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Self-Improving Diffusion Classifiers with Minority Preference Optimization

arXiv:2607.03770v1 Announce Type: cross Abstract: Prior studies have demonstrated that diffusion classifiers achieve robust zero-shot classification performance. However, their effectiveness is strong

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Self-Reference in Large Language Models: The Introspection Threshold for Recursive Self-Improvement

DGX agent

arXiv:2607.04277v1 Announce Type: cross Abstract: The pursuit of self-evolving AI raises a critical question: when is autonomous self-improvement sustainable rather than degenerative? Drawing an analo

safetyarxiv-cs-ai

7 Jul 2026

Self-Specializing Vision-Language Transmon Chip Calibration in a Physics-Grounded Environment

arXiv:2607.03193v1 Announce Type: cross Abstract: Calibrating a superconducting transmon chip is a sequential decision problem under noise, drift, and a finite budget: an expert must choose experiment

Self-Supervised Goal-Reaching Results in Multi-Agent Cooperation and Exploration

arXiv:2509.10656v2 Announce Type: replace-cross Abstract: For groups of autonomous agents to achieve a particular goal, they must engage in coordination and long-horizon reasoning. Rather than relying

Self-Supervised Learning from Structural Invariance

arXiv:2602.02381v2 Announce Type: replace Abstract: Joint-embedding self-supervised learning (SSL), the key paradigm for unsupervised representation learning from visual data, learns from invariances

SelfMem: Self-Optimizing Memory for AI Agents

arXiv:2607.03726v1 Announce Type: new Abstract: While current AI agents support increasingly long context windows, tool use, and skill execution for long-horizon tasks, they still require memory syste

agentsarxiv-cs-cl

Semantic-Guided Progressive Object Removal with Gaussian Splatting

arXiv:2607.04144v1 Announce Type: new Abstract: Removing unwanted objects from reconstructed 3D scenes is an important task in computer vision, supporting applications in AR/VR, robotics, and digital

researcharxiv-cs-ro

Semantic Homogenization in Italian Popular Music: A Diachronic Analysis

arXiv:2607.04832v1 Announce Type: new Abstract: In recent years, studies have revealed a decline in semantic variety across popular music lyrics, particularly in English-language songs on streaming pl

researcharxiv-cs-cl

Local Ai

Semantic Integration and Lexical Expectation Shape N400 and P600 Dynamics During Naturalistic Reading

arXiv:2607.04107v1 Announce Type: new Abstract: Word surprisal is a well-established computational predictor of human neural responses during language comprehension, but it remains less clear whether

local-aiarxiv-cs-cl

Semantic Segmentation-Driven Image-Level Diagnosis of Liver Cancers in Hematoxylin and Eosin Histopathology Images

arXiv:2607.03253v1 Announce Type: cross Abstract: As hematoxylin & eosin (H&E) staining constitutes the primary entry point in routine diagnostic workflows, computer-aided diagnosis from whole-slide H

Semantic Video Communication via Multi-Scale Convolution and Dynamic Routing for Next-Generation Networks

arXiv:2607.05093v1 Announce Type: new Abstract: The exponential growth of video traffic demands novel semantic communication paradigms that transmit meaning rather than raw bits. We present a generati

safetyarxiv-cs-cv

Semi-parametric Functional Classification via Path Signatures Logistic Regression with Adaptive Order Selection

arXiv:2507.06637v2 Announce Type: replace-cross Abstract: We propose Path Signatures Logistic Regression (PSLR), a semi-parametric framework for classifying vector-valued functional data with scalar c

applicationsarxiv-cs-lg

Semidefinite programming relaxations and debiasing for MAXCUT-based clustering

arXiv:2401.10927v3 Announce Type: replace-cross Abstract: In this paper, we consider the problem of partitioning a small data sample of size n drawn from a mixture of 2 sub-gaussian distributions in R

Sensitivity Sampling with Predictions for k-Means Clustering

arXiv:2607.04949v1 Announce Type: new Abstract: We study the problem of k-means clustering on large datasets. The state-of-the-art for the problem is given by coresets-based approaches, which build sm

Separating Representation from Reconstruction Enables Scalable Text Encoders

arXiv:2607.04011v1 Announce Type: cross Abstract: While decoders have rapidly scaled, encoders have remained largely unchanged since BERT. We revisit this disparity by frozen backbone evaluation via p

Sequential Cohort Selection under Uncertainty

arXiv:2508.16386v2 Announce Type: replace Abstract: We study the problem of fair cohort selection under uncertainty, motivated by university admissions where applicant outcomes are only partially obse

safetyarxiv-cs-lg

Sequential Correlations Change In-Context Learning: Effective Context Length and Architectural Mismatch

arXiv:2607.03660v1 Announce Type: cross Abstract: Modern sequence models have a striking capacity for in-context learning (ICL); they can perform new tasks based only on examples given in the prompt.

