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Scaling Up Thermodynamic AI Models

arXiv:2607.00170v1 Announce Type: cross Abstract: Thermodynamic computing devices based on the Ising model show great promise for low-power AI inference and edge computing, but scalable methods for tr

scDataset: Scalable Data Loading for Deep Learning on Large-Scale Single-Cell Omics

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arXiv:2506.01883v3 Announce Type: replace-cross Abstract: Training deep learning models on single-cell datasets with hundreds of millions of cells requires loading data from disk, as these datasets ex

researcharxiv-cs-ai

2 Jul 2026

SchemaRAG: Dynamic Large Schema Reduction for LLM-driven Structured Information Extraction

arXiv:2607.00008v1 Announce Type: cross Abstract: Extracting structured data from unstructured text using large language models (LLMs) becomes challenging when target schemas are large and complex. In

applicationsarxiv-cs-ai

SD-RouteFusion: Ego-Trajectory Prediction with SD-Map Route Conditioning

arXiv:2607.01139v1 Announce Type: new Abstract: This paper presents SD-RouteFusion, a deployable end-to-end ego-trajectory prediction method that fuses a front-facing camera, vehicle kinematics, and a

applicationsarxiv-cs-cv

Seahorse: A Unified Benchmarking Framework for Spatiotemporal Event Modeling

model-releasesarxiv-cs-lg

arXiv:2607.01022v1 Announce Type: new Abstract: Spatiotemporal point processes (STPPs) model event data in continuous time and space, with applications in mobility, epidemiology, and public safety. Re

Search-Based Spatiotemporal and Multi-Robot Motion Planning on Graphs of Space-Time Convex Sets

arXiv:2607.00444v1 Announce Type: cross Abstract: Spatiotemporal motion planning, especially in multi-robot settings, requires robots to reason about collision-free regions that change over time, whic

Seed2.0 Model Card: Towards Intelligence Frontier for Real-World Complexity

arXiv:2607.00248v1 Announce Type: new Abstract: We present Seed2.0, a model series that takes a meaningful step toward solving complex, real-world tasks. Our approach begins with identifying users' ge

applicationsarxiv-cs-ai

SEFORA: Student Essays with Feedback Corpus and LLM Feedback Evaluation Framework

arXiv:2607.00274v1 Announce Type: cross Abstract: Effective writing feedback is among the strongest drivers of student learning, yet producing it at scale is labor-intensive. LLMs offer a natural path

SegFly: A Dataset and 2D-3D-2D Paradigm for Aerial RGB-Thermal Semantic Segmentation at Scale

arXiv:2603.17920v2 Announce Type: replace Abstract: Semantic segmentation for uncrewed aerial vehicles (UAVs) is fundamental for aerial scene understanding, yet existing RGB and RGB-T datasets remain

Local Ai

Segmenting, Fast and Slow: Real-Time Open-Vocabulary Video Instance Segmentation with Dual-Path Processing

arXiv:2607.00124v1 Announce Type: new Abstract: Object-centric models inspired by DETR have become the dominant paradigm for open-vocabulary video instance segmentation (OV-VIS). While recent efforts

local-aiarxiv-cs-cv

Selective Expert Guidance for Effective and Diverse Exploration in Reinforcement Learning of LLMs

arXiv:2510.04140v2 Announce Type: replace Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become a widely adopted technique for enhancing the reasoning ability of Large Language Mo

Selective Test-Time Debiasing for CLIP via Reward Gating

arXiv:2607.00423v1 Announce Type: new Abstract: Vision language models (VLMs) demonstrate strong zero-shot performance, but often perpetuate social stereotypes in person-centric queries, yielding skew

safetyarxiv-cs-cl

Tutorials

Self-conditioned Flow Map Language Models via Fixed-point Flows

arXiv:2607.00714v1 Announce Type: cross Abstract: Self-conditioning is a core technique that enhances continuous flow-based language models, where the model learns to denoise generated text by conditi

tutorialsarxiv-cs-ai

Self-Evolving Agents with Anytime-Valid Certificates

arXiv:2607.00871v1 Announce Type: new Abstract: Self-evolving agents violate the assumption behind most learning-theoretic guarantees: the data, evaluator, components, and hypothesis space are produce

