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Skill Reuse as Compression in Agentic RL

arXiv:2605.31509v1 Announce Type: cross Abstract: Large language model agents trained with reinforcement learning (RL) often learn brittle, task-specific shortcuts. We hypothesize that agents generali

Skin Lesion Classification Based on ResNet-50 Enhanced With Adaptive Spatial Feature Fusion

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DGX agent

arXiv:2510.03876v2 Announce Type: replace Abstract: Skin cancer classification is challenging due to high inter-class similarity, intra-class variability, and artifacts in dermoscopic images. To addre

researcharxiv-cs-cv

1 Jun 2026

SLAP: The Semantic Least Action Principle for Variational Video-Language Modeling

arXiv:2605.30750v1 Announce Type: new Abstract: In the era of Large Video-Language Models (LVLMs), the computational necessity of sparse frame sampling creates a fundamental ``temporal gap'', renderin

SLAT: Segment-Level Adaptive Trimming for Efficient CoT Reasoning

arXiv:2605.30832v1 Announce Type: new Abstract: Recent advances in Large Reasoning Models have significantly improved chain-of-thought (CoT) capabilities via reinforcement learning (RL). However, gene

researcharxiv-cs-ai

SlotMemory: Object-Centric KV Memory for Streaming Long-Video Generation

arXiv:2605.31033v1 Announce Type: new Abstract: Streaming video generation models typically rely on temporal-centric memory, which organizes historical context as raw frames, chunk segments, or unclus

Smaller and Faster 3DGS via Post-Training Dictionary Learning

model-releasesarxiv-cs-lg

arXiv:2605.30396v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) is a promising neural scene representation for real-time rendering, but trained models often suffer from large memory foo

Smaller Models are Natural Explorers for Policy-Level Diversity in GRPO

arXiv:2605.30789v1 Announce Type: cross Abstract: We identify a new dimension for enhancing rollout diversity in Group Relative Policy Optimization (GRPO) for LLMs. While GRPO relies on diverse rollou

safetyarxiv-cs-ai

SMART: SMPLest-X Mesh Adaptation and RAFT Tracking for Soccer Pose Estimation

arXiv:2605.31551v1 Announce Type: new Abstract: We present our approach to the FIFA Skeletal Tracking Challenge 2026, which requires estimating 3D world-space poses of soccer players from broadcast vi

Social Reasoning in Machines: Investigating Collective Truth-Seeking Dynamics in Large Language Model Debate

arXiv:2605.30391v1 Announce Type: cross Abstract: Human reasoning has long been theorised to operate socially, not through isolated individual cognition, but through collective adversarial discourse,

Social welfare optimisation under institutional reward and punishment

arXiv:2605.31330v1 Announce Type: cross Abstract: Institutional incentives are widely used to promote cooperation among autonomous, self-regarding agents, from human societies to multi-agent and AI sy

SOCO: Benchmarking Semantic Object Correspondence in Vision Foundation Models

model-releasesarxiv-cs-cv

arXiv:2605.31597v1 Announce Type: new Abstract: Measuring structured object understanding in vision foundation models remains challenging due to inconsistent evaluation protocols and limited part-leve

Softly Constrained Denoisers for Diffusion Models Applied to Partial Differential Equations

arXiv:2512.14980v4 Announce Type: replace Abstract: Diffusion models have become a powerful generative prior for solutions of partial differential equations (PDEs). Existing approaches enforce physica

Softsign: Smooth Sign in Your Optimizer For Better Parameter Heterogeneity Handling

model-releasesarxiv-cs-lg

arXiv:2605.31371v1 Announce Type: new Abstract: Sign-based and LMO-inspired optimizers have recently attracted substantial attention in deep learning due to their strong performance and low memory foo

Sophrosyne: Agentic Exploration of Relational Data Systems Needs Moderation

arXiv:2605.30862v1 Announce Type: cross Abstract: Text2SQL agents powered by LLMs translate natural language intent into SQL by exploring the data system through tool calls before formulating the quer

SpatialAct: Probing Spatial Reasoning-to-Action Capabilities of VLM Agents in 3D Scenes

arXiv:2605.31148v1 Announce Type: cross Abstract: Humans can effortlessly perceive spatial layouts, form cognitive representations, reason about spatial relations, and translate such reasoning into ac

Applications

Spatio-temporal stochastic graph-based learning for infectious disease forecasting

arXiv:2605.30662v1 Announce Type: new Abstract: Spatio-temporal graph-based models have typically been used to forecast new cases of infectious diseases such as COVID-19 and chickenpox outbreaks. Howe

applicationsarxiv-cs-lg

SpecDB: LLM-Generated Customized Databases via Feature-Oriented Decomposition

arXiv:2605.31097v1 Announce Type: cross Abstract: Mainstream relational databases ship a uniform feature set across deployments, although individual workloads exercise only a fraction of the available

