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Distortion-Corrected Diffusion MRI Using Rotated-View EPI and Joint Field-Map/Image Estimation with Gaussian Primitives

arXiv:2606.31521v1 Announce Type: cross Abstract: Echo Planar Imaging (EPI) is the standard acquisition technique for diffusion and functional neuroimaging, enabling rapid imaging but suffering from g

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Do Not Break the Vessels: Structure-Preserving Mean Flow for Vascular Image Translation

DGX agent

arXiv:2606.31095v1 Announce Type: new Abstract: Reconstructing anatomically faithful vascular structures from clinically accessible imaging modalities is of substantial clinical significance. However,

researcharxiv-cs-cv

1 Jul 2026

Domain Adaptive Object Detection via Dual-Stream Bilevel-Cycle Optimization

arXiv:2606.31373v1 Announce Type: new Abstract: Cycle self-training (CST) breaks the shared classifier assumption of the standard self-training framework, which is effective for unsupervised domain ad

Domain-Decomposed Randomized Neural Networks for Partial Differential Equations in Unbounded Domains

arXiv:2606.31342v1 Announce Type: cross Abstract: Partial differential equations on unbounded domains are challenging because the exterior region must be represented without excessive truncation error

DPPE: Rethinking Camera-Based Positional Encoding for Scaling Multi-View Transformers

arXiv:2606.31585v1 Announce Type: cross Abstract: The remarkable scalability of Transformers has expanded their application to 3D computer vision, where camera-aware positional encoding is crucial for

researcharxiv-cs-ai

DriveWeaver: Point-Conditioned Video Inpainting for Controllable Vehicle Insertion in Autonomous Driving Simulation

arXiv:2606.31918v1 Announce Type: new Abstract: A pivotal step in autonomous driving simulation involves inserting foreground vehicles with predefined trajectories into simulated scenes. This process

agentsarxiv-cs-cv

DrivingDepth: Sparse-Prompted Pixel-wise Scale Correction for Driving Depth Estimation

arXiv:2606.31488v1 Announce Type: new Abstract: Dense depth estimation for autonomous driving faces a geometry-scale conflict: depth foundation models deliver pixel-aligned dense visual geometry witho

agentsarxiv-cs-cv

Drop-In Perceptual Optimization for 3D Gaussian Splatting

arXiv:2603.23297v2 Announce Type: replace Abstract: Despite their output being ultimately consumed by human viewers, 3D Gaussian Splatting (3DGS) methods often rely on ad-hoc combinations of pixel-lev

DSIP: A Dynamic Coordination Planner for Signal-Free Intersections using Diffusion-Model-Based Multi-Agent Motion Planning

arXiv:2606.30694v1 Announce Type: cross Abstract: Traffic signal control at urban intersections inherently introduces stop-and-go behavior, resulting in increased delays and reduced traffic efficiency

agentsarxiv-cs-ai

Dual Sparse Aggregation Transformer for Multispectral Object Detection

arXiv:2606.31015v1 Announce Type: new Abstract: Transformer-based approaches have obtained excellent performance in multispectral object detection tasks due to their ability to model long-range depend

Dualformer: Efficient Feature Extractor for Complex-valued Blind Communication Signal Analysis

arXiv:2606.31352v1 Announce Type: new Abstract: Designing effective feature extractors is critical for blind signal analysis tasks such as automatic modulation recognition (AMR), signal scheme recogni

Applications

DVG-WM: Disentangled Video Generation Enables Efficient Embodied World Model for Robotic Manipulation

arXiv:2606.32028v1 Announce Type: new Abstract: Video-based embodied world models provide an appealing substrate for robotic manipulation by predicting future states, yet current approaches remain lim

applicationsarxiv-cs-ro

Dynamic Gaussian Processes and the Vanilla-SPDE Exchange

arXiv:2606.31063v1 Announce Type: cross Abstract: Gaussian process inference is often limited by cubic computational costs, a challenge that becomes more pronounced in spatio-temporal settings where p

Dynamic Prediction of Alternating Recurrent Events via Neural Network

arXiv:2606.30889v1 Announce Type: cross Abstract: Alternating recurrent events -- event-times of a specific nature that trigger a secondary refractory period -- occur in a wide-range of fields, includ

DynFly: Dynamic-Aware Continuous Trajectory Generation for UAV Vision-Language Navigation in Urban Environments

arXiv:2606.31654v1 Announce Type: cross Abstract: Recent advances in multimodal large models have significantly improved UAV vision-language navigation (UAV-VLN) by enhancing high-level perception and

E-VLA: Event-Augmented Vision-Language-Action Model for Dark and Blurred Scenes

arXiv:2604.04834v2 Announce Type: replace Abstract: Robotic Vision-Language-Action (VLA) models generalize well for open-ended manipulation, but their perception is fragile under sensing-stage degrada