Serious Games: Human-AI Interaction, Evolution, and Coevolution

arXiv:2505.16388v2 Announce Type: replace Abstract: The serious games between humans and AI have only just begun. Evolutionary Game Theory (EGT) models the competitive and cooperative strategies of bi

Server-side Anti-cheat in FPS games for Aimbot detection using Deep learning and Machine learning

arXiv:2607.04336v1 Announce Type: new Abstract: Modern video games are becoming more complex day by day. Most of these modern games are multiplayer first-person shooter (FPS) games. The rising popular

SGF-CDNet: A Consistency-Discrepancy Graph Network over Semantic-Geometric Fused Nodes for Face Forgery Detection

arXiv:2607.03883v1 Announce Type: new Abstract: The rapid advancement of deepfakes necessitates robust face forgery detection. Although forged faces may lack obvious artifacts, they often contain subt

researcharxiv-cs-cv

Shapley-based Data Valuation for LLM Alignment via Sequential Preference Optimization

arXiv:2512.15765v3 Announce Type: replace Abstract: Data valuation is a natural framework for understanding which preference datasets matter most when aligning a Large Language Model (LLM) using multi

safetyarxiv-cs-lg

SharpSplat: Edge-Regularized 3D Gaussian Splatting for High Fidelity Urban Building Reconstruction from UAV images

arXiv:2607.03872v1 Announce Type: new Abstract: Reconstructing high-fidelity 3D building models from UAV imagery is essential for large-scale digital twin development. However, existing 3D Gaussian Sp

researcharxiv-cs-cv

Shifting from Discrete to Continuous Reference Data: QSM-Derived Horizontal Tree Biomass Distribution for Deep Learning Biomass Estimation

arXiv:2607.05260v1 Announce Type: cross Abstract: Conventional modeling approaches for LiDAR-based above-ground biomass (AGB) estimation rely on discrete plot-level inventory aggregates. This methodol

SHiPPO: Recurrent Memory with Transported Polynomial Projections

arXiv:2607.03055v1 Announce Type: new Abstract: HiPPO gives recurrent states memory semantics as coefficients of online polynomial projections, but in fixed channel coordinates. Modern selective SSMs,

Short-Horizon Position Accuracy of Single-Track Models: Implications for Motion Planning of Autonomous Vehicles

arXiv:2606.14216v2 Announce Type: replace Abstract: Accurate and computationally efficient vehicle models are essential for motion planning of autonomous vehicles, where positional accuracy directly a

safetyarxiv-cs-ro

Shortcut Learning in Legal Judgment Prediction: Empirical Evidence from the UK Employment Tribunal

arXiv:2607.04261v1 Announce Type: new Abstract: Current Legal Judgment Prediction (LJP) is constrained by its reliance on post-hoc judicial materials, increasing the likelihood that models perform ret

applicationsarxiv-cs-ai

Tutorials

Show Me Examples: Inferring Visual Concepts from Image Sets

arXiv:2607.02402v2 Announce Type: replace Abstract: Vision-language models (VLMs) can follow complex textual instructions, yet they struggle to reason from purely visual context. In particular, curren

tutorialsarxiv-cs-cv

Shutdownable Agents through POST-Agency

arXiv:2505.20203v4 Announce Type: replace Abstract: Many fear that future artificial agents will resist shutdown. I present an idea - the POST-Agents Proposal - for ensuring that doesn't happen. I pro

SiamixFormer: a fully-transformer Siamese network with temporal Fusion for accurate building detection and change detection in bi-temporal remote sensing images

arXiv:2208.00657v2 Announce Type: cross Abstract: Building detection and change detection using remote sensing images can help urban and rescue planning. Moreover, they can be used for building damage

SiamJEPA: On the Role of Siamese Student Encoders in JEPA

arXiv:2607.04044v1 Announce Type: new Abstract: Recently, Joint Embedding Predictive Architectures (JEPAs) have attracted significant attention in the computer vision and machine learning communities

safetyarxiv-cs-cv

Signal from Space: Detecting Schools and Towers to Bridge the Digital Divide

arXiv:2607.02724v1 Announce Type: cross Abstract: Reliable internet access is essential for modern education, yet millions of school-aged children especially in developing regions remain offline due t

applicationsarxiv-cs-ai

Signal or Noise? Understanding Generative Models for Real-World Sensor Time Series

arXiv:2607.04245v1 Announce Type: cross Abstract: Generative models have changed how machine learning represents complex data distributions, especially in language and vision, yet many real-world syst

applicationsarxiv-cs-ai

Signal Structure-Aware Gaussian Splatting for Large-Scale Scene Reconstruction

arXiv:2607.01698v2 Announce Type: replace Abstract: 3D Gaussian Splatting has demonstrated remarkable potential in novel view synthesis. In contrast to small-scale scenes, large-scale scenes inevitabl

researcharxiv-cs-cv

Significance-First Splitting: Aligning Treatment Heterogeneity Detection with Honest Estimation

arXiv:2607.03999v1 Announce Type: cross Abstract: Estimating heterogeneous treatment effects (CATE) requires simultaneously detecting effect modification and quantifying estimation uncertainty. Existi

