Search: “framework”

Parking Assistance for Trailer-Truck Transport Vehicles Using Sensor Fusion and Motion Planning

arXiv:2605.02716v1 Announce Type: new Abstract: Autonomous driving technology has rapidly evolved over the past decade, offering significant improvements in transportation efficiency, safety, and cost

safetyarxiv-cs-ro

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Local Ai

Personalized Federated Learning for Gradient Alignment

DGX agent

arXiv:2605.02143v1 Announce Type: new Abstract: Personalized federated learning (pFL) aims to adapt models to client specific data distributions, yet it often fails to reliably preserve personalized i

local-aiarxiv-cs-lg

5 May 2026

Physiology-Aware Masked Cross-Modal Reconstruction for Biosignal Representation Learning

arXiv:2605.00973v1 Announce Type: new Abstract: Biosignals acquired from different locations on the body often provide temporally ordered views of the same underlying physiological process. However, m

Pi-Change: A Prior-Informed Multiple Change Point Detection Algorithm

arXiv:2605.01003v1 Announce Type: cross Abstract: Statistical change point (CP) detection methods typically rely on likelihood-based inference and ignore contextual information about plausible CP loca

Pixel-to-4D: Camera-Controlled Image-to-Video Generation with Dynamic 3D Gaussians

arXiv:2601.00678v2 Announce Type: replace Abstract: Humans excel at forecasting the future dynamics of a scene given just a single image. Video generation models that can mimic this ability are an ess

applicationsarxiv-cs-cv

PointCSP: Cross-Sample Semantic Propagation and Stability Preservation in Self-Supervised Point Cloud Learning

arXiv:2605.01759v1 Announce Type: new Abstract: Scene-level point cloud self-supervised learning (PC-SSL) has demonstrated potential in enhancing the generalization capability of 3D vision models. Des

PPO guided Agentic Pipeline for Adaptive Prompt Selection and Test Case Generation

arXiv:2605.00942v1 Announce Type: cross Abstract: Developing effective test cases capable of thoroughly exercising large-scale software systems is inherently difficult, especially if such systems have

Pretraining A Large Language Model using Distributed GPUs: A Memory-Efficient Decentralized Paradigm

arXiv:2602.11543v2 Announce Type: replace Abstract: Pretraining large language models (LLMs) typically requires centralized clusters with thousands of high-memory GPUs (e.g., H100/A100). Recent decent

PRIME: Protein Representation via Physics-Informed Multiscale Equivariant Hierarchies

arXiv:2605.01625v1 Announce Type: new Abstract: Proteins are inherently multiscale physical systems whose functional properties emerge from coordinated structural organization across multiple spatial

Profile-Specific 3DMM Regression from a Single Lateral Face Image

arXiv:2605.01746v1 Announce Type: new Abstract: Single-image 3D face reconstruction is a core problem in computer vision, with important clinical applications such as cephalometric landmark analysis i

Projection-Free Transformers via Gaussian Kernel Attention

arXiv:2605.02144v1 Announce Type: new Abstract: Self-attention in Transformers is typically implemented as softmax(QK^op/sqrt{d})V, where Q=XW_Q, K=XW_K, and V=XW_V are learned linear projections of t

Protein-Conditioned Multi-Objective Reinforcement Learning for Full-Length mRNA Design

arXiv:2605.01513v1 Announce Type: new Abstract: Designing therapeutic messenger RNA (mRNA) requires creating full-length transcripts that carefully balance stability, translation efficiency, and immun

safetyarxiv-cs-lg

ProtoFair: Fair Self-Supervised Contrastive Learning via Pseudo-Counterfactual Pairs

arXiv:2605.01971v1 Announce Type: new Abstract: Self-supervised learning methods learn high-quality visual representations, yet recent studies show that these representations often capture demographic

Pruning Federated Models through Loss Landscape Analysis and Client Agreement Scoring

arXiv:2405.10271v4 Announce Type: replace Abstract: The practical deployment of Federated Learning (FL) on resource-constrained devices is fundamentally limited by the high cost of training large mode

Psychologically Potent, Computationally Invisible: LLMs Generate Social-Comparison Triggers They Fail to Detect

arXiv:2605.01017v1 Announce Type: new Abstract: We introduce Xiaohongshu Social Comparison Reader Elicitation (XHS-SCoRE), a reader-grounded benchmark for detecting if a text-only Xiaohongshu (RedNote

