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SSL4RL: Revisiting Self-supervised Learning as Intrinsic Reward for Visual-Language Reasoning

arXiv:2510.16416v4 Announce Type: replace-cross Abstract: Vision-language models (VLMs) have shown remarkable abilities by integrating large language models with visual inputs. However, they often fai

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Research

SSTL: Self-Sensing Tendon Loop for Hysteresis Modeling and Compensation in Tendon-Sheath Mechanisms

DGX agent

arXiv:2605.16870v1 Announce Type: new Abstract: Flexible endoscopic robots enable minimally invasive access through natural orifices, but their control accuracy is limited by configuration-dependent h

researcharxiv-cs-ro

19 May 2026

ST-BCP: Tightening Coverage Bound for Backward Conformal Prediction via Non-Conformity Score Transformation

arXiv:2602.01733v2 Announce Type: replace-cross Abstract: Conformal Prediction (CP) provides a statistical framework for uncertainty quantification that constructs prediction sets with coverage guaran

Stabilizing, Scaling & Enhancing MeanFlow for Large-scale Diffusion Distillation

model-releasesarxiv-cs-cv

arXiv:2605.17834v1 Announce Type: new Abstract: Diffusion models exhibit remarkable generative capability, but their high latency limits practical deployment. Many studies have attempted to reduce sam

Stabilizing Temporal Inference Dynamics for Online Surgical Phase Recognition

arXiv:2605.16387v1 Announce Type: cross Abstract: Online Surgical Phase Recognition (SPR) models can reach high frame-wise accuracy, yet their predictions often lack temporal stability, fragmenting wo

researcharxiv-cs-ai

Stable and Near-Reversible Diffusion ODE Solvers for Image Editing

arXiv:2605.16399v1 Announce Type: new Abstract: The inversion of diffusion models plays a central role in image editing. Algebraically reversible ODE solvers provide an appealing approach to diffusion

safetyarxiv-cs-cv

Hardware

Stable Audio 3

arXiv:2605.17991v1 Announce Type: cross Abstract: Stable Audio 3 is a family of fast latent diffusion models (small, medium, large) for variable-length audio generation and editing. Since our models c

hardwarearxiv-cs-ai

Stable Routing for Mixture-of-Experts in Class-Incremental Learning

arXiv:2605.17571v1 Announce Type: new Abstract: Class-incremental learning (CIL) requires models to learn new classes sequentially while preserving prior knowledge. Recently, approaches that combine p

safetyarxiv-cs-cv

StableHand: Quality-Aware Flow Matching for World-Space Dual-Hand Motion Estimation from Egocentric Video

arXiv:2605.18553v1 Announce Type: cross Abstract: Recovering world space 4D motion of two interacting hands from egocentric video is a fundamental capability for supervising robot policy learning, whe

StableVLA: Towards Robust Vision-Language-Action Models without Extra Data

model-releasesarxiv-cs-cv

arXiv:2605.18287v1 Announce Type: new Abstract: It is infeasible to encompass all possible disturbances within the training dataset. This raises a critical question regarding the robustness of Vision-

Tutorials

StAD: Stein Amortized Divergence for Fast Likelihoods with Diffusion and Flow

arXiv:2605.16486v1 Announce Type: cross Abstract: Diffusion and flow-based models are ubiquitously used for generative modelling and density estimation. They admit a deterministic probability flow ord

tutorialsarxiv-cs-lg

STAG-CN: Spatio-Temporal Apiary Graph Convolutional Network for Disease Onset Prediction in Beehive Sensor Networks

arXiv:2603.14462v2 Announce Type: replace-cross Abstract: Honey bee colony losses threaten global pollination services, yet current monitoring systems treat each hive as an isolated unit, ignoring the

researcharxiv-cs-ai

Industry

Standard Chartered plans to cut nearly 8,000 back-office positions by 2030, a 15%+ reduction in support functions in hubs like Bengaluru, amid growing AI usage (Arjun Neil Alim/Financial Times)

Arjun Neil Alim / Financial Times: Standard Chartered plans to cut nearly 8,000 back-office positions by 2030, a 15%+ reduction in support functions in hubs like Bengaluru, amid growing AI usage — Bil

industrytechmeme

Industry

Starship Human for scale

This post likely shows a photograph of SpaceX's Starship rocket with a human included in the frame to provide visual scale, demonstrating the massive size of the vehicle relative to a person. The imag

industryelon-musk--x

Starting today, use your Grok or X Premium subscription in @openclaw. Chat with your agent, generate images and videos, or search for X post…