Self-GC: Self-Governing Context for Long-Horizon LLM Agents

arXiv:2607.00692v1 Announce Type: new Abstract: Long-horizon LLM agents accumulate tool results, files, plans, and user constraints that are too structured to be treated as a disposable text suffix. C

agentsarxiv-cs-ai

Tutorials

Self-Improving Neural Pruning: A Graph Neural Network Framework for Scalable Mixed Bundle Pricing

arXiv:2509.22557v3 Announce Type: replace Abstract: Mixed bundle pricing is a classic revenue management problem arising in industries such as e-commerce, tourism, and video games. It refers to design

tutorialsarxiv-cs-lg

Self-Organized Learning in Oscillatory Neural Networks with Memristive Signed Couplings

arXiv:2607.00286v1 Announce Type: cross Abstract: Oscillatory neural networks (ONNs) have emerged as a promising neuromorphic architecture, leveraging coupled dynamical systems to perform computation

agentsarxiv-cs-lg

Semantic-Guided Reading Order Reconstruction in Historical Armenian Newspapers with LLMs

arXiv:2607.00596v1 Announce Type: new Abstract: This paper addresses reading order reconstruction in historical Armenian newspapers, which combine complex layouts with limited language resources. We i

applicationsarxiv-cs-cv

SemEval-2026 Task 9: Detecting Multilingual, Multicultural and Multievent Online Polarization

arXiv:2604.06817v2 Announce Type: replace Abstract: We present SemEval-2026 Task 9, a shared task on online polarization detection, covering 22 languages and comprising over 110K annotated instances.

researcharxiv-cs-cl

Semi-Bandit Learning for Monotone Stochastic Optimization

arXiv:2312.15427v3 Announce Type: replace Abstract: Stochastic optimization is a widely used approach for optimization under uncertainty, where uncertain input parameters are modeled by random variabl

safetyarxiv-cs-lg

SemiScope: Disentangling Classifier Tuning and Joint Optimization in Semi-Supervised Security Classification

arXiv:2607.00113v1 Announce Type: new Abstract: Background. Labeled data for security classification is scarce. Semi-supervised learning (SSL) propagates labels from a small labeled pool to larger unl

researcharxiv-cs-lg

SenseWalk: Agent-Based Semantic Trajectory Simulation Powered by Large Language Models in Zoned Environments

arXiv:2607.00989v1 Announce Type: cross Abstract: Semantic trajectory analysis has recently emerged as an approach for modeling human movement by capturing implicit patterns and behaviors through sema

agentsarxiv-cs-ai

Sensorless Four-Channel Control Architecture Using Inverse Dynamics Modeling for Human-Scale Bilateral Teleoperation

arXiv:2607.01201v1 Announce Type: new Abstract: The four-channel teleoperation architecture is a well-established framework for achieving transparency in bilateral systems. However, its performance in

applicationsarxiv-cs-ro

Sequentially-Controlled Interactive Multi-Particle Flow-Maps for Online Feedback-Driven Search

arXiv:2607.01144v1 Announce Type: cross Abstract: While generative models have enabled training-free reward alignment, current methods typically excel in local exploration within narrow regions of the

SFDATrack: Generalized Source-Free Domain Adaptive Tracking Under Adverse Weather Conditions

arXiv:2607.00369v1 Announce Type: new Abstract: Domain adaptive visual object tracking under adverse weather conditions has garnered significant attention in recent years. Despite the impressive perfo

Shapley in Context: Explaining Financial Language with Domain Expertise

arXiv:2607.00856v1 Announce Type: cross Abstract: In recent years, large language models have achieved remarkable success and have seen growing adoption in financial applications. At the same time, ex

applicationsarxiv-cs-lg

Sheet Music Benchmark: Standardized Optical Music Recognition Evaluation

arXiv:2506.10488v3 Announce Type: replace Abstract: In this work, we introduce the Sheet Music Benchmark (SMB), a dataset of six hundred and eighty-five pages specifically designed to benchmark Optica

Skills Are Not Islands: Measuring Dependency and Risk in Agent Skill Supply Chains

model-releasesarxiv-cs-ai

arXiv:2607.01136v1 Announce Type: cross Abstract: Agent skills package reusable operational knowledge for Large Language Model (LLM) agents, yet as they grow in scope, they become dependency-bearing a

SkillSelect-Serve: Budget-Controllable and QoS-Aware Skill Service Recommendation and Composition for Small LLM Agents

arXiv:2607.00011v1 Announce Type: cross Abstract: Reusable skill libraries are becoming important infrastructure for large language model (LLM) agents, yet existing selection methods often treat skill

agentsarxiv-cs-ai

SkipGS: Post-Densification Backward Skipping for Efficient 3DGS Training

arXiv:2603.08997v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) achieves real-time novel-view synthesis by optimizing millions of anisotropic Gaussians, yet its training remains expen

SleepLM: Natural-Language Intelligence for Human Sleep

arXiv:2602.23605v2 Announce Type: replace Abstract: We present SleepLM, a family of sleep-language foundation models that enable human sleep alignment, interpretation, and interaction with natural lan

SLIM-RL: Risk-Budgeted Random-Masking RL for Diffusion LLMs Without Trajectory Slicing

arXiv:2607.00208v1 Announce Type: cross Abstract: Reinforcement learning for diffusion large language models (dLLMs) has largely moved to trajectory-aware methods. The current state of the art, TraceR