PuppetAI: A Customizable Platform for Designing Tactile-Rich Affective Robot Interaction

arXiv:2602.04787v2 Announce Type: replace-cross Abstract: We introduce PuppetAI, a modular soft robot interaction platform. This platform offers a scalable cable-driven actuation system and a customiz

applicationsarxiv-cs-ro

Hardware

Quant VideoGen: Auto-Regressive Long Video Generation via 2-Bit KV-Cache Quantization

arXiv:2602.02958v4 Announce Type: replace Abstract: Despite rapid progress in autoregressive video diffusion, an emerging system algorithm bottleneck limits both deployability and generation capabilit

hardwarearxiv-cs-lg

Quantifying Multimodal Capabilities: Formal Generalization Guarantees in Pairwise Metric Learning

arXiv:2605.01424v1 Announce Type: new Abstract: Multimodal learning leverages the integration of diverse data modalities to enhance performance in complex tasks. Yet, it frequently encounters incomple

applicationsarxiv-cs-lg

RA-CMF: Region-Adaptive Conditional MeanFlow for CT Image Reconstruction

arXiv:2605.00901v1 Announce Type: new Abstract: The use of CT imaging is important for screening, diagnosis, therapy planning, and prognosis of lung cancers. Unfortunately, due to differences in imagi

Random-Effects Algorithm for Random Objects in Metric Spaces

arXiv:2605.02693v1 Announce Type: cross Abstract: Across many scientific disciplines, multiple observations are collected from the same experimental units, and in modern datasets these observations of

Rate-optimal Design for Anytime Best Arm Identification

arXiv:2510.23199v3 Announce Type: replace-cross Abstract: We consider the best arm identification problem, where the goal is to identify the arm with the highest mean reward from a set of K arms under

applicationsarxiv-cs-lg

Recall to Predict: Grounding Motion Forecasting in Interpretable Motion Bank

arXiv:2605.01393v1 Announce Type: new Abstract: Motion forecasting often requires trading interpretability for predictive accuracy. Standard anchor-based architectures rely on opaque latent queries th

RECAP: Transparent Inference-Time Emotion Alignment for Medical Dialogue Systems

arXiv:2509.10746v3 Announce Type: replace Abstract: Large language models in healthcare often produce emotionally flat or opaque responses, failing to provide the transparent reasoning required for cl

safetyarxiv-cs-cl

RefusalGuard: Geometry-Preserving Fine-Tuning for Safety in LLMs

arXiv:2605.01913v1 Announce Type: cross Abstract: Fine-tuning safety-aligned language models for downstream tasks often leads to substantial degradation of refusal behavior, making models vulnerable t

ReMedi: Reasoner for Medical Clinical Prediction

arXiv:2605.01474v1 Announce Type: new Abstract: Predicting future clinical outcomes from electronic health records (EHR) remains challenging due to the complexity and heterogeneity of patient data. LL

applicationsarxiv-cs-cl

Remote Action Generation: Remote Control with Minimal Communication

arXiv:2605.01833v1 Announce Type: cross Abstract: We address the challenge of remote control where one or more actors, lacking direct reward access, are steered by a controller over a communication-co

safetyarxiv-cs-lg

Representation learning from OCT images

arXiv:2605.02589v1 Announce Type: new Abstract: Optical Coherence Tomography (OCT) has become one of the most used imaging modality in ophthalmology. It provides high-resolution, non-invasive visualiz

Research on Vision-Language Question Answering Models for Industrial Robots

arXiv:2605.01483v1 Announce Type: new Abstract: A hierarchical cross-modal fusion model is proposed for vision-language question answering (VLQA) in industrial robotics, targeting the challenges of se

Rethink MAE with Linear Time-Invariant Dynamics

arXiv:2605.00915v1 Announce Type: new Abstract: Standard representation probing for visual models relies on mathematically permutation-invariant operations like Global Average Pooling (GAP) or CLS tok

Tutorials

Rethinking the Need for Source Models: Source-Free Domain Adaptation from Scratch Guided by a Vision-Language Model

arXiv:2605.02604v1 Announce Type: new Abstract: Source-Free Domain Adaptation (SFDA) adapts source models to target domains without accessing source data, addressing privacy and transmission issues. H

tutorialsarxiv-cs-cv

Robotic Affection -- Opportunities of AI-based haptic interactions to improve social robotic touch through a multi-deep-learning approach

arXiv:2605.02538v1 Announce Type: cross Abstract: Despite the advancement in robotic grasping and dexterity through haptic information, affective social touch, such as handshaking or reassuring stroki

researcharxiv-cs-ro

Agents

S^3-R1: Learning to Retrieve and Answer Step-by-Step with Synthetic Data

arXiv:2605.01248v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training has enabled newer capabilities in models, such as agentic tool-use for search. However, these models struggle

agentsarxiv-cs-lg

Safe Planning in Interactive Environments via Iterative Policy Updates and Adversarially Robust Conformal Prediction

arXiv:2511.10586v2 Announce Type: replace-cross Abstract: Safe planning of an autonomous agent in interactive environments -- such as the control of a self-driving vehicle among pedestrians -- poses a

safetyarxiv-cs-ro

SAIL: Structure-Aware Interpretable Learning for Anatomy-Aligned Post-hoc Explanations in OCT

arXiv:2605.02707v1 Announce Type: new Abstract: Optical coherence tomography (OCT), a commonly used retinal imaging modality, plays a central role in retinal disease diagnosis by providing high-resolu