Silicon Sampling via Cross-Survey Transfer

arXiv:2607.03091v1 Announce Type: new Abstract: Silicon sampling-using large language models (LLMs) to simulate human survey respondents-has emerged as a promising approach for augmenting traditional

safetyarxiv-cs-ai

Hardware

SILO: Simulation-in-the-Loop Sim-to-Real Transfer for Multi-Stage Cable Routing

arXiv:2607.04616v1 Announce Type: cross Abstract: Linear-deformable manipulation remains challenging due to the complex deformations of objects such as cables and ropes. Prior data-driven approaches,

hardwarearxiv-cs-ai

SilvaScenes: Tree Detection and Species Classification from Under-Canopy Images in Natural Forests

model-releasesarxiv-cs-ai

arXiv:2510.09458v2 Announce Type: replace-cross Abstract: Interest in forestry automation is growing alongside rapid advances in deep learning. In particular, tree detection and taxonomic classificati

Simple-to-Complex Structured Demonstrations for Vision-Language-Action Learning

arXiv:2607.04591v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have demonstrated strong capabilities in robotic manipulation by integrating visual perception, language understan

safetyarxiv-cs-ai

SIMPLER: Efficient Foundation Model Adaptation via Similarity-Guided Layer Pruning for Earth Observation

model-releasesarxiv-cs-cv

arXiv:2603.19873v2 Announce Type: replace Abstract: Fine-tuning foundation models for Earth Observation is computationally expensive, with high training time and memory demands for both training and d

SkillFab: An Agent-Native Skill Production Platform

arXiv:2607.03780v1 Announce Type: cross Abstract: SkillFab is an agent-native platform for turning missing capabilities into reviewed, reusable Agent Skills. At runtime, agents first search for reusab

SkillOpt-Lite: Better and Faster Agent Self-evolution via One Line of Vibe

model-releasesarxiv-cs-ai

arXiv:2607.03451v1 Announce Type: cross Abstract: While skill optimization for autonomous agents has gained traction, existing methods rely on complex pipelines. This leaves a fundamental question una

SLAM: Structured and Localized Analytic Manifold Adaptation for Lifelong VPR

model-releasesarxiv-cs-cv

arXiv:2607.04764v1 Announce Type: cross Abstract: Visual Place Recognition (VPR) in lifelong deployment requires continuous adaptation to new environments without catastrophic forgetting. In this pape

SleepBand: Single-Source Domain Generalization for Sleep Staging via Physiologically Structured Spectral Modeling

arXiv:2607.04851v1 Announce Type: cross Abstract: Generalizing sleep staging models to unseen datasets is challenging, and typical domain generalization (DG) methods often rely on multiple source doma

SMART: A Machine Learning and Monte Carlo Framework for Rapid Analysis of Stochastic Transistor Aging and Process Variation in Digital Circuits

model-releasesarxiv-cs-lg

arXiv:2607.05187v1 Announce Type: new Abstract: As CMOS technology scales into the deep nanometer regime, digital circuit reliability is increasingly threatened by the combined stochastic effects of B

SMF-VO: Direct Ego-Motion Estimation via Sparse Motion Fields

model-releasesarxiv-cs-cv

arXiv:2511.09072v2 Announce Type: replace-cross Abstract: Traditional Visual Odometry (VO) and Visual Inertial Odometry (VIO) methods rely on a 'pose-centric' paradigm, which computes absolute camera

SMOCS: A Streaming Framework for Simplified Deployment, Monitoring, and Optimization of ML Systems in Production

arXiv:2607.02731v1 Announce Type: cross Abstract: Machine learning has demonstrated significant potential for real-time monitoring, optimization, and control of scientific facilities. However, deployi

Smooth %MinMax: A Differentiable Relaxation for Codon Harmonization

arXiv:2607.03881v1 Announce Type: cross Abstract: Codon harmonization aims to adapt the coding sequences for heterologous expression while preserving the native-like patterns of frequent and rare codo

Local Ai

SnapGen++: Unleashing Diffusion Transformers for Efficient High-Fidelity Image Generation on Edge Devices

arXiv:2601.08303v3 Announce Type: replace Abstract: Recent advances in diffusion transformers (DiTs) have set new standards in image generation, yet remain impractical for on-device deployment due to

local-aiarxiv-cs-cv