SPECTRA: Synthetic IR Test Collections with Relevance Oracles and Controlled Distractor Diagnostics

arXiv:2605.31575v1 Announce Type: cross Abstract: Scalable information retrieval testing needs corpora that are large enough to stress index construction, ranking latency, query routing, and evaluatio

researcharxiv-cs-ai

Spectral Anatomy of Quantum Gaussian Process Kernels

arXiv:2605.30952v1 Announce Type: new Abstract: Two recent results have reshaped quantum Gaussian processes (QGPs). On the one hand, itet{lowe2025assessing} rule out the exponential speedups claimed b

researcharxiv-cs-lg

Spectral Collapse Drives Loss of Plasticity in Deep Continual Learning

arXiv:2509.22335v3 Announce Type: replace-cross Abstract: We investigate why deep neural networks suffer from loss of plasticity in continual learning, and thus fail to learn new tasks without reiniti

tutorialsarxiv-cs-ai

Spectral Reach: Understanding Neural Scaling as Progress into the Spectral Tail

arXiv:2605.31244v1 Announce Type: new Abstract: Neural scaling laws describe predictable power-law relationships between model size, dataset size, compute, and performance. While these laws guide the

tutorialsarxiv-cs-lg

Speculative Decoding Across Languages

arXiv:2605.30580v1 Announce Type: new Abstract: Speculative decoding has become a crucial component of large language model (LLM) inference, enabling faster generation by drafting multiple tokens and

researcharxiv-cs-cl

Speculative Pipeline Decoding: Higher-Accruacy and Zero-Bubble Speculation via Pipeline Parallelism

arXiv:2605.30852v1 Announce Type: new Abstract: Speculative Decoding (SD) accelerates low-concurrency LLM inference by employing a draft-then-verify paradigm. However, mainstream methods typically rel

researcharxiv-cs-cl

SPM-Bench: Benchmarking Large Language Models for Scanning Probe Microscopy

arXiv:2602.22971v2 Announce Type: replace Abstract: As LLMs achieved breakthroughs in general reasoning, their proficiency in specialized scientific domains reveals pronounced gaps in existing benchma

SpongeBob: Sync-Aware Harmonious Audio-Visual Generative Editing

arXiv:2605.25193v2 Announce Type: replace Abstract: Visual and acoustic events in the physical world are inherently coupled, yet existing video editing methods typically adopt decoupled pipelines, lac

safetyarxiv-cs-cv

SSR: Scaling Surefooted and Symmetric Humanoid Traversal to the Open World

arXiv:2605.30770v1 Announce Type: new Abstract: Extending humanoid traversal to the open world is key to practical deployment in human environments, but remains challenging. The robot must use vision

tutorialsarxiv-cs-ro

Stateful Online Monitoring Catches Distributed Agent Attacks

arXiv:2605.31593v1 Announce Type: cross Abstract: Language models can find thousands of severe software vulnerabilities, and agents are increasingly being misused for cyberattacks. To avoid detection,

safetyarxiv-cs-ai

SteerFace: Debiasing Synthetic Face Generation via Adaptive Residue Perturbation

arXiv:2605.30894v1 Announce Type: new Abstract: The shortage of legally compliant data for face recognition training has sparked growing interest in using synthetic data as an alternative. While recen

Steering LLMs? Actually, Sparse Autoencoders can outperform simple baselines

arXiv:2605.31183v1 Announce Type: cross Abstract: Sparse Autoencoders (SAEs) have been seen as a promising avenue for exploring the internals of Large Language Models (LLMs) and for steering model out

STEP: Learning STructured Embeddings for Progressive Time Series

arXiv:2605.31061v1 Announce Type: cross Abstract: We present a novel method for learning interpretable representations of progressive time series, that is, data capturing irreversible state transition

tutorialsarxiv-cs-ai

Stochastic Gradients under Nuisances

arXiv:2508.20326v2 Announce Type: replace-cross Abstract: Stochastic gradient optimization is the dominant learning paradigm for a variety of scenarios, from classical supervised learning to modern se

researcharxiv-cs-lg

Stop the Flip-Flop: Context-Preserving Verification for Fast Revocable Diffusion Decoding

arXiv:2602.06161v2 Announce Type: replace-cross Abstract: Parallel diffusion decoding can accelerate diffusion language model inference by unmasking multiple tokens per step, but aggressive parallelis

researcharxiv-cs-ai

Structural Bias Beyond Homophily: A Study of Fairness in Link Prediction

arXiv:2602.11802v2 Announce Type: replace Abstract: Graph link prediction (LP) plays a critical role in socially impactful applications such as job recommendation and friendship formation, making fair

