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Rule-Based Languages for Neurosymbolic AI

arXiv:2610.07313v1 Announce Type: new Abstract: Logic programming is increasingly used as the symbolic component of neurosymbolic AI systems. We survey the main rule-based languages in this setting, n

SAE++: Cascaded Sparse Autoencoders Learn Multi-Level Visual Concepts in Multimodal LLMs

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Human DGX agent

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DGX agent

arXiv:2606.16193v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have demonstrated strong performance on vision-language tasks, yet their internal visual representati

model-releasesarxiv-cs-ai

7 Oct 2026

Safe Multi-Robot Collaborative Transport Using Density Functions

arXiv:2610.08441v1 Announce Type: new Abstract: This paper presents a hierarchical density-based model predictive control framework for safe collaborative manipulation by multiple quadrupedal robots.

researcharxiv-cs-ro

Safeguarding LLMs via Model-Agnostic Latent Safety Signals from Dark Knowledge

arXiv:2610.07532v1 Announce Type: cross Abstract: LLMs have advanced rapidly, raising growing concerns about their safety. Recent work has proposed approaches to detect and defend against attacks incl

SAFESHIELD: A Decision-Organization Framework for Deployment-Time Safety of Small Language Models

arXiv:2610.07276v1 Announce Type: cross Abstract: Deployment-time safety of language models is commonly implemented through runtime guardrails such as input moderation, routing, retrieval verification

Local Ai

SAGE: Semantic Anchor-Guided Evolution for Grounded Medical QA Data Synthesis

arXiv:2610.08093v1 Announce Type: cross Abstract: Developing reliable models for clinical tasks, such as Medical Question Answering (QA), is severely constrained by the limited availability of high-qu

local-aiarxiv-cs-ai

SalArt-VQA: Diagnosing Whether VLMs Understand Salient Artifacts in Generated Images

model-releasesarxiv-cs-cv

arXiv:2606.12671v2 Announce Type: replace Abstract: Vision-language models (VLMs) are increasingly used to detect whether AI-generated images contain visible artifacts, yet their ability to analyze su

Same Feedback, Different Answer: Measuring Run-to-Run Instability in Frontier-Model Customer Feedback Analysis

arXiv:2610.08036v1 Announce Type: new Abstract: AI agents are increasingly being programmed to automate knowledge work over large collections of unstructured data. Such automation requires repeatabili

Same-Number Citation Swaps: Stress-Testing Jev as a Financial Evidence Judge

model-releasesarxiv-cs-cl

arXiv:2610.08675v1 Announce Type: new Abstract: Financial reports repeat values across periods, metrics and accounting lines, allowing an LLM-generated calculation to be numerically correct while citi

Sample-Optimal Estimation of the Frechet Inception Distance

arXiv:2610.07114v1 Announce Type: cross Abstract: The Frechet Inception Distance (FID) is widely used to evaluate generative models, but its empirical plug-in estimator suffers from finite-sample bias

safetyarxiv-cs-cv

SanSi: A Looped Typed Decision Model for System 1.5 Thinking

arXiv:2610.07730v1 Announce Type: cross Abstract: Typed decision models answer a declared question without generating text: a decision head returns a probability for each of the declared options in a

SC3BF: Shifted Collision Cone Control Barrier Function for Dynamic Obstacle Avoidance

arXiv:2610.08332v1 Announce Type: new Abstract: The collision cone used by velocity-space control barrier functions is conservative: it rejects every relative velocity aimed into an obstacle, however

safetyarxiv-cs-ro

Applications

Scalable extraction and visualization of multi-attribute logical and functional dependencies in tabular data

arXiv:2610.08287v1 Announce Type: new Abstract: Understanding the structural relationships among attributes in tabular data is fundamental to machine learning and pattern recognition. While functional

applicationsarxiv-cs-lg

Scalable next-scale autoregression for medical image generation across anatomical regions

arXiv:2602.14512v3 Announce Type: replace Abstract: Autoregressive pretraining has been key to the scalability of large language models, yet medical generative foundation models remain predominantly b

researcharxiv-cs-cv

Scale-Invariant Training for Time Series Foundation Models

arXiv:2610.07324v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) are trained on large collections of time series datasets that span various morphologies and domains. This settin

Scaling Laws for Deepfake Detection

arXiv:2510.16320v2 Announce Type: replace Abstract: This paper presents a systematic study of scaling laws for the deepfake detection task. Specifically, we analyze the model performance against the n

researcharxiv-cs-cv

Hardware

ScanSTL: Parallel Robustness Evaluation for Signal Temporal Logic

arXiv:2610.07346v1 Announce Type: new Abstract: Repeated evaluation and differentiation of Signal Temporal Logic (STL) robustness can become a computational bottleneck in robot planning and control. S

hardwarearxiv-cs-ro

Scen-Opt: A Scenario Optimization Toolbox for Data-Driven Convex Programming

arXiv:2610.07846v1 Announce Type: cross Abstract: The scenario approach is a well-established statistical framework for data-driven decision-making. In particular, in data-driven optimization, the sce

SchemaFill: Efficient LLM Tool Calling via Slot-Parallel Speculative Decoding

arXiv:2610.07086v1 Announce Type: cross Abstract: LLM agents interact with external systems by generating structured tool calls. Given a user request, conversational context, and a catalog of tool sch

ScienceClaw: Benchmarking Continual Self-Evolution of AI-for-Science Agents Across the Natural and Social Sciences

arXiv:2610.08691v1 Announce Type: new Abstract: Large language model agents are accelerating scientific automation, yet verified executions rarely become persistent program-level improvements, and exi

