All entries

arXiv:2605.00869v1 Announce Type: cross Abstract: Device-free fall detection utilizing WiFi Channel State Information (CSI) has emerged as a promising, privacy-preserving solution for elderly health m

local-aiarxiv-cs-cv

Robust Fundamental Matrix Estimation from Single Image Motion Blur

DGX agent

arXiv:2605.01552v1 Announce Type: new Abstract: In this paper, we introduce a challenging task: extracting a fundamental matrix from a single motion blurred image. For a camera moving in 3D during exp

applicationsarxiv-cs-cv

5 May 2026

Robust Linear Dueling Bandits with Post-serving Context under Unknown Delays and Adversarial Corruptions

arXiv:2605.01752v1 Announce Type: new Abstract: We study linear dueling bandits in volatile environments characterized by the simultaneous presence of post-serving contexts, delayed feedback, and adve

Robust Parameter Learning for Uncertain MDPs

arXiv:2605.01339v1 Announce Type: new Abstract: Learning-based approaches to verifying unknown Markov decision processes (MDPs) often employ uncertain MDPs. These models use, for example, confidence i

Robust volatility updates for Hierarchical Gaussian Filtering

arXiv:2605.00966v1 Announce Type: new Abstract: Hierarchical Gaussian Filtering (HGF) networks allow for efficient updating of posterior distributions (beliefs) about hidden states of an agent's envir

Robustness of Transformer-Based Fluence Map Prediction Under Clinically Realistic Perturbations

arXiv:2605.00904v1 Announce Type: new Abstract: Learning-based fluence map prediction offers a fast alternative to iterative inverse planning in intensity-modulated radiation therapy (IMRT), but its r

Rule Extraction in Machine Learning: Chat Incremental Pattern Constructor

arXiv:2208.00335v4 Announce Type: replace Abstract: Rule extraction is a central problem in interpretable machine learning because it seeks to convert opaque predictive behavior into human-readable sy

Run an entire company with agents 🔥 It's always awesome to see companies continuing to innovate on AI-native UI/UX, particularly around mul…

Run an entire company with agents 🔥 It's always awesome to see companies continuing to innovate on AI-native UI/UX, particularly around multi-agent coordination, to solve deeply complex tasks beyond w

agentsjerry-liu--x

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

SAGA: A Robust Self-Attention and Goal-Aware Anchor-based Planner for Safe UAV Autonomous Navigation

arXiv:2605.02301v1 Announce Type: new Abstract: Agile unmanned aerial vehicle (UAV) navigation in cluttered environments demands a planning architecture that is both computationally efficient and stru

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

SaLF: Sparse Local Fields for Multi-Sensor Rendering in Real-Time

arXiv:2507.18713v2 Announce Type: replace Abstract: High-fidelity sensor simulation of light-based sensors such as cameras and LiDARs is critical for safe and accurate autonomy testing. Neural radianc

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.

Sample-wise Adaptive Weighting for Transfer Consistency in Adversarial Distillation

arXiv:2512.10275v2 Announce Type: replace Abstract: Adversarial distillation in the standard min-max adversarial training framework aims to transfer adversarial robustness from a large, robust teacher

Sampling-Based Control via Entropy-Regularized Optimal Transport

arXiv:2605.02147v1 Announce Type: new Abstract: Sampling-based model predictive control methods like MPPI and CEM are essential for real-time control of nonlinear robotic systems, particularly where d

researcharxiv-cs-ro

Industry

Samsung reaches a $1T valuation, making it only the second Asian company after TSMC to hit the mark, after its stock rose 4x+ over the past year on the AI boom (Sangmi Cha/Bloomberg)

Sangmi Cha / Bloomberg: Samsung reaches a 1T valuation, making it only the second Asian company after TSMC to hit the mark, after its stock rose 4x+ over the past year on the AI boom — Samsung Electro

industrytechmeme

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 Sequence-to-Sequence Generative Neural Rendering

arXiv:2510.04236v3 Announce Type: replace Abstract: We present Kaleido, a family of generative models designed for photorealistic, unified object- and scene-level neural rendering. Kaleido operates on

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

model-releasesarxiv-cs-cl

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

ScribbleEdit: Synthetic Data for Image Editing with Scribbles and Text

arXiv:2605.01135v1 Announce Type: new Abstract: Recent progress in generative models has significantly advanced image editing capabilities, yet precise and intuitive user control remains difficult. Sp

Applications

Secure AI agents with Amazon Bedrock AgentCore Identity on Amazon ECS

AI agents in production require secure access to external services. Amazon Bedrock AgentCore Identity, available as a standalone service, secures how your AI agents access external services whether th

applicationsaws-ml-blog

Security remediation is an engineering capacity problem. AI has collapsed the time to exploit, but defensive tools haven’t kept up. Today we…

Security remediation is an engineering capacity problem. AI has collapsed the time to exploit, but defensive tools haven’t kept up. Today we’re introducing Devin for Security: a set of workflows for r

agentscognition-ai--x

See you all soon! We've got some fun announcements ahead. I'll also be doing a workshop on 'how we Claude Code' with some workflows I'm exci…

