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arXiv:2609.24130v1 Announce Type: new Abstract: LLM agents can change their own future behavior, raising a basic control question of which self-generated changes should be allowed to persist. We formu

local-aiarxiv-cs-ai

Self-Organizing Agent Teams Learn to Reason Together

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DGX agent

arXiv:2609.22682v1 Announce Type: new Abstract: Collective intelligence depends not only on what team members know, but also on how they organize their work. When the structure of a solution is unknow

agentsarxiv-cs-ai

23 Sept 2026

Self-Supervised Combinatorial Optimization with Constraints via Frank-Wolfe

arXiv:2609.25728v1 Announce Type: new Abstract: Self-supervised learning for combinatorial optimization has emerged as a promising paradigm for solving discrete optimization problems with neural netwo

SelfOp: An Optimization Algorithm for Self-Improving Security Agents

model-releasesarxiv-cs-ai

arXiv:2609.22792v1 Announce Type: cross Abstract: LLM agents are increasingly used for security tasks: vulnerability discovery, exploit reproduction, and patch generation. Improving them at the model

Semantic Abstraction for Natural Language Inference: a Methodological Framework for Discovering and Compensating Semantic Knowledge and Reasoning Gaps in Large Language Models

arXiv:2609.26610v1 Announce Type: new Abstract: Despite their outstanding performance on many NLP tasks, LLMs face serious challenges related to semantic abstraction. In this study, we are interested

Semantic-Anchored Evidential Fusion for Domain-Robust Whole-Slide Survival Analysis

arXiv:2606.19966v2 Announce Type: replace-cross Abstract: Whole-slide images (WSIs) are widely used for computational cancer prognosis. However, most existing methods primarily focus on in-domain perf

Semantic Candidate-Job Matching: A Comparative Evaluation of Dense Embedding Models in Hybrid Retrieval

model-releasesarxiv-cs-ai

arXiv:2609.23307v1 Announce Type: cross Abstract: This paper presents a comparative evaluation of dense embedding models for semantic candidate-job matching in high-volume staffing workflows. Incoming

Semantic Self-Distillation for Language Model Uncertainty

arXiv:2602.04577v3 Announce Type: replace Abstract: Large language models present challenges for principled uncertainty quantification, in part due to their complexity and the diversity of their outpu

Semantically-Guided Domain Randomization for Industrial Object Detection in Low-Image-Budget Regimes

model-releasesarxiv-cs-cv

arXiv:2609.26505v1 Announce Type: new Abstract: Retraining visual perception pipelines in High-Mix, Low-Volume (HMLV) automotive manufacturing must be carried out under tight annotation, energy, and t

SemDHT: Certified Semantic Discovery for Peer-to-Peer Agent Networks over Exact-Key DHTs

arXiv:2609.23539v1 Announce Type: cross Abstract: Agents may need capabilities exposed through external agent endpoints or service APIs. When a requester is not already bound to a provider, it must di

agentsarxiv-cs-ai

Separators in Enhancing Autoregressive Pretraining for Vision Mamba

arXiv:2603.03806v2 Announce Type: replace Abstract: The state space model Mamba has recently emerged as a promising paradigm in computer vision, attracting considerable attention for its efficient han

researcharxiv-cs-cv

Sex Estimation from Footwear Outsole Impressions Using CNN Transfer Learning and Interpretable Image Statistics

arXiv:2609.25386v1 Announce Type: cross Abstract: Footwear outsole impressions are a common form of forensic pattern evidence, yet quantitative methods for estimating wearer attributes from these imag

SG-CPG: Severity-Gated Central Pattern Generators for Adaptive Quadruped Locomotion under Continuous Actuator Degradation

arXiv:2609.25687v1 Announce Type: new Abstract: An animal with a weakened limb does not necessarily switch its gait, instead it unloads the affected limb, re-coordinates the remaining limbs, and scale

Shaft-Configuration-Adaptive Catheter Tip Position Estimation via Motor-History Conditioned Residual Learning

arXiv:2609.26304v1 Announce Type: new Abstract: Tendon-driven continuum manipulators are widely used in medical applications, where accurate tip-position estimation is essential for precise navigation

researcharxiv-cs-ro

Shallow to Deep: Aligning Token Pruning with Stage-wise Roles in LVLMs

model-releasesarxiv-cs-cv

arXiv:2609.25635v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) incur high computational costs from redundant visual tokens. Although training-free attention-based multi-layer pru

Sharp First-Order Lower Bounds for Higher-Order Smooth Nonconvex Optimization

arXiv:2606.05438v2 Announce Type: replace Abstract: We study the deterministic first-order oracle complexity of finding (epsilon)-stationary points in smooth nonconvex optimization when the objective

