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arXiv:2609.27289v1 Announce Type: cross Abstract: Conventional Japanese automatic speech recognition (ASR) is supervised by an orthographic transcript, although the same written form can correspond to

local-aiarxiv-cs-ai

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Human DGX agent

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Safety

S2A:Semantic-to-Spatial Alignment for Alignment-Free RGB-T Salient Object Detection

DGX agent

arXiv:2609.27413v1 Announce Type: new Abstract: Alignment-free RGB-T salient object detection (RGB-T SOD) aims to identify salient objects from unregistered RGB and thermal image pairs without costly

safetyarxiv-cs-cv

24 Sept 2026

Safe learning-based control via function-based uncertainty quantification

arXiv:2604.01173v2 Announce Type: replace-cross Abstract: Uncertainty quantification is essential when deploying learning-based control methods in safety-critical systems. This is commonly realized by

safetyarxiv-cs-lg

Safe Multi-Robot Coordination via VLM-LLM Reasoning and Reachability Analysis

arXiv:2609.27816v1 Announce Type: cross Abstract: Safe coordination in heterogeneous machine-to-machine (M2M) robotic systems is challenging when robots differ in sensing capabilities, environmental a

SafeTutors: Benchmarking Pedagogical Safety in AI Tutoring Systems

arXiv:2603.17373v2 Announce Type: replace Abstract: Large language models are rapidly being deployed as AI tutors, yet current evaluation paradigms assess problem-solving accuracy and generic safety i

Local Ai

Safety-Filtered Distributed Koopman-MPC

arXiv:2609.27463v1 Announce Type: new Abstract: Distributed model predictive control (DMPC) often constructs both predictions and collision constraints from neighbor trajectories, so packet loss can r

local-aiarxiv-cs-ro

Safety Nudges: User-Facing Interventions for Real-Time AI Risk Awareness

arXiv:2609.26865v1 Announce Type: cross Abstract: Conversational AI systems can pose safety risks to their users such as hallucination, sycophancy, overconfidence, and anthropomorphism, but these risk

Same evidence, different judgments: Evidence noncommutative in vision/speech-text conflicts

arXiv:2609.26986v1 Announce Type: new Abstract: For multimodal large language models, when images or speech conflict with accompanying text, measured text reliance can entangle modality preference wit

Same Scores, Different Decisions: Evaluating JEV and Language Models for Legal Document Understanding

arXiv:2609.27678v1 Announce Type: new Abstract: Contract inference requires multiple judgments about a shared document, but aggregate accuracy can conceal changes in the individual decisions. Repeated

Same Stories, Different Journeys: Exploring Persona-Grounded Conversational Agents for Supporting Career Exploration with Peers' Posts

arXiv:2607.11039v2 Announce Type: replace-cross Abstract: Young job seekers frequently explore their career possibilities by browsing peers' posts that share job-seeking experiences. However, static b

Applications

SatUnreal: A High-Precision Synthetic Dataset for Satellite Stereo Matching via Unreal Engine

arXiv:2609.27442v1 Announce Type: new Abstract: 3D reconstruction from satellite imagery is essential for large-scale topographic analysis, yet the lack of high-fidelity training datasets with accurat

applicationsarxiv-cs-cv

Hardware

Scalable Subgraph Sampling via Resistance Curvature

arXiv:2609.27209v1 Announce Type: cross Abstract: Subgraph sampling reduces the training cost of large-scale graph neural networks, but sampling criteria may overlook the geometric roles of edges. We

hardwarearxiv-cs-ai

Scaling Attention Head Analysis via Gradient-Based Attribution in Context-Aware Machine Translation

arXiv:2609.28117v1 Announce Type: cross Abstract: In this paper, we introduce a gradient-based head attribution strategy where the Token-level Max-Margin loss is backpropagated to the attention maps.

Scaling of Capability and Efficiency at Inference Time in Large Reasoning Models

model-releasesarxiv-cs-lg

arXiv:2609.27166v1 Announce Type: new Abstract: Capability and efficiency are two key dimensions of reasoning in large language models (LLMs). Capability refers to the ability to solve a given problem

Schrodinger's Code Repository: Have LLMs Learned SWE-bench or Memorized It?

arXiv:2609.27891v1 Announce Type: cross Abstract: Repository-level coding benchmarks have become the standard for evaluating coding agents, yet they inherently suffer from data leakage because they ar