Grok and X Premium subscribers can now access their subscriptions within OpenClaw, enabling them to chat with AI agents, generate images and videos, and search X posts directly through the platform. T

agentselon-musk--x

Tutorials

Starve to Perceive: Taming Lazy Perception in VLMs with Constrained Visual Bandwidth

arXiv:2605.18603v1 Announce Type: new Abstract: Vision-Language Models (VLMs) deployed as situated agents in high-resolution visual environments require active perception -- the ability to dynamically

tutorialsarxiv-cs-cv

State-Conditional Adversarial Learning: An Off-Policy Visual Domain Transfer Method for End-to-End Imitation Learning

arXiv:2512.05335v3 Announce Type: replace Abstract: We study visual domain transfer for end-to-end imitation learning in a realistic and challenging setting where target-domain data are strictly off-p

safetyarxiv-cs-ro

State Contamination in Memory-Augmented LLM Agents

arXiv:2605.16746v1 Announce Type: new Abstract: LLM agents increasingly rely on persistent state, including transcripts, summaries, retrieved context, and memory buffers, to support long-horizon inter

State-of-the-Art Claims Require State-of-the-Art Evidence

arXiv:2605.17273v1 Announce Type: cross Abstract: State-of-the-Art (SOTA) claims pervade Artificial Intelligence (AI) and Machine Learning (ML) research. These claims rest on benchmark evaluations, wh

Statistical Hand Shape Modeling from Clinical CT Scans Using Deep Learning and Implicit Skinning

arXiv:2605.16980v1 Announce Type: new Abstract: Accurate segmentation and statistical shape modeling of hand anatomy have significant implications for medical diagnostics, ergonomics, and biomechanics

researcharxiv-cs-cv

Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning

arXiv:2605.18656v1 Announce Type: cross Abstract: Federated Learning is a leading framework for training ML and AI models collaboratively across numerous user devices or databases. We study the trade-

Statistical Unlearning of Distributions: A Hypothesis Testing Approach

arXiv:2605.16645v1 Announce Type: cross Abstract: Machine learning systems increasingly face requirements to forget not only individual data points, but entire domains of information, such as toxic la

StatQAT: Statistical Quantizer Optimization for Deep Networks

arXiv:2605.17745v1 Announce Type: cross Abstract: Quantization is essential for reducing the computational cost and memory usage of deep neural networks, enabling efficient inference on low-precision

SteadyDancer: Harmonized and Coherent Human Image Animation with First-Frame Preservation

model-releasesarxiv-cs-cv

arXiv:2511.19320v2 Announce Type: replace Abstract: Preserving first-frame identity while ensuring precise motion control is a fundamental challenge in human image animation. The Image-to-Motion Bindi

Stein Diffusion Guidance: Training-Free Posterior Correction for Sampling Beyond High-Density Regions

arXiv:2507.05482v3 Announce Type: replace Abstract: Training-free diffusion guidance offers a flexible framework for leveraging off-the-shelf classifiers without additional training. Yet, current appr

Step-wise Rubric Rewards for LLM Reasoning

arXiv:2605.17291v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is widely used to improve reasoning in large language models, but rewards only final-answer correc

Stochastic Penalty-Barrier Methods for Constrained Machine Learning

arXiv:2605.18618v1 Announce Type: cross Abstract: Constrained machine learning enables fairness-aware training, physics-informed neural networks, and integration of symbolic domain knowledge into stat

Stochastic Regret Guarantees for Online Zeroth- and First-Order Bilevel Optimization

arXiv:2511.01126v2 Announce Type: replace Abstract: Online bilevel optimization (OBO) is a powerful framework for machine learning problems where both outer and inner objectives evolve over time, requ

Stop bolting AI onto brownfield and start treating legacy as a feeder, not a foundation, says Dell CTO

Fully autonomous AI has crossed the threshold from concept to commercial reality, forcing enterprises to rethink the very foundation on which they run their businesses. The shift is arriving faster th

agentssiliconangle

Stop rogue AI: How Unity Catalog secures your agent actions

Unity Catalog is a Databricks governance solution that helps secure AI agent actions by managing access controls and permissions across agent operations. It prevents unauthorized or 'rogue' AI behavio

agentsdatabricks

Stop When Reasoning Converges: Semantic-Preserving Early Exit for Reasoning Models

arXiv:2605.17672v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) achieve strong performance by generating long chains of thought (CoT), but often overthink, continuing to reason after a s

safetyarxiv-cs-cl

Strategic Over-Parameterization for Generalizable Low-Rank Adaptation

arXiv:2605.16470v1 Announce Type: cross Abstract: Adapting large language models (LLMs) to downstream tasks via full fine-tuning is increasingly impractical due to its computational and memory demands

