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arXiv:2605.18007v1 Announce Type: new Abstract: Rhetorical Role Labeling (RRL) assigns a functional role to each sentence in a document and is widely used in legal, medical, and scientific domains. Wh

applicationsarxiv-cs-cl

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Safety

Semantic Smoothing via Novel View Synthesis for Robust SAR Image Classification

DGX agent

arXiv:2605.16440v1 Announce Type: cross Abstract: Deep neural networks are vulnerable to adversarial perturbations, limiting deployment in safety-critical applications such as synthetic aperture radar

safetyarxiv-cs-ai

19 May 2026

Semantics Disentanglement and Composition for Universal Image Coding with Efficiently LLM Reasoning and Generative Diffusion

arXiv:2412.18158v2 Announce Type: replace Abstract: Learned image compression methods have shown impressive performance but are often highly specialized for either human perception or specific machine

researcharxiv-cs-cv

Semi-LAR: Semi-supervised Contrastive Learning with Linear Attention for Removal of Nighttime Flares

arXiv:2605.18156v1 Announce Type: new Abstract: Lens flare removal is challenging due to the large spatial extent of flare artifacts and their entanglement with scene structures, while existing method

researcharxiv-cs-cv

SENSE: Satellite-based ENergy Synthesis for Sustainable Environment

arXiv:2605.18101v1 Announce Type: cross Abstract: Urban Building Energy Modeling plays a critical role in achieving the United Nations' Sustainable Development Goals 7 and 11. Although existing studie

researcharxiv-cs-ai

Applications

Sequential Structure in Intraday Futures Data: LSTM vs Gradient Boosting on MNQ

arXiv:2605.17724v1 Announce Type: cross Abstract: This paper compares gradient boosting and long short-term memory (LSTM) architectures for intraday directional prediction in Micro E-Mini Nasdaq 100 f

applicationsarxiv-cs-lg

Setting the Stage: Text-Driven Scene-Consistent Image Generation

model-releasesarxiv-cs-cv

arXiv:2512.12598v3 Announce Type: replace Abstract: We focus on the foundational task of Scene Staging: given a reference scene image and a text condition specifying an actor category to be generated

SG-CADVLM: A Context-Aware Decoding Powered Vision Language Model for Safety-Critical Scenario Generation

arXiv:2601.18442v3 Announce Type: replace Abstract: Autonomous Vehicle (AV) requires rigorous testing in safety-critical scenarios for safety validation, yet its validation is hindered by the high cos

safetyarxiv-cs-ro

SGSoft: Learning Fused Semantic-Geometric Features for 3D Shape Correspondence via Template-Guided Soft Signals

arXiv:2605.18039v1 Announce Type: new Abstract: Learning dense correspondences across deformable 3D shapes remains a long-standing challenge due to structural variability, non-isometric deformation, a

Shallow Deep Learning Can Still Excel in Fine-Grained Few-Shot Learning

arXiv:2507.22041v2 Announce Type: replace Abstract: Deep learning has witnessed the extensive utilization across a wide spectrum of domains, including fine-grained few-shot learning (FGFSL) which heav

researcharxiv-cs-cv

Shallow ReLU^s Networks in L^p-Type and Sobolev Spaces: Approximation and Path-Norm Controlled Generalization

model-releasesarxiv-cs-lg

arXiv:2605.18468v1 Announce Type: cross Abstract: We study approximation by shallow ReLU^s networks, sigma_s(t)=max{0,t}^s, and the generalization behavior of such networks under ell_1 path-norm contr

ShareChat: A Dataset of Chatbot Conversations in the Wild

arXiv:2512.17843v4 Announce Type: replace-cross Abstract: By evaluating Large Language Models (LLMs) through uniform, text-only interfaces, current academic benchmarks obscure how the unique designs a

Shared Backbone PPO for Multi-UAV Communication Coverage with Connection Preservation

arXiv:2605.17999v1 Announce Type: new Abstract: This paper proposes a Shared Backbone Proximal Policy Optimization (Shared Backbone PPO) algorithm. By sharing the base module between the Actor and Cri

safetyarxiv-cs-ai

SHED: Style-Homogenized Embedding Alignment for Domain Generalization

arXiv:2605.16973v1 Announce Type: new Abstract: Domain generalization aims to enhance model robustness against unseen domains with embedding distribution shifts. While large-scale vision-language mode

