottleneck Localization

arXiv:2607. 24176v1 Announce Type: cross Abstract: Compressed short-text generators can fail in two different places: the codec may discard information before generation starts, or the latent generator may produce weak codes.

By Alexey Gavrilov, Alan-Barsag Gazzaev, Sergey Muravyov

llms diffusion

arXiv AI

Jul 28

Escaping the Euclidean Void: Manifold-Informed Flow Matching for Sequential Recommendation

arXiv:2607. 23762v1 Announce Type: cross Abstract: Conventional recommenders capture users' preferences by optimizing observed user-item relations, whereas continuous generative recommendation additionally learns the trajectory of synthesizing a target item.

By Dengzhao Fang, Jingtong Gao, Yu Li, Xiangyu Zhao, Yi Chang

rag diffusion benchmarks

arXiv Machine Learning

Jul 28

Accelerating Frequency Domain Diffusion Models with Error-Feedback Event-Driven Caching

arXiv:2604. 22901v2 Announce Type: replace Abstract: Diffusion models achieve remarkable success in time series generation.

By Dong Liu, Yanxuan Yu, Ying Nian Wu

llms diffusion

arXiv AI

Jul 28

Bridging MARL to SARL: An Order-Independent Multi-Agent Transformer via Latent Consensus

arXiv:2604. 13472v2 Announce Type: replace-cross Abstract: Cooperative multi-agent reinforcement learning (MARL) is widely used to address large joint observation and action spaces by decomposing a centralized control problem into multiple interacting agents.

By Zijian Zhao, Jing Gao, Sen Li

llms agents diffusion reinforcement-learning benchmarks

arXiv AI

Jul 28

FILLER: Feature Imputation via Latent Location Exploration and Retrieval

arXiv:2607. 23295v1 Announce Type: cross Abstract: In real-world machine learning applications, incomplete observations create a fundamental challenge.

By Santu Mondal, Chayan Maitra, Rajat K. De

diffusion benchmarks

arXiv Machine Learning

Jul 28

WorldDiT: A Unified Diffusion Architecture for World and Action Modeling

arXiv:2607. 23909v1 Announce Type: new Abstract: Many recent robot policies pursue stronger control by using large pretrained vision-language models (VLMs) as the action backbone.

By Sen Wang, R. Gnana Praveen, Bidhan Roy, Marcos Villagra

llms diffusion robotics multimodal

arXiv AI

Jul 28

ChangeFlow -- Latent Rectified Flow for Change Detection in Remote Sensing

arXiv:2605. 15375v2 Announce Type: replace-cross Abstract: Remote sensing change detection (RSCD) localises changes between two images of the same geographic region.

By Bla\v{z} Rolih, Matic Fu\v{c}ka, Filip Wolf, Luka \v{C}ehovin Zajc

diffusion benchmarks

arXiv Machine Learning

Jul 28

LanteRn: Latent Visual Structured Reasoning

arXiv:2603. 25629v2 Announce Type: replace-cross Abstract: While language reasoning models excel in many tasks, visual reasoning remains challenging for current large multimodal models (LMMs).

By Andr\'e G. Viveiros, Nuno Gon\c{c}alves, Matthias Lindemann, Andr\'e Martins

llms rag diffusion reinforcement-learning fine-tuning multimodal benchmarks

arXiv Machine Learning

Jul 28

Restoration Flow Matching-Based Channel Refinement and Equalization Correction for MIMO Semantic Communications

arXiv:2607. 23615v1 Announce Type: new Abstract: In multiple-input multiple-output (MIMO) semantic communication, imperfect channel state information (CSI) and equalization mismatch can seriously degrade semantic reconstruction quality.

By Wenkai Liu, Nan Ma, Jianqiao Chen, Xiaodong Xu, Meixia Tao, Ping Zhang

diffusion

arXiv Machine Learning

Jul 28

Learning Sampling Parameters for Diffusion Models

arXiv:2607. 23488v1 Announce Type: new Abstract: Text-to-image diffusion models expose many inference-time sampling parameters, including prompts, negative prompts, classifier-free guidance scales, and noise schedules.

By Arisrei Lim, Yossi Gandelsman

llms diffusion reinforcement-learning multimodal

arXiv AI

Jul 28

What CLIP Knows but Cannot Say: Recovering Negation from Frozen Intermediate Features

arXiv:2607. 23271v1 Announce Type: cross Abstract: Contrastive vision-language models such as CLIP map semantically opposite phrases (e.

