Search: “framework”

Communication-Aware Robot Execution for Cloud Inference under Spatially Heterogeneous Connectivity

arXiv:2606.31497v1 Announce Type: new Abstract: Cloud-hosted foundation models enable robots to use semantic reasoning beyond onboard computational limits. In this setting, the robot executes a curren

researcharxiv-cs-ro

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Research

Conformalized Regression for Continuous Bounded Outcomes

DGX agent

arXiv:2507.14023v2 Announce Type: replace-cross Abstract: Regression problems with bounded continuous outcomes frequently arise in statistical and machine learning applications, such as the analysis o

researcharxiv-cs-lg

1 Jul 2026

Applications

CoReLIN: Constraint-based Reasoning for Zero-shot Lifelong Interactive Navigation

arXiv:2602.20055v2 Announce Type: replace-cross Abstract: Robot navigation typically assumes an obstacle-free path exists between start and goal. In real environments, however, clutter may block all r

applicationsarxiv-cs-ai

Corruption Robust Offline Reinforcement Learning with Human Feedback

arXiv:2402.06734v2 Announce Type: replace-cross Abstract: We study data corruption robustness for reinforcement learning with human feedback (RLHF) in an offline setting. Given an offline dataset of p

Cross-Domain Feature Expansion for Tabular Medical Data via Knowledge Graphs Injection

arXiv:2606.31171v1 Announce Type: new Abstract: Acquiring comprehensive cross-domain biomedical profiles is often costly and time-consuming, resulting in severe data scarcity in medical research. To a

Cross-Modal Hierarchical Fusion for from Multi-Sensor Ground Observation

arXiv:2606.30647v1 Announce Type: cross Abstract: Dense volumetric reconstruction of cloud microphysical fields from sparse ground-based instruments remains an open problem, largely because the availa

Cross-Resolution Distribution Matching for Diffusion Distillation

arXiv:2603.06136v2 Announce Type: replace Abstract: Diffusion distillation is central to accelerating image and video generation, yet existing methods are fundamentally limited by the denoising proces

CSO-LLM: Class Subspace Orthogonalization for Post-Training Backdoor Detection and Trigger Inversion in LLMs

arXiv:2606.31309v1 Announce Type: cross Abstract: While post-training backdoor detection and trigger inversion schemes have been developed for AIs used e.g. for images, there is a paucity of such meth

CSTrader: A Testbed for Language-Grounded Trading in a Community-Driven Virtual Asset Market

arXiv:2606.31461v1 Announce Type: new Abstract: Niche asset markets, such as Counter-Strike 2 (CS2) weapon skins, are small, volatile, and heavily driven by community discussions and platform rules. T

Curvature-Guided Module Localization for Low-Rank Detoxification of Backdoored Large Language Models

arXiv:2606.30899v1 Announce Type: cross Abstract: Backdoor attacks pose a serious threat to large language models (LLMs) by causing otherwise benign systems to produce attacker-specified malicious beh

CVE-TTP KG: Knowledge Graph Linking Software Vulnerabilities to Attack Behaviors

arXiv:2606.31557v1 Announce Type: cross Abstract: In the evolving threat landscape, adversaries exploit software vulnerabilities to launch sophisticated attacks, challenging traditional defenses. Alth

DANTE-W: Diffuse Albedo Neural Texturing in the Wild

arXiv:2606.30677v1 Announce Type: cross Abstract: Classical mesh texturing techniques blend captured multi-view images directly, which inevitably suffer from baked-in shading and casted shadows that c

DataEvolver: Self-Evolving Multi-Agent Data Construction for Text-Rich Image Generation

arXiv:2606.31537v1 Announce Type: new Abstract: Text-rich image generation is one of the most challenging settings in image generation, since models must simultaneously produce visually realistic imag

safetyarxiv-cs-cv

DDIAgents: Mechanism-Conditioned Context Flow for Drug-Drug Interaction Prediction

arXiv:2606.31085v1 Announce Type: new Abstract: Drug-drug interaction (DDI) prediction is essential for medication safety, yet it requires reasoning over heterogeneous biomedical evidence whose releva

Deep Reinforcement Learning for Spacecraft Attitude Control During Atmospheric Re-Entry

arXiv:2606.31291v1 Announce Type: new Abstract: Deep reinforcement learning has the potential to solve attitude control problems more adaptively, precisely, and robustly by handling nonlinear dynamics

safetyarxiv-cs-lg

Local Ai

Dense Structural Priors for Sparse Functional Landmark Localization in Surgical Videos

arXiv:2606.31007v1 Announce Type: new Abstract: Vision foundation models such as SAM 3 can provide transferable object-level structure across diverse surgical video conditions, but segmentation output

local-aiarxiv-cs-cv

Design and Implementation of Agentic Orchestrations and Orchestration of Agents

arXiv:2606.31518v1 Announce Type: new Abstract: Agentic Business Process Management has gained momentum recently. The prospect is that the autonomy of AI agents, i.e., predominantly LLM-based agents,