Signed Graph Pre-Training and Prompt Learning

arXiv:2609.25722v1 Announce Type: new Abstract: Signed graphs arise in trust--distrust networks, financial correlation systems, biological interaction graphs, and many other domains in which edges can

applicationsarxiv-cs-lg

Silent Sabotage: Internal State Triggered Backdoor Attacks on LLM-Powered Robotic Systems

arXiv:2609.26184v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) into robotic control systems is enabling a new generation of autonomous agents capable of complex reason

agentsarxiv-cs-ro

Tutorials

Simulation-free Structure Learning for Stochastic Population Dynamics

arXiv:2510.16656v2 Announce Type: replace Abstract: Modeling dynamical systems and unraveling their underlying structural dependencies is central to many domains in the natural sciences. Various physi

tutorialsarxiv-cs-lg

Situation Aware Locomotion for Dual Mobile Cobots in Shared Environments

arXiv:2609.26083v1 Announce Type: new Abstract: This paper presents a situation aware locomotion framework for two mobile collaborative robots operating in shared industrial environments. The proposed

Skill Sequence Planning for Collaborative Multi-Robot Construction

arXiv:2609.25649v1 Announce Type: new Abstract: Robots have significant potential to automate construction processes. However, their industry adoption remains limited, partly because of the programmin

applicationsarxiv-cs-ro

Skytopia: Monocular Drone Navigation with Action-Conditioned Latent World Models

arXiv:2609.26007v1 Announce Type: new Abstract: Monocular drone navigation requires reaching a goal in an unseen environment from a single forward-facing camera, which offers few cues for depth and sc

Slow Decay and Silenced Expression: Iterated Subliminal Trait Transfer in Language-Model Lineages

arXiv:2609.25721v1 Announce Type: cross Abstract: Language models are increasingly trained on the outputs of other models, forming chains that we call lineages, in which a trait present in one generat

Small-world Networks of Agents Brainstorm AI Risks to Support Ideation

arXiv:2609.24859v1 Announce Type: cross Abstract: The ideation phase of participatory AI risk assessment often starts with a blank slate or a limited list of predefined risks, making it difficult to s

agentsarxiv-cs-ai

Smoothed Analysis of Inconsistent A*

arXiv:2609.23680v1 Announce Type: cross Abstract: The A* search is a fundamental path-finding algorithm in artificial intelligence. While admissible and consistent heuristics guarantee efficient perfo

applicationsarxiv-cs-ai

Social Influence and the Allocation of Scientific Attention in AI Populations

arXiv:2609.22408v1 Announce Type: new Abstract: AI systems are becoming participants in the evaluation and use of scientific research. They encounter citation counts, download statistics and lists of

agentsarxiv-cs-ai

Sometimes You Gotta Run Before You Can Walk: Run-then-Walk Scheduling Strategy for VLM Autonomous Driving

arXiv:2609.25831v1 Announce Type: new Abstract: Recent VLM-based autonomous driving planners adopt GRPO-style reinforcement learning to optimize driving performance. However, existing GRPO recipes eit

Sonicmesh: Enhancing 3D Human Mesh Reconstruction in Vision-Impaired Environments With Acoustic Signals

arXiv:2412.11325v2 Announce Type: replace Abstract: 3D human mesh reconstruction (HMR) from RGB images often degrades under poor illumination, occlusion, and non-line-of-sight conditions. Acoustic sen

researcharxiv-cs-cv

SPARC: SuperPixel-Aware Region Contrastive Learning for Self-Supervised Dense Prediction

arXiv:2609.25067v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has become an effective approach for learning visual representations without manual annotations. Among SSL approaches,

SparseNav: Instruction-conditioned Sparse Semantic Perception for Training-Free Vision-Language Navigation

arXiv:2609.26408v1 Announce Type: new Abstract: Map-based vision-language navigation (VLN) relies on persistent spatial representations to connect language understanding with geometric planning. Howev

researcharxiv-cs-ro

Spatiotemporal Calibration of Doppler Velocity Logs for Underwater Robots

arXiv:2510.24571v2 Announce Type: replace Abstract: The calibration of extrinsic parameters and clock offsets between sensors for high-accuracy performance in underwater SLAM systems remains insuffici

applicationsarxiv-cs-ro

Spatiotemporal Kronecker Covariance Neural Networks

arXiv:2609.25326v1 Announce Type: new Abstract: Multivariate time series contain complex patterns that span across both space and time. While covariance-based statistical tools like spatiotemporal Pri

applicationsarxiv-cs-lg

Local Ai

SpeakerMem-R1: Speaker-Centered Dual-Track Memory for Multi-Party Dialogue

arXiv:2609.26780v1 Announce Type: new Abstract: Long-term conversational memory in multi-party settings requires more than retrieving relevant content from long-term conversations: it must distinguish

local-aiarxiv-cs-cl

SPEANet: Structural Prior Enhanced Attention Network for Parameter-Efficient Remote Sensing Object Detection

model-releasesarxiv-cs-cv

arXiv:2609.26064v1 Announce Type: new Abstract: Remote sensing object detection (RSOD) requires compact backbones capable of preserving weak geometric cues under extreme scale variation and background