Early-Terminable Energy-Safe Iterative Coupling for Parallel Simulation of Partitioned Port-Hamiltonian Systems

model-releasesarxiv-cs-ro

arXiv:2603.16424v2 Announce Type: replace Abstract: Parallel simulation of robotic systems requires partitioning the dynamics into coupled subsystems. Finite-iteration coupling across the partition bo

ECHO: Prune to act, trace to learn with selective turn memory in agentic RL

arXiv:2606.31650v1 Announce Type: cross Abstract: Long-horizon language agents must repeatedly interact with tools, accumulate evidence, and make decisions under bounded context windows. Existing cont

safetyarxiv-cs-ai

Editing Everything Everywhere All at Once

arXiv:2606.31278v1 Announce Type: new Abstract: Editing multiple elements of an image in a single forward pass is a practical alternative to multi-turn image manipulation, offering improved efficiency

Efficient Public Verification of Private ML via Regularization

arXiv:2512.04008v2 Announce Type: replace Abstract: Training with differential privacy (DP) guarantees dataset members that they cannot be identified by users of the released model. However, those dat

Efficient Sampling with Discrete Diffusion Models: Sharp and Adaptive Guarantees

arXiv:2602.15008v2 Announce Type: replace Abstract: Diffusion models over discrete spaces have recently shown striking empirical success, yet their theoretical foundations remain incomplete. In this p

Efficient Sim-to-Real Transfer of World-Action Models from Synthetic Priors

arXiv:2606.31101v1 Announce Type: new Abstract: Bridging the sim-to-real gap is a core challenge in deploying learned manipulation policies. Sim-to-real learning is attractive because it can replace e

safetyarxiv-cs-ro

Applications

EgoCogNav: Cognition-aware Human Egocentric Navigation

arXiv:2511.17581v3 Announce Type: replace-cross Abstract: Modeling the cognitive and experiential factors of human navigation is central to deepening our understanding of human-environment interaction

applicationsarxiv-cs-cv

EgoVITA: Learning to Plan and Verify for Egocentric Video Reasoning

arXiv:2511.18242v3 Announce Type: replace Abstract: Egocentric video understanding requires procedural reasoning under partial observability and continuously shifting viewpoints. Current multimodal la

safetyarxiv-cs-cv

ELASTIC: Efficiently Learning to Adaptively Scale Test-Time Compute for Generative Control Policies

arXiv:2606.31132v1 Announce Type: new Abstract: Generative control policies (GCPs), such as diffusion policies and flow-based vision-language-action models, enable test-time scaling in robot control.

safetyarxiv-cs-ro

ElemeNet: Multiscale Molecular Machine Learning with Uncertainty Quantification Across the Periodic Table

arXiv:2606.30961v1 Announce Type: cross Abstract: Advances in deep learning architectures and representations have enabled ML-driven chemical property prediction, but state-of-the-art (SOTA) models ha

Local Ai

ELEVATE: Designing Human-Centered GenAI Virtual Tutors for Scalable and Inclusive Education

arXiv:2606.30662v1 Announce Type: cross Abstract: The advent of Generative Artificial Intelligence (GenAI), and in particular Large Language Models (LLMs), is reshaping educational practice, while int

local-aiarxiv-cs-ai

Embodied CAD: Solver-Grounded LLM Agents for Parametric B-Rep Assembly Modeling

model-releasesarxiv-cs-ai

arXiv:2606.31252v1 Announce Type: new Abstract: Large language models can write plausible CAD scripts, but reliable industrial CAD modeling requires more than syntactically valid code: every feature,

Emergent Culture in Minimal LLM Systems

arXiv:2606.30668v1 Announce Type: cross Abstract: What happens when LLM agents operate with no context outside a turn, minimal prompting, and simple tools? Inspired by swarm engineering, we give colle

agentsarxiv-cs-ai

End-to-End Efficient RL for Linear Bellman Complete MDPs with Deterministic Transitions

arXiv:2603.23461v2 Announce Type: replace Abstract: We study reinforcement learning (RL) with linear function approximation in Markov Decision Processes (MDPs) satisfying linear Bellman completeness -

safetyarxiv-cs-lg

Energy-Optimal Spatial Iterative Learning within a Virtual Tube

model-releasesarxiv-cs-ro

arXiv:2606.31487v1 Announce Type: new Abstract: Due to the limited endurance of embedded energy sources such as lithium-polymer (LiPo) batteries, the flight duration and operational range of unmanned

Enhancing Graph Representations with Neighborhood-Contextualized Message-Passing

model-releasesarxiv-cs-ai

arXiv:2511.11046v3 Announce Type: replace-cross Abstract: Graph neural networks (GNNs) have become an indispensable tool for analyzing relational data. Classical GNNs are broadly classified into three

