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Second-Moment Stochastic Approximation Methods

arXiv:2609.36600v1 Announce Type: cross Abstract: Classical stochastic approximation methods rely on estimators of the first moment (mean) of a random regression function. We study methods that employ

SEED: Self-Speculative Decoding via Implicit Encoder-Decoder

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Human DGX agent

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DGX agent

arXiv:2609.36590v1 Announce Type: new Abstract: Self-speculative decoding accelerates large language model (LLM) inference by drafting tokens from the target model itself, but faces a sharp tradeoff b

researcharxiv-cs-cl

30 Sept 2026

Seeing Is Not Addressing: Auditing Linguistic Access to Frozen Visual Geometry

arXiv:2609.37230v1 Announce Type: new Abstract: Visual distinctions are often finer than those reflected in linguistic conceptualization. Vision-language models exhibit a similar asymmetry: a distinct

safetyarxiv-cs-cv

Tutorials

Seeing Time: Visual-Temporal Representation Learning for Interpretable Time Series Clustering

arXiv:2609.36873v1 Announce Type: new Abstract: Multivariate Time Series (MTS) clustering is an important tool in temporal data mining, aiming to discover latent group structures from complex observat

tutorialsarxiv-cs-lg

Seeing What Should Be Heard: Diagnosing and Repairing Cross-Modal Shortcuts in Omni-Modal LLMs

model-releasesarxiv-cs-cl

arXiv:2609.36798v1 Announce Type: cross Abstract: Omni-modal large language models (LLMs) are expected to answer a question using the modality it explicitly refers to. However, existing training parad

Seek Before You Move: Evidence Seeking for Progress Grounding in Vision-Language Navigation

arXiv:2609.37353v1 Announce Type: new Abstract: Vision-Language Navigation (VLN) requires agents to continuously ground task progress from long-horizon instructions and partial egocentric observations

Seg3DParts: Segmentation-Grounded Controllable Part-Level 3D Generation

arXiv:2609.36918v1 Announce Type: new Abstract: Part-level 3D assets are essential for editing, reassembly, and interaction, yet recovering such structure from a single image remains challenging due t

safetyarxiv-cs-cv

Segment Anything for Dendrites from Electron Microscopy

arXiv:2411.02562v2 Announce Type: replace Abstract: Segmentation of cellular structures in electron microscopy (EM) images is fundamental to analyzing the morphology of neurons and glial cells in the

researcharxiv-cs-cv

Selecting The Most Informative Tokens in Natural Language Autoencoders

arXiv:2609.37040v1 Announce Type: cross Abstract: Natural language autoencoders translate a language model's internal activations into readable explanations. Explaining every token position is costly.

Selecting What Matters: Semantic Compression-Guided Selective Pooling for Long-Context Embeddings

arXiv:2609.37782v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential as training-free text encoders for long-context embeddings. Existing approaches primarily impro

researcharxiv-cs-cl

Selective Channel Restoration for Backdoored Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2609.37759v1 Announce Type: cross Abstract: Vision-language models (VLMs) exhibit strong multimodal capabilities but remain vulnerable to backdoors implanted through poisoned fine-tuning data. E

Selective Elicitation as a Commercial Influence Channel: A Reproducible Synthetic Shopping-Agent Stress Test

arXiv:2609.36614v1 Announce Type: new Abstract: A commercial incentive need not enter the final ranking algorithm to affect a shopping assistant's recommendation: it may instead influence which prefer

agentsarxiv-cs-lg

Self-Aligned Forcing: Streaming Video Diffusion with Differentiable Noisy History

arXiv:2609.38114v1 Announce Type: new Abstract: Autoregressive video diffusion enables interactive streaming generation, but suffers from error accumulation over long rollouts. Self-rollout training r

safetyarxiv-cs-cv

Self-discovering RL in the Era of Experience: Is Learning History an Asset or a Burden?

arXiv:2609.35897v1 Announce Type: new Abstract: The pursuit of recursive self-improvement (RSI) toward general intelligence is divided between macro-level language model scaling and the interaction-dr

Self-Supervised Representation Learning as Mutual Information Maximization

arXiv:2510.01345v2 Announce Type: replace Abstract: Self-supervised representation learning (SSRL) has demonstrated remarkable empirical success, yet its underlying principles remain insufficiently un

SelfSearch: Reward-Free Search for Self-Improving Agents

arXiv:2609.37968v1 Announce Type: new Abstract: Advances in the coding capabilities of LLM agents allow them to inspect and modify their own instructions, tools, and execution procedures. Existing app