Shift Detection and Adaptation for Network Intrusion Detection

arXiv:2508.15100v2 Announce Type: replace-cross Abstract: Distribution shift, a change in the statistical properties of data over time, poses a critical challenge for deep learning anomaly detection s

researcharxiv-cs-lg

Hardware

SignMuon: Communication-Efficient Distributed Muon Optimization

arXiv:2605.16311v1 Announce Type: new Abstract: Distributed training of large neural networks is bottlenecked by full-precision gradient communication and by coordinatewise optimizers that ignore the

hardwarearxiv-cs-lg

SignRoundV2: Toward Closing the Performance Gap in Extremely Low-Bit Post-Training Quantization for LLMs

arXiv:2512.04746v2 Announce Type: replace-cross Abstract: Extremely low-bit quantization is critical for efficiently deploying Large Language Models (LLMs), yet it often leads to severe performance de

tutorialsarxiv-cs-ai

Simple Approximation and Derivative Free Inference-Time Scaling for Diffusion Models via Sequential Monte Carlo on Path Measures

arXiv:2605.17850v1 Announce Type: cross Abstract: iffusion-based generative models increasingly rely on inference-time guidance, adding a drift term or reweighting mixture of experts, to improve sampl

Single Image Reflection Removal with Patch Reflectance Prior

arXiv:2312.03798v2 Announce Type: replace Abstract: Single Image Reflection Removal (SIRR) in real-world images is a challenging task due to diverse image degradations occurring on the glass surface d

tutorialsarxiv-cs-cv

Single-Sample Black-Box Membership Inference Attack against Vision-Language Models via Cross-modal Semantic Alignment

arXiv:2605.17341v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have achieved remarkable success, yet their reliance on massive datasets and unintended memorization of training data ra

safetyarxiv-cs-ai

SIPO: Stabilized and Improved Preference Optimization for Aligning Diffusion Models

arXiv:2505.21893v3 Announce Type: replace-cross Abstract: Preference learning has garnered extensive attention as an effective technique for aligning diffusion models with human preferences in visual

SIREM: Speech-Informed MRI Reconstruction with Learned Sampling

model-releasesarxiv-cs-cl

arXiv:2605.18221v1 Announce Type: cross Abstract: Real-time magnetic resonance imaging (rtMRI) of speech production enables non-invasive visualization of dynamic vocal-tract motion and is valuable for

Local Ai

Sketch Then Paint: Hierarchical Reinforcement Learning for Diffusion Multi-Modal Large Language Models

arXiv:2605.16842v1 Announce Type: new Abstract: Diffusion Multi-Modal Large Language Models (dMLLMs) are powerful for image generation, but optimizing them through reinforcement learning (RL) remains

local-aiarxiv-cs-ai

Local Ai

SKG-Eval: Stateful Evaluation of Multi-Turn Dialogue via Incremental Semantic Knowledge Graphs

arXiv:2605.16650v1 Announce Type: cross Abstract: Evaluating multi-turn dialogue systems remains challenging because response quality depends not only on the current prompt, but also on previously est

local-aiarxiv-cs-ai

SkillGenBench: Benchmarking Skill Generation Pipelines for LLM Agents

arXiv:2605.18693v1 Announce Type: new Abstract: As LLM agents are increasingly built around reusable skills, a central challenge is no longer only whether agents can use provided skills, but whether t

Agents

SkillJect: Effectively Automating Skill-Based Prompt Injection for Skill-Enabled Agents

arXiv:2602.14211v2 Announce Type: replace-cross Abstract: Agent skills are increasingly used to extend LLM agents with task-specific instructions, executable scripts, and auxiliary resources. While im

agentsarxiv-cs-ai

Skills on the Fly: Test-Time Adaptive Skill Synthesis for LLM Agents

arXiv:2605.16986v1 Announce Type: cross Abstract: LLM agents benefit from reusable skills, yet test-time tasks often require guidance more specific than a static skill library can provide. We propose

SkillsVote: Lifecycle Governance of Agent Skills from Collection, Recommendation to Evolution

arXiv:2605.18401v1 Announce Type: cross Abstract: Long-horizon LLM agents leave traces that could become reusable experience, but raw trajectories are noisy and hard to govern. We treat Agent Skills a

Agents

Skim: Speculative Execution for Fast and Efficient Web Agents

arXiv:2605.16565v1 Announce Type: new Abstract: Skim is a speculative execution framework for web agents that exploits the predictable structure of purpose-built websites. Today's web-agent expense is

agentsarxiv-cs-ai

SkyNative: A Native Multimodal Framework for Remote Sensing Visual Evidence Reasoning

model-releasesarxiv-cs-cv

arXiv:2605.17949v1 Announce Type: new Abstract: Remote sensing vision-language models commonly rely on pretrained visual encoders to convert images into semantic features before language-model reasoni

SLEIGHT-Bench: A Benchmark of Evasion Attacks Against Agent Monitors

arXiv:2605.16626v1 Announce Type: cross Abstract: Since autonomous coding agents generate complex behaviors at high-volume, we may want to use other LLMs to monitor actions to reduce the risk from dan

Small-scale photonic Kolmogorov-Arnold networks using standard telecom nonlinear modules

arXiv:2604.08432v2 Announce Type: replace-cross Abstract: Photonic neural networks promise ultrafast inference, yet most architectures rely on linear optical meshes with electronic nonlinearities, rei