agentsarxiv-cs-ai

Diffusion-based 4D Trajectory Prediction and Distributed Control for UAV Swarms

arXiv:2606.31197v1 Announce Type: new Abstract: Accurate 4D trajectory prediction and closed-loop tracking are essential for Unmanned Aerial Vehicle (UAV) swarms to achieve safe and efficient operatio

agentsarxiv-cs-ro

Direction-Magnitude Decomposition for Low-Rank Matrix Optimization: Faster Convergence and Saddle-to-saddle Dynamics

arXiv:2606.31390v1 Announce Type: cross Abstract: Low-rank matrix optimization is often carried out via the Burer-Monteiro (BM) formulation, but choosing the factorization rank r is delicate and can s

researcharxiv-cs-lg

Disentangling Reasoning Logic to Resolve Explicit Knowledge Conflicts

arXiv:2508.01273v3 Announce Type: replace Abstract: Explicit knowledge conflicts, occurring when retrieved contexts contain contradictory information, pose a fundamental challenge for Large Language M

Distill Once, Adapt Life-Long: Exploring Dataset Distillation for Continual Test-Time Adaptation

arXiv:2606.20196v2 Announce Type: replace Abstract: Continual Test-Time Adaptation (CTTA) aims to maintain model performance under evolving target domains by adapting online without labeled data. Howe

Distilling Temporal Coherence into 2D Networks for Transrectal Ultrasound Prostate Video Segmentation

arXiv:2606.31198v1 Announce Type: cross Abstract: Real-time video segmentation of the prostate in Transrectal Ultrasound (TRUS) is essential for image-guided interventions. While conventional 2D metho

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

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

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

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

model-releasesarxiv-cs-lg

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

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

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

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

model-releasesarxiv-cs-lg

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 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

researcharxiv-cs-lg

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

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

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

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

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,

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

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

researcharxiv-cs-lg

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

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,

Tutorials

FedLAB: Traceable Semantic Codebooks for Federated Multimodal Graph Foundation Learning

arXiv:2606.32016v1 Announce Type: new Abstract: Multimodal graph foundation models aim to learn reusable knowledge from graphs enriched with text, images, attributes, and relational topology, thereby

tutorialsarxiv-cs-lg

Few to Big: Prototype Expansion Network via Diffusion Learner for Point Cloud Few-shot Semantic Segmentation

arXiv:2509.12878v2 Announce Type: replace Abstract: Few-shot 3D point cloud semantic segmentation aims to segment novel categories using a minimal number of annotated support samples. However, prototy

Fine-grained Motion Retrieval via Joint-Angle Motion Images and Token-Patch Late Interaction

arXiv:2603.09930v2 Announce Type: replace Abstract: Text-motion retrieval aims to learn a semantically aligned latent space between natural language descriptions and 3D human motion skeleton sequences

safetyarxiv-cs-cv

Fleet: Few Shots Lead Effective AI-generated Image Detection

arXiv:2606.31082v1 Announce Type: new Abstract: AI-generated image (AIGI) detection is undergoing a critical transition from laboratory benchmarks to open-world adversarial defense. The prevalent para

FlexViT: A Flexible FPGA-based Accelerator for Edge Vision Transformers

arXiv:2606.31938v1 Announce Type: cross Abstract: Deploying Vision Transformer (ViT) models on edge platforms remains challenging due to their high computational demands and the architectural heteroge

Local Ai

FLORA: A deep learning approach to predict forest attributes from heterogeneous LiDAR data

arXiv:2606.32023v1 Announce Type: cross Abstract: Forest attributes are essential for national-scale resource monitoring. Airborne LiDAR metrics are among the auxiliary variables most strongly correla

local-aiarxiv-cs-ai

Tutorials

FMA-Net++: Motion- and Exposure-Aware Joint Video Super-Resolution and Deblurring

arXiv:2512.04390v2 Announce Type: replace-cross Abstract: Joint video super-resolution and deblurring (VSRDB) requires both efficient long-range temporal modeling and robustness to frame-wise exposure

tutorialsarxiv-cs-ai

ForgeDrive: Bidirectional Cross-Conditioning for Unified Visual-Action Generation in Autonomous Driving

arXiv:2606.31226v1 Announce Type: new Abstract: World-model-based autonomous driving endows the model with the ability to understand scene evolution. Yet this promise is undermined by the prevailing i

agentsarxiv-cs-cv

From Grasps to Dexterity: Large-Scale Grasp Pretraining for Dexterous Manipulation

model-releasesarxiv-cs-ro

arXiv:2606.30749v1 Announce Type: new Abstract: Large-scale dexterous grasp datasets encode rich priors over hand-object interaction, but their use has largely been confined to grasp generation and pi