Slope-Guided Mamba and Angular-Refined Transformer for Light Field Super-Resolution

arXiv:2607.00965v1 Announce Type: new Abstract: Light Field Super-Resolution (LFSR) necessitates accurate modeling of spatial-angular correlations while preserving intrinsic 4D ray coherence. However,

SlowBA: An efficiency backdoor attack towards VLM-based GUI agents

arXiv:2603.08316v3 Announce Type: replace-cross Abstract: Modern vision-language-model (VLM) based graphical user interface (GUI) agents are expected not only to execute actions accurately but also to

agentsarxiv-cs-cl

Hardware

SNAP-FM: Sparse Nonlinear Accelerated Projection for Physics-Constrained Generative Modeling

arXiv:2607.00095v1 Announce Type: cross Abstract: Generative models have emerged as scalable surrogates for physical simulation, yet they offer no guarantee that their outputs respect the conservation

hardwarearxiv-cs-ai

SocialOmni: Benchmarking Audio-Visual Social Interactivity in Omni Models

model-releasesarxiv-cs-ai

arXiv:2603.16859v2 Announce Type: replace Abstract: Omni-modal large language models (OLMs) redefine human-machine interaction by natively integrating audio, vision, and text. However, existing OLM be

Soft Mixture-of-Recursions: Going Deeper with Recursive Vision Transformers

arXiv:2607.00774v1 Announce Type: new Abstract: Recent recursive Transformer studies have primarily reused shared parameters across computation steps to construct compact, parameter-efficient models.

Local Ai

SoK: Attack and Defense Landscape of Mobile On-device AI Systems

arXiv:2607.00362v1 Announce Type: cross Abstract: Mobile on-device AI (MoAI) systems that integrate locally deployed AI models with conventional mobile software components are emerging as a key paradi

local-aiarxiv-cs-ai

Solution space path planning for supporting en-route air traffic control

arXiv:2607.00064v1 Announce Type: new Abstract: As technology advances, many path-planning algorithms have been proposed for Air Traffic Management, yet their operational adoption in tactical control

SONIC: Spectral Optimization of Noise for Inpainting with Consistency

arXiv:2511.19985v3 Announce Type: replace Abstract: We propose a novel training-free method for inpainting with off-the-shelf text-to-image models. While guidance-based methods in theory allow generic

Spatio-Temporal Gaussian Process for Building Terrain-Incorporating Wind Power Curves

arXiv:2607.00051v1 Announce Type: cross Abstract: Accurate modeling of wind turbine power curves is crucial for optimal wind farm operation. Nearly all existing power curve models focus on temporal va

safetyarxiv-cs-lg

SPECSIA: Stylization Dataset for Novel-View Enhancement in Drawing-based 3D Animation

arXiv:2607.00525v1 Announce Type: new Abstract: Generating animation from a single 2D drawing is challenging because the output must preserve character appearance while remaining plausible and tempora

Spectral and Trajectory Regularization for Diffusion Transformer Super-Resolution

arXiv:2603.06275v2 Announce Type: replace Abstract: Diffusion transformer (DiT) architectures show great potential for real-world image super-resolution (Real-ISR). However, their computationally expe

Spectral Geometry and Bosonic-Bloch Probes: Explorations in Quantum Learning

arXiv:2607.00063v1 Announce Type: cross Abstract: This paper studies how spectral geometry emerges in quantum learning models and how it can be diagnosed with physically grounded probes. In graph-regu

Spectroscopy Analysis with Machine Learning Regression for the Quantification of Carbon and Nitrogen Contents in Inceptisol and Oxisol Soil Types: Comparing Different Preprocessing and Validation methods as well as Feature Importance

arXiv:2607.00834v1 Announce Type: new Abstract: Near-Infrared (NIR) spectroscopy has emerged as a promising alternative to traditional soil analysis methods, offering advantages such as speed, low cos

researcharxiv-cs-lg

Speech Playground: An Interactive Tool for Speech Analysis and Comparison

arXiv:2607.00418v1 Announce Type: new Abstract: This paper presents Speech Playground, an interactive speech visualization and comparison tool. While existing tools such as Praat are excellent, it can

safetyarxiv-cs-cl

SpiralFovea: Input-Adaptive Foveated Tokenization as a Third Lever of Resource-Adaptive Inference

arXiv:2607.00780v1 Announce Type: new Abstract: Most adaptive-inference techniques for foundation models change what the model does - early exit, MoE routing, KV-cache compression, dynamic attention s

Spotted: Location-informed Reidentification of Hyenas and Leopards in Camera Trap Surveys

arXiv:2607.00804v1 Announce Type: new Abstract: Animal re-identification (ReID) in camera-trap surveys remains challenging due to low image quality, strong variation in illumination and viewpoint, and