ScoutNeRV: Rapid Encoding of Grid-Based Video INRs via ScoutNet

arXiv:2609.27958v1 Announce Type: new Abstract: Implicit neural representations (INRs) have emerged as a promising paradigm for video compression, providing compact neural representations with flexibl

researcharxiv-cs-cv

Self-Evolving Multimedia Verification through Memory Consolidation of Contestation Experiences

model-releasesarxiv-cs-ai

arXiv:2609.27175v1 Announce Type: cross Abstract: Multimedia verification requires not only accurate decisions but also traceable evidence, reliable human correction, and safe reuse of prior experienc

Self-Improvement as Coherence Optimization: A Theoretical Account

arXiv:2601.13566v2 Announce Type: replace-cross Abstract: Can language models improve their accuracy without external supervision? Methods such as debate, bootstrap, and internal coherence maximizatio

Semantic-Guided Fusion Network for Multi-Source Remote Sensing Image Classification

arXiv:2609.27854v1 Announce Type: cross Abstract: Multi-source remote sensing image classification has attracted increasing attention due to the complementary spectral, structural, and geometric infor

researcharxiv-cs-cv

SGDet3D++: Geometry-Grounded Semantics for 4D Radar and Camera 3D Object Detection

model-releasesarxiv-cs-cv

arXiv:2609.27671v1 Announce Type: new Abstract: 4D radar complements dense image semantics with long-range geometry and radial motion, but existing radar--camera detectors largely solve where to align

Shared Global KV with Layer-Specific Local History

arXiv:2609.28006v1 Announce Type: new Abstract: Decoder-only Transformer language models cache keys and values (KV) to reuse past computation during generation. Sharing KV across layers saves storage

Sharp Convergence of Wasserstein Gradient Flows for Spectrally Nonnegative Interaction Energies

arXiv:2609.27008v1 Announce Type: cross Abstract: We study the long-time behavior of Wasserstein gradient flows for interaction energies [ mathsf E[mu] = frac12iint_{Mimes M}K(x,y),mathrm dmu(x),mathr

Shopping by algorithm: How agentic AI deploys human heuristics as a surrogate consumer

arXiv:2609.28372v1 Announce Type: cross Abstract: Consumers increasingly delegate purchasing decisions to Large Language Models (LLMs) acting as surrogate consumers. Using 'Tool-Lab,' an adaptation of

SHRAV: State-Hypothesis-Reason-Action-Verify Framework for Physical Modeling and Inverse Design

arXiv:2609.27621v1 Announce Type: new Abstract: Physical modeling and inverse design require computation that can continue from reusable state. We introduce SHRAV, an architecture-independent computat

Shutdown Sabotage Propensities in Multi-Agent Systems

arXiv:2609.28274v1 Announce Type: new Abstract: The final safeguard against rogue AI behavior is the human ability to shut systems down. It has been theorized that when an AI is instructed to perform

Signal2Symbol: Neuro-Symbolic Temporal Reasoning for Explainable Physiological Time-Series Anomaly Detection

arXiv:2609.26820v1 Announce Type: cross Abstract: Physiological time series such as electrocardiograms (ECG) and electroencephalograms (EEG) exhibit complex temporal structure, substantial acquisition

Silent Failures in Agent-Tool Interaction: An Audit of ToolUniverse

arXiv:2609.26836v1 Announce Type: new Abstract: Agentic AI systems are increasingly adopting automated pipelines that integrate multiple tools. While prior research and benchmarks have studied about t

Simultaneous Latent Budget Trees for Stratified Classification

arXiv:2606.13295v3 Announce Type: replace-cross Abstract: In the era of Explainable Artificial Intelligence, there is a renewed focus on single trees for their ease of interpretation. This paper intro

Six Layers Less: Encoder Pruning for Whisper with Label-Free Recovery

arXiv:2609.27980v1 Announce Type: new Abstract: Pruning large pre-trained transformer-based ASR models such as OpenAI's Whisper has seen great adoption, as pruning the decoder led to significant end-t

researcharxiv-cs-cl

SkillGym: Internalizing Human Skills into LLMs for Real-World Problem Solving

arXiv:2609.27717v1 Announce Type: new Abstract: Human-written agent skills encode rich workflows for real-world problem solving, but are typically used as external inference-time instructions rather t

SlackDrive: Reclaiming Runtime Slack for Adaptive Driving Inference

arXiv:2609.28064v1 Announce Type: new Abstract: Driving world-action models improve planning by coupling multimodal reasoning with future prediction, but their growing inference cost increasingly conf

Small Cues, Big Consequences: Learning Pivotal Cues for Multimodal Meme Classification

arXiv:2609.26907v1 Announce Type: cross Abstract: Memes often derive their harmful, hateful, or sarcastic meaning from small but decisive visual, textual, or cross-modal cues. Existing multimodal clas