SpecialEduBench: Benchmarking Vision-Language Models on Knowledge, Skill, and Attitude in Language Intervention for Autistic Children

model-releasesarxiv-cs-cl

arXiv:2609.26090v1 Announce Type: new Abstract: Language is the target of most early intervention for autistic children. Because the goal and the method change from child to child, the work falls to a

SPECTRA: Adaptive Execution of Speculative Decoding on a Runtime-Reconfigurable Tiled Architecture

arXiv:2609.24847v1 Announce Type: cross Abstract: LLM inference on edge devices is constrained by computational and memory resources, making efficient autoregressive decoding challenging. Speculative

researcharxiv-cs-ai

Spectral Overfitting in Noisy Linear Probing of Pretrained Representations

arXiv:2603.02293v3 Announce Type: replace Abstract: Frozen pretrained features are often treated as a safe interface for downstream learning: only a small linear readout is trained, while the backbone

Spectral Tail Interventions in Decoder-Only Language Models: Reasoning-Sensitive Weight Structure from Controlled Surgery

arXiv:2609.26165v1 Announce Type: new Abstract: Weight-space structure often correlates with language-model behavior, but correlation alone does not establish computational involvement. We study conce

Splitting Documents at Lower Cost: Multi-Split Boundary Decisions for LLM-Based Page Stream Segmentation

arXiv:2609.22620v1 Announce Type: new Abstract: Scanned mail, uploaded PDFs, and consolidated attachments often arrive as page streams that must be split into individual documents before downstream cl

researcharxiv-cs-ai

Spoken Language Models that Think Aloud

arXiv:2609.26488v1 Announce Type: new Abstract: While Chain-of-Thought (CoT) reasoning has improved the capability of language models, directly applying it to Spoken Language Models (SLMs) may introdu

SSP-Bench: A Hybrid Data Generation Framework for Safety, Security, and Privacy Evaluation

model-releasesarxiv-cs-lg

arXiv:2609.25352v1 Announce Type: cross Abstract: Evaluation of large language models (LLMs) for safety, security, and privacy (SSP) relies heavily on static benchmarks, which suffer from score satura

Stable Unsupervised Continual Chunking with Sheaf SyncMap

arXiv:2609.25143v1 Announce Type: new Abstract: Unsupervised Continual chunking is a fundamental problem in machine learning and neuroscience, where the goal is to identify groups of states that frequ

StableVQ: Practical Guidelines for Stable Vector-Quantized Tokenizer Training

arXiv:2609.26774v1 Announce Type: new Abstract: Vector Quantization (VQ) is fundamental to discrete visual tokenizers that power modern autoregressive and masked image generation models. While recent

researcharxiv-cs-cv

STAR-VAE: A Scalable Latent-Variable Transformer for Controllable Molecular Generation

arXiv:2511.02769v2 Announce Type: replace Abstract: Many molecular Transformers lack probabilistic latent variables for posterior inference and latent interpolation. We introduce STAR-VAE, a SELFIES-e

Statistical Gains from Looped Estimation under Parameter Budgets

model-releasesarxiv-cs-lg

arXiv:2609.25778v1 Announce Type: cross Abstract: Growing memory demands in artificial intelligence motivate learning with fewer trainable parameters. We ask whether a looped estimator, which repeated

Statistical Rates for Entropic Optimal Transport in the Discrete to SubGaussian Regime

arXiv:2609.26647v1 Announce Type: cross Abstract: We study statistical rates in entropic optimal transport in the semi-discrete regime where one measure has finite support and the other is subGaussian

StepTrigger: Contact-State-Triggered Backdoor Attacks on VLM-Powered Legged Robots

arXiv:2609.26131v1 Announce Type: new Abstract: Large language models and vision-language models are increasingly used as high-level planners in robotic systems, using task goals and sensor summaries

StrataVLA: Hierarchical and Efficient 3D Geometric Grounding for Vision-Language-Action Models

arXiv:2609.26071v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models inherit strong semantic priors from large-scale vision-language pretraining, yet remain limited in robotic manipulat

applicationsarxiv-cs-ro