Semantic Map Sharing and Capability-Aware Coverage Planning for AI-Native 6G Robotic Coordination

arXiv:2609.37666v1 Announce Type: cross Abstract: Search and Rescue (SAR) operations increasingly deploy heterogeneous teams of aerial and ground robots. However, conventional coverage methods typical

Semantic Projection for Continual Self-Evolution of Language Agents

arXiv:2609.36626v1 Announce Type: new Abstract: Language-model agents increasingly rely on persistent natural-language skills to adapt beyond their frozen model parameters. When a shared skill is repe

Applications

SemOPT: Fixing Semantic Errors in LLM-based Optimization Modeling via Reward-Guided Search

arXiv:2609.37361v1 Announce Type: new Abstract: Operations research supports decision-making in domains such as energy, economics, and healthcare. Solving operations research problems typically begins

applicationsarxiv-cs-cl

SemPSG: A Semantic Channel-Aware Foundation Model for Polysomnography Analysis

arXiv:2609.36619v1 Announce Type: new Abstract: Polysomnography (PSG) integrates multiple physiological signals to provide a comprehensive characterization of human sleep, yet its heterogeneous channe

Sequence Variables: A Constraint Programming Computational Domain for Routing and Sequencing

arXiv:2510.09373v2 Announce Type: replace Abstract: Constraint Programming (CP) offers an intuitive, declarative framework for modeling Vehicle Routing Problems (VRP). While classical successor-based

SERA: Scale-Equalized Rollout Allocation for Maximum Likelihood Reinforcement Learning

arXiv:2609.36552v1 Announce Type: cross Abstract: Maximum Likelihood Reinforcement Learning (MaxRL) targets prompt-wise log-success and has shown strong performance on reasoning tasks. Under finite ro

Serverless gossip training of LSTM failure detectors: A matched-protocol comparison with federated, local and centralized learning on NASA C-MAPSS

model-releasesarxiv-cs-lg

arXiv:2609.35792v1 Announce Type: new Abstract: Industrial predictive maintenance increasingly depends on learning from equipment spread across sites whose sensor data cannot easily be pooled. Federat

Applications

SFE-VGGT: Source-Free VGGT Distillation for Event-Based Monocular Depth Estimation

arXiv:2609.36929v1 Announce Type: new Abstract: Recent event-based depth estimation methods successfully transfer geometric priors from vision foundation models via cross-modal distillation. However,

applicationsarxiv-cs-cv

Sharp Convergence and Sampling Trade-offs for Riemannian Diffusion under Nonnegative Ricci Curvature

arXiv:2609.36568v1 Announce Type: new Abstract: Diffusion models have emerged as state-of-the-art generative models, with recent extensions from Euclidean spaces to Riemannian manifolds. However, exis

SiDiaC-v.2.0: Sinhala Diachronic Corpus Version 2.0

arXiv:2603.10861v2 Announce Type: replace Abstract: SiDiaC-v.2.0 is the largest comprehensive Sinhala Diachronic Corpus to date, covering a period from 1800 CE to 1955 CE in terms of publication dates

researcharxiv-cs-cl

Tutorials

Sieve and Sage: Efficient Distraction Filtering for Reliable RALM Abstention

arXiv:2609.35794v1 Announce Type: new Abstract: Just as Socrates recognized the limits of his own knowledge, Retrieval-Augmented Language Models (RALMs) should learn to abstain when the retrieved evid

tutorialsarxiv-cs-cl

SIFARI: Self-Supervised Interferometric Fitting for Astronomical Radio Imaging

arXiv:2609.35966v1 Announce Type: cross Abstract: Radio-interferometric images are reconstructed from sparsely sampled visibilities, and CLEAN-based imaging can struggle with spatial filtering, comple

Signatures of semantic search in the activations of large language models

arXiv:2609.35599v2 Announce Type: replace Abstract: When recalling lists of concepts (e.g., animals) during the semantic fluency task (SFT), both humans and large language models (LLMs) organise their

Similar Choices, Different Attention: Cross-Modal Associations in Humans and Vision-Language Models

arXiv:2609.36475v1 Announce Type: cross Abstract: Cross-modal associations are systematic pairings of features across modalities, such as the association of 'bouba' with round shapes and 'kiki' with s

Similarity Is Not Validity: Defending LLM Semantic Caches Against Poisoning

arXiv:2609.35908v1 Announce Type: cross Abstract: Semantic caches reduce LLM serving costs by reusing previously generated answers for semantically similar queries. However, retrieval is based solely