EpiMask: Leveraging Epipolar Distance Based Masks in Cross-Attention for Satellite Image Matching

arXiv:2603.21463v2 Announce Type: replace Abstract: The deep-learning based image matching networks can now handle significantly larger variations in viewpoints and illuminations while providing match

ERA: Entropy-Guided Visual Token Pruning with Rectified Attention for Efficient MLLMs

arXiv:2606.31982v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) incur prohibitive inference costs due to long visual token sequences. Training-free visual token reduction prov

safetyarxiv-cs-cv

Estimating Supply Incrementality in Two-sided Marketplaces: A Causal Machine Learning Approach

arXiv:2606.30999v1 Announce Type: new Abstract: In two-sided marketplaces with heterogeneous products, it is important to understand the causal relationship between additional supply and marketplace o

Estimating the Effect of Timing on Coupon Effectiveness

arXiv:2606.30664v1 Announce Type: cross Abstract: The coupon incentive is one of the most common tools marketers use to court users to engage with a business at various stages of the customer life cyc

researcharxiv-cs-ai

Estimating Velocity of Spheres from Rolling-Shutter Image(s)

arXiv:2606.31760v1 Announce Type: new Abstract: Rolling-shutter cameras introduce characteristic distortions when imaging fast moving objects, and these effects are typically treated as artifacts to b

Applications

Evaluation of Population Initialization Methods for Genetic Programming-based Symbolic Regression

arXiv:2606.31990v1 Announce Type: cross Abstract: We analyze the effect of optimizing the initial population of genetic programming (GP) for symbolic regression (SR) on the accuracy and complexity of

applicationsarxiv-cs-lg

Local Ai

Event-Driven Video Generation

arXiv:2603.13402v3 Announce Type: replace Abstract: Current text-to-video models can make individual frames look convincing while still getting simple interactions wrong: objects move before contact,

local-aiarxiv-cs-cv

Evidence Triangulation for Multimodal Fact-Checking in the Wild

arXiv:2606.31367v1 Announce Type: cross Abstract: The proliferation of multimedia content on social platforms has fueled multimodal misinformation, where images are used to reinforce false claims. Con

Evil Spectra: How Optimisers can Amplify or Suppress Emergent Misalignment

arXiv:2606.31591v1 Announce Type: cross Abstract: Emergent misalignment (EM) is a recently discovered phenomenon in LLMs where fine-tuning on a narrow misaligned task, such as writing insecure code, l

safetyarxiv-cs-ai

Evo-PI: Aligning Medical Reasoning via Evolving Principle-Guided Supervision

arXiv:2606.31800v1 Announce Type: new Abstract: Despite recent progress, the reasoning capabilities of large multimodal language models (MLLMs) remain fundamentally constrained by static supervision,

safetyarxiv-cs-ai

Expected Gain-based Escalation in Vertical Federated Learning

arXiv:2606.31331v1 Announce Type: new Abstract: Collaborative inference can improve predictive performance by integrating complementary information across agents, but applying collaborative fusion to

Explainable Artificial Intelligence For The Detection and Characterisation of Stage B Heart Failure

arXiv:2606.30665v1 Announce Type: cross Abstract: Stage B heart failure is characterized by asymptomatic structural or functional cardiac abnormalities. Identifying individuals at this stage is clinic

safetyarxiv-cs-lg

Explaining Machine Learning and Memorization with Statistical Mechanics

arXiv:2606.31110v1 Announce Type: new Abstract: Artificial neural networks (NNs) and machine learning (ML) algorithms are poorly understood from a theoretical perspective, which makes it difficult to

Explicit Fuzzy Logic in the Feed-Forward Layer: Self-Forgetting Quantifiers Discover Legible Grammatical-Licensing Detectors

model-releasesarxiv-cs-cl

arXiv:2606.31845v1 Announce Type: new Abstract: A transformer's feed-forward (FFN) sublayer materializes the distinctions attention gathers, yet gives no account of what it computes. In a parameter-ne

ExPLoRe: Expert Patch-Level Loss Routing for Multi-Objective Masked Image Modeling

arXiv:2606.31201v1 Announce Type: new Abstract: Multi-objective masked image modeling (MIM) combines complementary learning signals (token distillation, CLS alignment, and pixel reconstruction) but ex

safetyarxiv-cs-cv

Exploring the relationship between team institutional composition and novelty in academic papers based on fine-grained knowledge entities

arXiv:2606.31058v1 Announce Type: new Abstract: The composition of author teams is an important factor influencing the novelty of academic papers. However, existing studies have paid limited attention

researcharxiv-cs-cl