SAMamba3D: adapting Segment Anything for generalizable 3D segmentation of multiphase pore-scale images

arXiv:2605.00916v1 Announce Type: new Abstract: Reliable segmentation of multiphase pore-scale X-ray images of rocks is necessary to quantify fluid saturation, connectivity, and interfacial geometry.

SCALE-LoRA: Auditing Post-Retrieval LoRA Composition with Residual Merging and View Reliability

arXiv:2605.01429v1 Announce Type: cross Abstract: Libraries of Low-Rank Adaptation (LoRA) adapters are becoming a practical by-product of parameter-efficient adaptation. Once such adapters accumulate,

Scaling Vision Transformers for Functional MRI with Flat Maps

arXiv:2510.13768v2 Announce Type: replace Abstract: We study the problem of training self-supervised foundation models for functional MRI. Our main contributions are: (1) we introduce a new model fami

SCARV: Structure-Constrained Aggregation for Stable Sample Ranking in Redundant NLP Datasets

arXiv:2605.00944v1 Announce Type: cross Abstract: Sample-level rankings are increasingly used in data-centric NLP for analysis, filtering, debugging, and curation, yet existing pipelines typically sco

researcharxiv-cs-cl

SciResearcher: Scaling Deep Research Agents for Frontier Scientific Reasoning

arXiv:2605.01489v1 Announce Type: cross Abstract: Frontier scientific reasoning is rapidly emerging as a key foundation for advancing AI agents in automated scientific discovery. Deep research agents

Seeing Realism from Simulation: Efficient Video Transfer for Vision-Language-Action Data Augmentation

arXiv:2605.02757v1 Announce Type: new Abstract: Vision-language-action (VLA) models typically rely on large-scale real-world videos, whereas simulated data, despite being inexpensive and highly parall

Selective Attention-Based Network for Robust Infrared Small Target Detection

arXiv:2605.00886v1 Announce Type: new Abstract: Infrared small target detection (IRSTD) plays a pivotal role in a broad spectrum of mission-critical applications, including maritime surveillance, mili

Selective Correlation Based Knowledge Distillation for Ground Reaction Force Estimation

arXiv:2605.00888v1 Announce Type: new Abstract: Wearable sensor-based human gait analysis holds great promise in healthcare, rehabilitation, clinical diagnosis and monitoring, and sports activities. S

applicationsarxiv-cs-cv

Semantic Risk-Aware Heuristic Planning for Robotic Navigation in Dynamic Environments: An LLM-Inspired Approach

arXiv:2605.02862v1 Announce Type: new Abstract: The integration of Large Language Model (LLM) reasoning principles into classical robot path planning represents a rapidly emerging research direction.

safetyarxiv-cs-ro

Semi-Supervised Treatment Effect Estimation with Unlabeled Covariates for Prediction-Powered Causal Inference

arXiv:2511.08303v2 Announce Type: replace-cross Abstract: This study investigates treatment effect estimation in the semi-supervised setting, also can be interpreted as prediction-powered inference. I

Separation Assurance between Heterogeneous Fleets of Small Unmanned Aerial Systems via Multi-Agent Reinforcement Learning

arXiv:2605.01041v1 Announce Type: cross Abstract: In the envisioned future dense urban airspace, multiple companies will operate heterogeneous fleets of small unmanned aerial systems (sUASs), where ea

safetyarxiv-cs-lg

SIAM: Head and Brain MRI Segmentation from Few High-Quality Templates via Synthetic Training

arXiv:2605.02737v1 Announce Type: new Abstract: Synthetic training has recently advanced brain MRI segmentation by enabling contrast-agnostic models trained entirely on generated data. However, most e

SignVerse-2M: A Two-Million-Clip Pose-Native Universe of 25+ Sign Languages

arXiv:2605.01720v1 Announce Type: cross Abstract: Existing large-scale sign language resources typically provide supervision only at the level of raw video-text alignment and are often produced in lab

safetyarxiv-cs-cl

Agents

Sim-to-Real Transfer and Robustness Evaluation of Reinforcement Learning Control with Integrated Perception on an ASV for Floating Waste Capture

arXiv:2605.02529v1 Announce Type: new Abstract: Autonomous surface vessels for floating-waste removal operate under varying hydrodynamics, external disturbances, and challenging water-surface percepti

agentsarxiv-cs-ro