By Chen-Yi Lu, Yueh-Shao Chen, Somali Chaterji

llms rag diffusion fine-tuning multimodal safety

arXiv AI

Jul 28

FMOPF: Latent Flow Matching with Constraint-Aware Interaction Priors for AC Optimal Power Flow

arXiv:2607. 22788v1 Announce Type: cross Abstract: AC optimal power flow determines the minimum-cost generation dispatch under nonlinear power balance constraints and is solved thousands of times daily in electricity market operations.

By Zhilin Huang

diffusion benchmarks

arXiv AI

Jul 28

X-Stage: An Overlooked Pipeline Stage for Communication-Computation Overlap in DiT Inference

arXiv:2607. 23264v1 Announce Type: cross Abstract: Fine-grained, device-initiated communication lets persistent GPU kernels in distributed diffusion transformer (DiT) inference issue remote stores and overlap data movement with Tensor Core computation.

By Jianwen Xian, Zhiyuan Xu, Yuchen Li, Ziliang Lai, Kang He, Zhen Huang, Aichen Feng, Jinyan Chen, Yilin Zhang, Qinqin Chen, Chengru Song

llms diffusion

arXiv AI

Jul 28

MegaSlide-DiT: Memory-Centric Adaptation and Deformable Local Attention for Efficient Video Diffusion

arXiv:2607. 22696v1 Announce Type: cross Abstract: High-resolution video diffusion models built on Diffusion Transformers (DiTs) deliver strong fidelity but quickly exhaust the memory budget of a single workstation.

By Jiacheng Liu, Jason Liu

llms diffusion

arXiv AI

Jul 28

UNIFUSION: Adapting Autoregressive Language Models into Discrete Diffusion under a Unified Reverse-Rate Objective

arXiv:2607. 24507v1 Announce Type: cross Abstract: Existing methods mainly adapt pretrained autoregressive (AR) language models to masked diffusion, whereas we directly adapt them to uniform-noise diffusion, where every token remains editable during sampling.

By Xiaoyi Jiang, Jingyuan Li, Yixuan Jiang, Wei Liu, Yi Zhu, Zuoqiang Shi, Pipi Hu

llms diffusion

arXiv AI

Jul 28

Spectral Dynamics of Semantic Drift in Clinical Multi-Agent Language Model Networks

arXiv:2607. 22758v1 Announce Type: cross Abstract: The integration of iterative LLMs within multi-agent diagnostic frameworks requires a rigorous quantitative reevaluation of underlying communication topologies.

By Amritesh Banerjee

llms rag agents diffusion safety

arXiv Machine Learning

Jul 28

From Score Learning to Discretized Sampling: An End-to-End Generalization Analysis of Diffusion Models

arXiv:2607. 23226v1 Announce Type: new Abstract: Despite the empirical success of score-based diffusion models, a complete theoretical understanding of how finite-sample learning, network parameterization, and numerical discretization jointly dictate generative quality remains underdeveloped.

By Jinshu Huang, Yiming Jiang, Chunlin Wu

diffusion

arXiv Machine Learning

Jul 28

Data-Driven Diffusion Processes on Differential Forms via the Projected Ambient Connection Laplacian

arXiv:2607. 23192v1 Announce Type: cross Abstract: We develop a data-driven approximation of the projected ambient connection Laplacian acting on differential forms over smooth Riemannian manifolds sampled by point clouds.

By Alvaro Almeida Gomez, Jorge Duque Franco

diffusion

arXiv AI

Jul 28

Hybrid Semantic and Spectral Ensemble for Robust Synthetic Image Source Attribution

arXiv:2607. 22808v1 Announce Type: cross Abstract: The rapid advancement of text-to-image (T2I) models has necessitated robust Synthetic Image Source Attribution (SIA) methodologies.

By Md. Ajwad Hossain

diffusion benchmarks

arXiv AI

Jul 28

Token-Region Guided Cross-Attention Fusion for Multimodal Affect Interpretation

arXiv:2607. 23493v1 Announce Type: cross Abstract: Automated analysis of multimodal content on social networks has become a critical task for understanding public sentiment and information diffusion in the digital age.

By Musa Tur Farazi, Nufayer Jahan Reza

llms diffusion computer-vision multimodal benchmarks safety