Hardware

StreamingEffect: Real-Time Human-Centric Video Effect Generation

arXiv:2605.17019v1 Announce Type: new Abstract: Streaming video effect generation is highly desirable for live human-centric applications such as e-commerce streaming, entertainment, and vlogging, yet

hardwarearxiv-cs-cv

StreamingTalker: Audio-driven 3D Facial Animation with Autoregressive Diffusion Model

arXiv:2511.14223v3 Announce Type: replace Abstract: This paper focuses on the task of speech-driven 3D facial animation, which aims to generate realistic and synchronized facial motions driven by spee

researcharxiv-cs-cv

StreamPro: From Reactive Perception to Proactive Decision-Making in Streaming Video

arXiv:2605.16381v1 Announce Type: cross Abstract: Proactive streaming video understanding requires models to continuously process video streams and decide when to respond, rather than merely what to r

Stress-Testing Neural Network Verifiers with Provably Robust Instances

arXiv:2605.17153v1 Announce Type: new Abstract: Neural network verifiers aim to provide formal guarantees on model behavior, but existing verification benchmarks are fundamentally limited by their lac

Stretch-ICP: A Continuous-Trajectory Registration and Deskewing Algorithm in Scenarios of Aggressive Motions

arXiv:2605.17264v1 Announce Type: new Abstract: Robust robotic autonomy remains challenging in complex environments, where loss of stability on uneven or slippery terrain can induce extreme accelerati

researcharxiv-cs-ro

STRIDE: A Self-Reflective Agent Framework for Reliable Automatic Equation Discovery

arXiv:2605.17790v1 Announce Type: new Abstract: LLM-based equation discovery offers a promising route to recovering symbolic laws from data, but many systems still rely on generation-centered loops th

agentsarxiv-cs-ai

Applications

STRIDE-AI: A Threat Modeling Framework for Generative AI Security Assessment

arXiv:2605.17163v1 Announce Type: cross Abstract: Traditional cybersecurity methodologies target deterministic systems and fail to address the probabilistic nature of AI, leaving systems vulnerable to

applicationsarxiv-cs-ai

StrLoRA: Towards Streaming Continual Visual Instruction Tuning for MLLMs

arXiv:2605.16353v1 Announce Type: cross Abstract: Continual Visual Instruction Tuning (CVIT) enables Multimodal Large Language Models to incrementally acquire new abilities. However, existing CVIT met

Stroke of Surprise: Progressive Semantic Illusions in Vector Sketching

arXiv:2602.12280v2 Announce Type: replace Abstract: Visual illusions traditionally rely on spatial manipulations such as multi-view consistency. In this work, we introduce Progressive Semantic Illusio

researcharxiv-cs-cv

StructLens: A Structural Lens for Language Models via Maximum Spanning Trees

arXiv:2603.03328v2 Announce Type: replace-cross Abstract: Language exhibits inherent structures, a property that explains both language acquisition and language change. Given this characteristic, we e

researcharxiv-cs-ai

Structure-Aware Masking for Protein Representation Learning

arXiv:2605.16581v1 Announce Type: new Abstract: Masked language modeling (MLM) is the standard objective for training protein language models, typically implemented by randomly masking individual resi

safetyarxiv-cs-lg

Structured Labeling Enables Faster Vision-Language Models for End-to-End Autonomous Driving

arXiv:2506.05442v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) offer a promising approach to end-to-end autonomous driving due to their human-like reasoning capabilities. Howe

Structured Neural Marked Point Processes for Interpretable Event Interaction Modeling

model-releasesarxiv-cs-lg

arXiv:2605.17568v1 Announce Type: new Abstract: Multi-class event streams arise in numerous real-world applications, where uncovering structured, interpretable inter-event relationships, together with

STT-Arena: A More Realistic Environment for Tool-Using with Spatio-Temporal Dynamics

arXiv:2605.18548v1 Announce Type: cross Abstract: Large language models (LLMs) deployed in real-world agentic applications must be capable of replanning and adapting when mid-task disruptions invalida

StyleText: A Large-Scale Dataset and Benchmark for Stylized Scene Text Inpainting

arXiv:2605.17309v1 Announce Type: cross Abstract: We present StyleText, a large-scale dataset and benchmark for localized scene-text inpainting with style preservation. StyleText contains 28,518 image

Subject-Specific Analysis of Self-Initiated Attention Shifts from EEG with Controlled Internal and External Attention Conditions

arXiv:2605.18251v1 Announce Type: cross Abstract: Self-initiated attention shifts play a critical role in voluntary behavior but are difficult to study due to the absence of explicit temporal markers.