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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

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Human DGX agent

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

DGX agent

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

19 May 2026

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

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

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

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

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

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

safetyarxiv-cs-cv

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

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

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

Tutorials

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

Tutorials

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

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

Spatiotemporal Robustness of Temporal Logic Tasks using Multi-Objective Reasoning

arXiv:2603.29868v2 Announce Type: replace Abstract: The reliability of autonomous systems depends on their robustness, i.e., their ability to meet their objectives under uncertainty. In this paper, we

Speak Your Mind: The Speech Continuation Task as a Probe of Voice-Based Model Bias

arXiv:2509.22061v2 Announce Type: replace-cross Abstract: Speech Continuation (SC) is the task of generating a coherent extension of a spoken prompt while preserving both semantic context and speaker

safetyarxiv-cs-cl

SpecSem-Net: Integrating Spectral and Semantic Features for Robust AI-generated Video Detection

arXiv:2605.17311v1 Announce Type: new Abstract: The remarkable visual fidelity of recent commercial video generative models, such as Sora and Veo, renders robust AI-generated video detection increasin

Spectral Progressive Diffusion for Efficient Image and Video Generation

arXiv:2605.18736v1 Announce Type: new Abstract: Diffusion models have been shown to implicitly generate visual content autoregressively in the frequency domain, where low-frequency components are gene

researcharxiv-cs-cv

Speech-Guided Multimodal Learning for Vocal Tract Segmentation in Real-Time MRI

arXiv:2605.18466v1 Announce Type: new Abstract: Segmenting vocal tract articulators in real-time MRI (rtMRI) is a challenging dynamic image segmentation problem characterized by low contrast, rapid mo

local-aiarxiv-cs-cv

Speech-Hands: A Self-Reflection Voice Agentic Approach to Speech Recognition and Audio Reasoning with Omni Perception

arXiv:2601.09413v2 Announce Type: replace-cross Abstract: We introduce a voice-agentic framework that learns one critical omni-understanding skill: knowing when to trust itself versus when to consult

Hardware

Spherical Harmonic Optimal Transport: Application to Climate Models Comparisons

arXiv:2605.18389v1 Announce Type: new Abstract: Optimal transport provides a powerful framework for comparing measures while respecting the geometry of their support, but comes with an expensive compu

hardwarearxiv-cs-lg

Spherical Steering: Geometry-Aware Activation Rotation for Language Models

arXiv:2602.08169v2 Announce Type: replace-cross Abstract: Inference-time steering offers a promising way to control language models (LMs) without retraining. However, standard approaches typically rel

researcharxiv-cs-cl

Spherical VAE with Cluster-Aware Feasible Regions: Guaranteed Prevention of Posterior Collapse

arXiv:2603.10935v4 Announce Type: replace-cross Abstract: Variational autoencoders (VAEs) frequently suffer from posterior collapse, where the latent variables become uninformative as the approximate

SPIKE: An Adaptive Dual Controller Framework for Cost-Efficient Long-Horizon Game Agents

arXiv:2605.18636v1 Announce Type: new Abstract: Long-horizon multimodal agents in open-world games must stay goal-directed across many low-level interactions under tight token and latency budgets. Exi

researcharxiv-cs-cv

Spiker-LL: An Energy-Efficient FPGA Accelerator Enabling Adaptive Local Learning in Spiking Neural Networks

arXiv:2605.18003v1 Announce Type: cross Abstract: Deploying adaptive intelligence at the edge remains challenging due to the high computational and energy cost of training neural models. Spiking Neura

local-aiarxiv-cs-ai

Tutorials

SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation

arXiv:2605.18267v1 Announce Type: new Abstract: Normalizing flows (NFs) provide exact likelihoods and deterministic invertible sampling, but have historically lagged behind diffusion models for large-

tutorialsarxiv-cs-cv

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

safetyarxiv-cs-ai

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

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

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

researcharxiv-cs-lg

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

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

safetyarxiv-cs-ai

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

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-