SNLP: Layer-Parallel Inference via Structured Newton Corrections

arXiv:2605.17842v1 Announce Type: new Abstract: Autoregressive language models execute Transformer layers sequentially, creating a latency bottleneck that is not removed by conventional tensor or pipe

safetyarxiv-cs-lg

Soap2Soap: Long Cinematic Video Remaking via Multi-Agent Collaboration

arXiv:2605.17423v1 Announce Type: new Abstract: We study series-level cinematic remaking, a long-horizon video-to-video generation problem that localizes full episodes or films via stylization or acto

SocialMemBench: Are AI Memory Systems Ready for Social Group Settings?

arXiv:2605.17789v1 Announce Type: cross Abstract: Memory systems for AI assistants were built for single-user dialogue and fail characteristically when applied to multi-party social group settings. Th

SomaliWeb v1: A Quality-Filtered Somali Web Corpus with a Matched Tokenizer and a Public Language-Identification Benchmark

arXiv:2605.18232v1 Announce Type: cross Abstract: Somali is a Cushitic language of the Horn of Africa with ~25 million speakers, yet no documented dedicated Somali pretraining corpus with a companion

Agents

Some[Body] Must Receive That Pain for Agent Accountability

arXiv:2605.16872v1 Announce Type: cross Abstract: AI agents increasingly act consequentially in the real world. This creates a problem we call consequence reception: harm occurs, the producing system

agentsarxiv-cs-ai

Sometin Beta Pass Notin (SBPN): Improving Multilingual ASR for Nigerian Languages via Knowledge Distillation

model-releasesarxiv-cs-cl

arXiv:2605.17710v1 Announce Type: new Abstract: Although modern multilingual Automatic Speech Recognition (ASR) systems support several Nigerian languages, their performance consistently lags behind h

Applications

SonarSweep: Fusing Sonar and Vision for Robust 3D Reconstruction via Plane Sweeping

arXiv:2511.00392v2 Announce Type: replace-cross Abstract: Accurate 3D reconstruction in visually-degraded underwater environments remains a formidable challenge. Single-modality approaches are insuffi

applicationsarxiv-cs-ai

Sparse Autoencoders are Topic Models

arXiv:2511.16309v2 Announce Type: replace Abstract: Sparse autoencoders (SAEs) are used to analyze embeddings, but their role and practical value are debated. We propose a new perspective on SAEs by d

tutorialsarxiv-cs-cv

Sparse Deep Additive Model with Interactions: Enhancing Interpretability and Predictability

arXiv:2509.23068v2 Announce Type: replace-cross Abstract: Recent advances in deep learning highlight the need for personalized models that can learn from small samples, handle high-dimensional feature

tutorialsarxiv-cs-lg

Hardware

Sparse Mamba Decoder for Quantum Error Correction: Efficient Defect-Centric Processing of Surface Code Syndromes

arXiv:2605.17156v1 Announce Type: cross Abstract: Quantum error correction (QEC) is essential for building fault-tolerant quantum computers, requiring decoders that are simultaneously accurate, fast,

hardwarearxiv-cs-lg

Sparse-to-Dense: A Free Lunch for Lossless Acceleration of Video Understanding in LLMs

arXiv:2505.19155v2 Announce Type: replace-cross Abstract: Due to the auto-regressive nature of current video large language models (Video-LLMs), the inference latency increases as the input sequence l

researcharxiv-cs-cl

Sparse Training of Neural Networks based on Multilevel Mirror Descent

model-releasesarxiv-cs-lg

arXiv:2602.03535v2 Announce Type: replace Abstract: We introduce a dynamic sparse training algorithm based on linearized Bregman iterations / mirror descent that exploits the naturally incurred sparsi

SparseSAM: Structured Sparsification of Activations in Segment Anything Models

arXiv:2605.17633v1 Announce Type: cross Abstract: The Segment Anything Model (SAM) achieves strong open-vocabulary segmentation, but its ViT-based image encoders dominate inference latency and memory.

researcharxiv-cs-ai

Spatial Blindness in Whole-Slide Multiple Instance Learning

arXiv:2605.17449v1 Announce Type: cross Abstract: Whole-slide MIL models are often called context-aware once graphs, Transform ers, or state-space modules are placed above patch embeddings. We show th

researcharxiv-cs-ai

Local Ai

Spatially Aware Linear Transformer (SAL-T) for Particle Jet Tagging

arXiv:2510.23641v2 Announce Type: replace-cross Abstract: Transformers are very effective in capturing both global and local correlations within high-energy particle collisions, but they present deplo

local-aiarxiv-cs-ai

SPATIOROUTE: Dynamic Prompt Routing for Zero-Shot Spatial Reasoning

arXiv:2605.18209v1 Announce Type: cross Abstract: Spatial question answering over egocentric video is a challenging task that requires Vision-Language Models (VLMs) to reason about 3D object positions