Structure-Induced Information for Rerooting Levin Tree Search

arXiv:2605.30664v1 Announce Type: new Abstract: Subgoal-based policy tree search, which uses a policy to guide search, is effective for complex single-agent deterministic problems but often relies on

safetyarxiv-cs-ai

Structured interactions improve distributed coordination beyond model scaling in a real-world multi-robot system

arXiv:2605.30383v1 Announce Type: cross Abstract: Scaling individual robot capabilities is common but costly. Here we investigate a system-level design question in real-world multi-robot coordination:

Student Capacity Moderates Knowledge Distillation Effectiveness: A Systematic Study Across ResNet Teacher-Student Pairs on CIFAR-10

arXiv:2605.31191v1 Announce Type: cross Abstract: We investigate how teacher-student capacity relationships modulate knowledge distillation (KD) effectiveness in ResNet-based image classification on C

Subspace-Decomposed JEPAs: Disentangling Progression and Content in Latent World Models

arXiv:2605.31111v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) learn compact latent world models by predicting future embeddings, but no single coordinate of the late

agentsarxiv-cs-lg

Hardware

SubsurfaceGen: Procedural Generation of Field-Scale Earth Models and Seismic Data

arXiv:2605.30541v1 Announce Type: new Abstract: Full waveform inversion (FWI) is the gold standard for subsurface imaging, with applications from carbon sequestration to energy and mineral exploration

hardwarearxiv-cs-lg

Supervised Learning as Lossy Compression: Characterizing Generalization and Sample Complexity via Finite Blocklength Analysis

arXiv:2602.04107v2 Announce Type: replace Abstract: This paper presents a novel information-theoretic perspective on generalization in machine learning by framing the learning problem within the conte

Supervised Training Rapidly Degrades Early Visual Cortex Alignment Across Biologically Plausible Learning Rules

arXiv:2605.30556v1 Announce Type: new Abstract: Random, untrained neural networks consistently match or exceed trained networks in representational similarity to early visual cortex. This puzzling fin

Surface Constraint Policy for Learning Surface-Constrained and Dynamically Feasible Robot Skills

arXiv:2605.31321v1 Announce Type: new Abstract: Diffusion-based imitation learning methods have driven rapid progress in robot dexterous manipulation tasks. However, they have limitations when applied

safetyarxiv-cs-ro

Local Ai

SurGe: Improved Surface Geometry in Point Maps

arXiv:2605.31577v1 Announce Type: new Abstract: Recent feedforward 3D reconstruction methods predict point maps and estimate global 3D geometry remarkably well. However, their predictions still exhibi

local-aiarxiv-cs-cv

Surprised by Attention: Predictable Query Dynamics for Time Series Anomaly Detection

arXiv:2603.12916v3 Announce Type: replace-cross Abstract: Multivariate time series anomalies often manifest as shifts in cross-channel dependencies rather than simple amplitude excursions. In autonomo

Survival Reinforcement Learning: Toward Scalable Self-Supervised RL

arXiv:2605.31273v1 Announce Type: new Abstract: While self-supervised Contrastive Reinforcement Learning (CRL) has shown remarkable depth-scaling capabilities, successfully using networks over 64 laye

agentsarxiv-cs-lg

SVI-Bench: A Dynamic Microworld for Strategic Video Intelligence

model-releasesarxiv-cs-cv

arXiv:2605.31529v1 Announce Type: new Abstract: True video intelligence demands more than recognizing what is visible: it requires reasoning about why events unfold, predicting what would change under

SWIM: Single-Instance Whole-Body Imitation for swiMming

arXiv:2605.31120v1 Announce Type: cross Abstract: We propose a new method for synthesizing physically-based swimming motions. Physically-based character animation aims to generate physically valid, co

tutorialsarxiv-cs-ai

Symbolic Intermediaries as a Linguistic-Numerical Interface for LLM-Driven Geometric Reasoning

arXiv:2505.17607v3 Announce Type: replace Abstract: Large Language Models (LLMs) display reasoning capabilities over linguistic and symbolic objects but have limited capabilities to directly interpret

Synthetic Stimuli, Real Gains: Rethinking VLM Fine-Tuning Through Fully Controlled Data Generation

arXiv:2511.11440v3 Announce Type: replace-cross Abstract: Performance gains of Vision Language Models (VLMs) obtained by fine-tuning are generally based on ad hoc data collection and annotation of rea

safetyarxiv-cs-cl