SMDDFNet: State-space Modeling and Dynamic Dual Fusion Network for Traffic Sign Detection

arXiv:2505.05491v2 Announce Type: replace-cross Abstract: Traffic sign detection is a challenging visual signal processing task for advanced driver assistance, where small objects, scale variation, an

Softmax gradient policy for variance minimization and risk-averse multi armed bandits

arXiv:2604.00241v2 Announce Type: replace-cross Abstract: Algorithms for the Multi-Armed Bandit (MAB) problem play a central role in sequential decision-making and have been extensively explored both

SoLiD26: A First Principles Solid-Liquid Interface Dataset for Machine-learned Interatomic Potentials

arXiv:2609.28013v1 Announce Type: cross Abstract: Machine-learned interatomic potentials (MLIPs) for solid-liquid interfaces in advanced materials applications, e.g., electrochemistry, catalysis and c

Sparse-Observation Atmospheric Thermal Forecasting with Physics-Informed Neural Networks for Climate-Aware Digital Twins

arXiv:2609.27290v1 Announce Type: new Abstract: Short-horizon forecasts of atmospheric temperature are needed to support climate-aware digital-twin systems, but such forecasts must be produced where t

Spatial and Semantic Reasoning for LLM-Driven Robot Navigation via MCP

arXiv:2609.27340v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as natural-language interfaces for robotic systems, yet their integration with Robot Operating System

agentsarxiv-cs-ro

Spatiality-Frequency Domain Video Forgery Detection System Based on ResNet-LSTM-CBAM and DCT Hybrid Network

model-releasesarxiv-cs-cv

arXiv:2609.27904v1 Announce Type: new Abstract: As information technology advances, digital content has become widely adopted across diverse fields such as news broadcasting, entertainment, commerce,

Spec2COBOLRot: An Agentic-AI Degradation Loop for Realistic COBOL Corpus Generation

arXiv:2609.26835v1 Announce Type: cross Abstract: COBOL remains widely deployed, yet representative corpora reflecting real production code are rarely available, limiting rigorous benchmarking of mode

Spiderbot: An Open-Source Energy-Efficient Hexapod with Passive Gravity Compensation

arXiv:2609.26989v1 Announce Type: new Abstract: Hexapod robots can achieve static stability with fewer actuated joints than bipeds or quadrupeds, yet many platforms still use 3-DOF legs, increasing we

safetyarxiv-cs-ro

Spread and Scale: What Determines Whether Test-Time Budget Allocation Pays

arXiv:2609.27917v1 Announce Type: cross Abstract: Neural combinatorial optimization solvers generate many candidate solutions per instance and report the best one found, using the same sample budget f

SR-Fraud: An Outcome-Supervised Reflective LLM Agent Framework for Non-Stationary Payment Fraud Detection

model-releasesarxiv-cs-lg

arXiv:2609.27287v1 Announce Type: new Abstract: Real-time payment fraud detection is a non-stationary streaming prediction problem: adversaries adapt before supervised labels mature, and localized bur

SsgCaps: A controlled dataset for the evaluation of sound scene generation algorithms

arXiv:2609.26854v1 Announce Type: cross Abstract: Sound Scene Generation is about the automatic synthesis of artificial sound scenes. We introduce SsgCaps, a publicly available dataset of human-engine

Stable Geometry with Divergent Task Evidence for Efficient Long-Horizon Agent Compression

arXiv:2609.27332v1 Announce Type: new Abstract: Long horizon agents accumulate growing interaction histories that increase context and inference costs. We find that geometric redundancy alone is an in

Stable Neural Decoding Across Sessions via Task-Conditioned Latent Alignment for Brain-Machine Interfaces

arXiv:2609.27441v1 Announce Type: new Abstract: Achieving stable long-term neural decoding in invasive brain-machine interfaces (BMIs) remains challenging due to variations in recorded neural populati

safetyarxiv-cs-lg

Starter-Iterator Neural Operator: A Unified Architecture for High-Fidelity Forward and Inverse PDE Problems

model-releasesarxiv-cs-lg

arXiv:2606.18305v2 Announce Type: replace-cross Abstract: Operator learning is an emerging field at the intersection of machine learning and scientific computing. By learning mappings between function

State-Grounded Conditioning: Wrapping User-Facing LLM Agents Where Direction Depends on Live State

model-releasesarxiv-cs-ai

arXiv:2609.27606v1 Announce Type: new Abstract: We introduce State-Grounded Conditioning (SGC), a design principle for user-facing LLM agents that must condition on live user state (game state, sessio

StateComp: Learning When to Compress History in Long Horizon Agents

arXiv:2609.27298v1 Announce Type: new Abstract: Long-horizon agents continuously accumulate interaction history during task execution, yet the importance of past interactions changes as the agent stat