Search: “pretraining”

DeCo: Frequency-Decoupled Pixel Diffusion for End-to-End Image Generation

arXiv:2511.19365v2 Announce Type: replace-cross Abstract: Pixel diffusion aims to generate images directly in pixel space in an end-to-end fashion. This approach avoids the limitations of VAE in the t

researcharxiv-cs-ai

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Discrete Flow Matching Policy Optimization

DGX agent

arXiv:2604.06491v1 Announce Type: cross Abstract: We introduce Discrete flow Matching policy Optimization (DoMinO), a unified framework for Reinforcement Learning (RL) fine-tuning Discrete Flow Matchi

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10 Apr 2026

Distilling Specialized Orders for Visual Generation

arXiv:2504.17069v2 Announce Type: replace Abstract: Autoregressive (AR) image generators are becoming increasingly popular due to their ability to produce high-quality images and their scalability. Ty

Drift-Based Policy Optimization: Native One-Step Policy Learning for Online Robot Control

arXiv:2604.03540v2 Announce Type: replace Abstract: Although multi-step generative policies achieve strong performance in robotic manipulation by modeling multimodal action distributions, they require

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Flux Attention: Context-Aware Hybrid Attention for Efficient LLMs Inference

model-releasesarxiv-cs-cl

arXiv:2604.07394v1 Announce Type: cross Abstract: The quadratic computational complexity of standard attention mechanisms presents a severe scalability bottleneck for LLMs in long-context scenarios. W

Hardware

Graph Neural ODE Digital Twins for Control-Oriented Reactor Thermal-Hydraulic Forecasting Under Partial Observability

arXiv:2604.07292v1 Announce Type: new Abstract: Real-time supervisory control of advanced reactors requires accurate forecasting of plant-wide thermal-hydraulic states, including locations where physi

hardwarearxiv-cs-lg

GroundingAnomaly: Spatially-Grounded Diffusion for Few-Shot Anomaly Synthesis

arXiv:2604.08301v1 Announce Type: new Abstract: The performance of visual anomaly inspection in industrial quality control is often constrained by the scarcity of real anomalous samples. Consequently,

How Independent are Large Language Models? A Statistical Framework for Auditing Behavioral Entanglement and Reweighting Verifier Ensembles

arXiv:2604.07650v1 Announce Type: cross Abstract: The rapid growth of the large language model (LLM) ecosystem raises a critical question: are seemingly diverse models truly independent? Shared pretra

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ImVideoEdit: Image-learning Video Editing via 2D Spatial Difference Attention Blocks

arXiv:2604.07958v1 Announce Type: new Abstract: Current video editing models often rely on expensive paired video data, which limits their practical scalability. In essence, most video editing tasks c

JoyAI-LLM Flash: Advancing Mid-Scale LLMs with Token Efficiency

model-releasesarxiv-cs-ai

arXiv:2604.03044v2 Announce Type: replace-cross Abstract: We introduce JoyAI-LLM Flash, an efficient Mixture-of-Experts (MoE) language model designed to redefine the trade-off between strong performan

Low-Rank Key Value Attention

arXiv:2601.11471v3 Announce Type: replace Abstract: The key-value (KV) cache is a primary memory bottleneck in Transformers. We propose Low-Rank Key-Value (LRKV) attention, which reduces KV cache memo

researcharxiv-cs-lg

Monocular Depth Estimation From the Perspective of Feature Restoration: A Diffusion Enhanced Depth Restoration Approach

arXiv:2604.07664v1 Announce Type: new Abstract: Monocular Depth Estimation (MDE) is a fundamental computer vision task with important applications in 3D vision. The current mainstream MDE methods empl

Non-identifiability of Explanations from Model Behavior in Deep Networks of Image Authenticity Judgments

arXiv:2604.07254v1 Announce Type: cross Abstract: Deep neural networks can predict human judgments, but this does not imply that they rely on human-like information or reveal the cues underlying those

researcharxiv-cs-lg

Local Ai

PixelCAM: Pixel Class Activation Mapping for Histology Image Classification and ROI Localization

arXiv:2503.24135v3 Announce Type: replace Abstract: Weakly supervised object localization (WSOL) methods allow training models to classify images and localize ROIs. WSOL only requires low-cost image-c

local-aiarxiv-cs-cv

Reinforcement-Guided Synthetic Data Generation for Privacy-Sensitive Identity Recognition

arXiv:2604.07884v1 Announce Type: new Abstract: High-fidelity generative models are increasingly needed in privacy-sensitive scenarios, where access to data is severely restricted due to regulatory an

Rethinking Entropy Allocation in LLM-based ASR: Understanding the Dynamics between Speech Encoders and LLMs

model-releasesarxiv-cs-cl

arXiv:2604.08003v1 Announce Type: cross Abstract: Integrating large language models (LLMs) into automatic speech recognition (ASR) has become a dominant paradigm. Although recent LLM-based ASR models

Semantic Noise Reduction via Teacher-Guided Dual-Path Audio-Visual Representation Learning

arXiv:2604.08147v1 Announce Type: cross Abstract: Recent advances in audio-visual representation learning have shown the value of combining contrastive alignment with masked reconstruction. However, j

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Stress Estimation in Elderly Oncology Patients Using Visual Wearable Representations and Multi-Instance Learning

arXiv:2604.06990v1 Announce Type: cross Abstract: Psychological stress is clinically relevant in cardio-oncology, yet it is typically assessed only through patient-reported outcome measures (PROMs) an

researcharxiv-cs-ai

The Illusion of Superposition? A Principled Analysis of Latent Thinking in Language Models

arXiv:2604.06374v1 Announce Type: cross Abstract: Latent reasoning via continuous chain-of-thoughts (Latent CoT) has emerged as a promising alternative to discrete CoT reasoning. Operating in continuo

researcharxiv-cs-lg

UniversalVTG: A Universal and Lightweight Foundation Model for Video Temporal Grounding

arXiv:2604.08522v1 Announce Type: new Abstract: Video temporal grounding (VTG) is typically tackled with dataset-specific models that transfer poorly across domains and query styles. Recent efforts to

Weakly-Supervised Lung Nodule Segmentation via Training-Free Guidance of 3D Rectified Flow

arXiv:2604.08313v1 Announce Type: new Abstract: Dense annotations, such as segmentation masks, are expensive and time-consuming to obtain, especially for 3D medical images where expert voxel-wise labe

You Point, I Learn: Online Adaptation of Interactive Segmentation Models for Handling Distribution Shifts in Medical Imaging

arXiv:2503.06717v3 Announce Type: replace Abstract: Interactive segmentation uses real-time user inputs, such as mouse clicks, to iteratively refine model predictions. Although not originally designed