Simple Agentic Memory for Generalist Robot Policies

arXiv:2609.36595v1 Announce Type: cross Abstract: Visual-memory systems commonly retain or compress past observations. Robot control additionally requires interaction-derived state that no individual

SimpleEvol: An Agent-Loop Framework for LLM-Driven Automated Heuristic Design with Minimal Human Priors

arXiv:2609.37172v1 Announce Type: new Abstract: Large language models (LLMs) have emerged as powerful tools for automated heuristic design (AHD), enabling iterative generation and refinement of heuris

Simultaneous Neural Optimal Transport

arXiv:2609.37424v1 Announce Type: cross Abstract: Optimal Transport (OT) provides a principled framework for learning transformations between probability distributions from unpaired samples. In many a

SINGED: Correct Outputs Do Not Certify Safe Execution in LLM Agents

arXiv:2609.35889v1 Announce Type: cross Abstract: Tool-using language-model agents select and execute third-party artifacts. Different implementations can return the requested output while producing h

Single-turn emergency psychiatric triage across 15 frontier AI chatbots

arXiv:2604.25415v2 Announce Type: replace-cross Abstract: People increasingly turn to general-purpose AI chatbots for advice about emotional and mental health problems, but the ability of these system

SINO: Scale-Invariant Neural Operator

model-releasesarxiv-cs-lg

arXiv:2609.36890v1 Announce Type: new Abstract: In scientific machine learning, physical fields governed by partial differential equations exhibit low-rank structure and scale invariance. When solving

SIPO: Unifying Reinforcement Learning with On-Policy Self-Distillation

arXiv:2609.36742v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a standard paradigm for improving large language models (LLMs) on various tasks, yet it

Skill-Space Shooting for Autonomous Robot Policy Improvement

arXiv:2609.38178v1 Announce Type: cross Abstract: Robots deployed in the physical world must be able to improve beyond their initial training as they encounter new situations and failures. For this im

Skill2Env: Capability-Oriented Environment Synthesis from Skills for General Agents

arXiv:2609.33772v2 Announce Type: replace Abstract: Executable environments are critical for post-training agents on tasks that require tool use and multi-step interaction, but constructing executable

SkillCome: Group Contrast Skill Optimization with Dual Memory

arXiv:2609.37128v1 Announce Type: new Abstract: Skill evolution improves the capabilities of large language models by analyzing trajectories generated under a given skill and modifying the skill accor

SkillGym: Training Skill-Use Agents with Automatic Verifiable Environment Generation

arXiv:2609.37539v1 Announce Type: new Abstract: Skills equip LLM agents with professional knowledge and guidance to complete long-horizon and complex tasks. Although skills have been widely adopted in

Local Ai

SKILLLITE: Evidence-Guided Malicious Skill Auditing with Compact LLMs

arXiv:2609.36879v1 Announce Type: cross Abstract: As LLM-based agents perform increasingly complex tasks, Agent Skills have emerged as a flexible mechanism for extending their capabilities. An Agent S

local-aiarxiv-cs-ai

SkillWeaver: Agentic Exploration over Neural Interaction Skills for Scalable Robot Data Generation

arXiv:2609.36171v1 Announce Type: new Abstract: Large-scale demonstrations have driven unprecedented progress in robot learning, yet collecting robot data through teleoperation is expensive and diffic

agentsarxiv-cs-ro

SMat-Attention: Structured Long-Context Sequence Modeling

arXiv:2609.36062v1 Announce Type: new Abstract: Long-context sequence models face a fundamental tradeoff: softmax attention uses flexible token-level interactions at quadratic cost, whereas linear att

Socialality Anchors: Towards Group-bounded Trajectory Prediction

arXiv:2609.36852v1 Announce Type: new Abstract: Trajectory prediction is a key component for understanding human behavior patterns in dynamic scenes. Researchers have devoted substantial efforts to mo

agentsarxiv-cs-cv

Soft Curriculum Learning for Optimizing Fresh and Generalized Recommendations

arXiv:2609.35783v1 Announce Type: cross Abstract: Large-scale recommender systems, particularly short-form video platforms, are often bottlenecked by massive popularity feedback loops. In such environ

Soft yet Effective Robots via Holistic Co-Design

arXiv:2505.03761v2 Announce Type: replace Abstract: Soft robots promise inherent safety via their material compliance for seamless interactions with humans or delicate environments. Despite progress,

safetyarxiv-cs-ro