See you all soon! We've got some fun announcements ahead. I'll also be doing a workshop on 'how we Claude Code' with some workflows I'm excited to share. Don't worry if you're not there, everything wi

model-releasesthariq--x

Local Ai

Seedance 2.0 https://links.comfy.org/4d0Lkv2

Seedance 2.0 is an update or feature release for ComfyUI, a node-based UI for Stable Diffusion and other generative AI models. This announcement likely describes new functionality, improvements, or en

local-aicomfyui--x

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

Seeing the Scene Matters: Revealing Forgetting in Video Understanding Models with a Scene-Aware Long-Video Benchmark

arXiv:2603.27259v2 Announce Type: replace Abstract: Long video understanding (LVU) remains a core challenge in multimodal learning. Although recent vision-language models (VLMs) have made notable prog

Segment-Aligned Policy Optimization for Multi-Modal Reasoning

arXiv:2605.01327v1 Announce Type: cross Abstract: Existing reinforcement learning approaches for Large Language Models typically perform policy optimization at the granularity of individual tokens or

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

Applications

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

Selective Prediction from Agreement: A Lipschitz-Consistent Version Space Approach

arXiv:2605.02611v1 Announce Type: new Abstract: We consider selective classification with abstention in the fixed-pool (or transductive) setting, where the unlabeled pool is given beforehand and only

Selector-Guided Autonomous Curriculum for One-Shot Reinforcement Learning from Verifiable Rewards

arXiv:2605.01823v1 Announce Type: new Abstract: Recently, Reinforcement Learning from Verifiable Rewards (RLVR) has been established as a highly effective technique for augmenting the math reasoning s

Self-Normalized Martingales and Uniform Regret Bounds for Linear Regression

arXiv:2605.01628v1 Announce Type: cross Abstract: Self-normalized martingale inequalities lie at the heart of confidence ellipsoids for online least squares and, more broadly, many bandit and reinforc

Self-Supervised Learning for Multimodal Non-Rigid 3D Shape Matching

arXiv:2303.10971v2 Announce Type: replace Abstract: The matching of 3D shapes has been extensively studied for shapes represented as surface meshes, as well as for shapes represented as point clouds.

Self-Supervised Spatial And Zero-Shot Angular Super-Resolution by Spatial-Angular Implicit Representation For Rotating-View SNR-Efficient Diffusion MRI

arXiv:2605.02575v1 Announce Type: new Abstract: Rotating-view thick-slice acquisition is highly SNR-efficient for mesoscale diffusion MRI (dMRI) but requires numerous rotating views to satisfy Nyquist

Semantic-Contact Fields for Category-Level Generalizable Tactile Tool Manipulation

arXiv:2602.13833v2 Announce Type: replace Abstract: Generalizing tool manipulation requires both semantic planning and precise physical control. Modern generalist robot policies, such as Vision-Langua

Local Ai

Semantic Context-aware mOdality fUsion Transformer (SCOUT): A Context-Aware Multimodal Transformer for Concept-Grounded Pathology Report Generation

arXiv:2605.01144v1 Announce Type: new Abstract: Whole-slide images (WSIs) present a fundamental challenge for computational pathology due to their extreme resolution, multi-scale heterogeneity, and th

local-aiarxiv-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.

SemEval-2026 Task 7: Everyday Knowledge Across Diverse Languages and Cultures

model-releasesarxiv-cs-cl

arXiv:2605.02601v1 Announce Type: new Abstract: We present our shared task on evaluating the adaptability of LLMs and NLP systems across multiple languages and cultures. The task data consist of an ex

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

Semia: Auditing Agent Skills via Constraint-Guided Representation Synthesis

arXiv:2605.00314v1 Announce Type: cross Abstract: An agent skill is a configuration package that equips an LLM-driven agent with a concrete capability, such as reading email, executing shell commands,

agentsarxiv-cs-ai

Sentiment Analysis of Mobile Legends App Reviews Using Machine Learning and LSTM-Based Deep Learning Models

arXiv:2605.01317v1 Announce Type: new Abstract: This paper compares Machine Learning and LSTM-based Deep Learning methods for sentiment analysis of Mobile Legends app reviews. Using a dataset of 10,00

researcharxiv-cs-cl

Sentinel-VLA: A Metacognitive VLA Model with Active Status Monitoring for Dynamic Reasoning and Error Recovery

model-releasesarxiv-cs-ro

arXiv:2605.01191v1 Announce Type: new Abstract: Vision-language-action (VLA) models have advanced the field of embodied manipulation by harnessing broad world knowledge and strong generalization. Howe

Sentra-Guard: A Real-Time Multilingual Defense Against Adversarial LLM Prompts

arXiv:2510.22628v2 Announce Type: replace-cross Abstract: This paper presents a real-time modular defense system named Sentra-Guard. The system detects and mitigates jailbreak and prompt injection att

safetyarxiv-cs-ai

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

Sequential Learning and Catastrophic Forgetting in Differentiable Resistor Networks

arXiv:2605.01383v1 Announce Type: new Abstract: Differentiable physical networks provide a simple setting in which learning can be studied through the interaction between trainable parameters and phys