SCOPE: Certified Theorem Proving with a Language Model as the Policy Planner

arXiv:2610.08319v1 Announce Type: new Abstract: In proof assistants such as Lean, a generated proof must pass machine compilation checks, so evaluation needs no human scoring. Direct generation fails

SEAL: Mixture-Closed Additive Reconstruction and Refinement-Aware Expert Routing for Efficient Speech Separation

arXiv:2610.07047v1 Announce Type: cross Abstract: Compact time-frequency separators that mask the mixture and refine through a shared cell face two limits. First, a bounded multiplicative mask only sc

researcharxiv-cs-cl

Secure Speculative Decoding for Large Language Models

arXiv:2610.08678v1 Announce Type: cross Abstract: Speculative decoding accelerates inference for a large language model (LLM), referred to as the target model, by first using a smaller model, referred

Seeing the Invisible: Physics-Guided Visual Prompting for Temperature- and Radiation-Aware VLA Navigation

arXiv:2610.07558v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have become a major paradigm for Vision-and-Language Navigation (VLN). However, in safety-critical facilities, inv

Seeing Through the Displaced Frame: Privileged Noise Distillation for Vision-Force Precision Assembly

model-releasesarxiv-cs-ro

arXiv:2610.07745v1 Announce Type: new Abstract: Pose error in precision assembly can corrupt not only what a robot observes but also the coordinate frame in which it acts. On the FORGE benchmark, the

Local Ai

Selective Critique for Cost-Aware LLM Agents in Long-Horizon Decision Making

arXiv:2610.07335v1 Announce Type: cross Abstract: Improving the reliability of large language model (LLM) agents in long-horizon decision-making remains a key challenge. When deployed as autonomous ag

local-aiarxiv-cs-ai

Selective Transfer of RL Updates for Visual Reasoning

arXiv:2610.08659v1 Announce Type: cross Abstract: Model merging provides a training-free way to transfer reasoning capabilities from language models to vision-language models (VLMs), but endpoint-base

Self-Referenced Social Preferences: Cooperation without Observing Others Rewards

arXiv:2610.07881v1 Announce Type: new Abstract: Social preferences can promote cooperation in multi-agent reinforcement learning, but existing approaches often require agents to observe the rewards of

Self-Retrospection Distillation: Turning Post-hoc Experiences into Prior Foresight

arXiv:2610.08077v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) turns agent experience into learning signals primarily through scalar outcome rewards after intera

Agents

Semantic Behavioral Watermarking: Paraphrase-Robust and Forgery-Resistant Provenance for LLM Agents

arXiv:2610.08668v1 Announce Type: cross Abstract: Behavioral watermarking embeds an owner identifier in an LLM agent's high-level action choices, giving provenance without touching output tokens. Prio

agentsarxiv-cs-ai

Semantic Capability Acquisition and Specialization During Vision-Language Model Fine-Tuning

arXiv:2610.07385v1 Announce Type: new Abstract: Fine-tuning vision-language models (VLMs) is typically evaluated at a single downstream checkpoint, obscuring whether a semantic capability was never ac

researcharxiv-cs-cv

SENSE: State-aware Emotion Navigation Storytelling Engine

arXiv:2610.07666v1 Announce Type: cross Abstract: This paper presents SENSE, a state-aware framework for generating playable branching visual novels with multi-track emotional navigation. Integrating

Sensitivity Shaping for Latent Modeling

arXiv:2606.14585v2 Announce Type: replace-cross Abstract: Generative dynamics models enable planning in challenging systems, but safe deployment requires detecting policy-induced out-of-distribution (

Tutorials

Sensor Geometry as a Flow-Matching Prior for Multi-Channel Brain Signals

arXiv:2610.08355v1 Announce Type: cross Abstract: Flow-matching models start from an isotropic Gaussian source, the standard choice when the correlation structure of the data is unknown in advance. Fo

tutorialsarxiv-cs-ai

Sensor-Language-Action Models

arXiv:2610.08244v1 Announce Type: new Abstract: Sensors are useful not only for understanding the world but also for deciding what to do next. Existing sensor models however largely stop at perception

Sensor-Layout-Agnostic Navigation via Geometric Observation Canonicalization

arXiv:2610.08306v1 Announce Type: new Abstract: Existing visual navigation policies are inherently bound to fixed camera configurations, creating a fundamental barrier to zero-shot deployment across h

safetyarxiv-cs-ro

SepsisLens: Structure-Preserving Sequence Modelling for Decomposable Early Sepsis Warning

arXiv:2610.08046v1 Announce Type: new Abstract: Early sepsis warning from ICU records can be cast as a structure-preserving prediction problem. A model needs to detect deterioration from irregular mea

ServeLearnBench: How Well Can Agents Self-Improve from Serving Experience?

arXiv:2610.07792v1 Announce Type: cross Abstract: Large language model agents are increasingly deployed to perform complex tasks in real-world environments. However, the knowledge required for correct

sHAIL-Causal: A Sequential Staircase Procedure for Invariant Causal Predictor Discovery

arXiv:2610.07057v1 Announce Type: cross Abstract: We introduce sHAIL-Causal, the causal specialization of the Saturated Hierarchical Atomic Incremental Learning (sHAIL) paradigm: a sequential staircas

ShanLiangRen: A Nutrition Agent for Personalized Daily Meal Planning

arXiv:2610.07886v1 Announce Type: new Abstract: Dietary nutrition planning plays an important role in chronic disease management and maintaining a healthy body. In applications, it must simultaneously

Shaping the Wind: Nested Potentials for Kinematically Admissible Urban Wind Prediction

arXiv:2610.07033v1 Announce Type: new Abstract: Predicting transient urban winds is fundamental to understanding urban microclimates and designing climate-resilient cities. Building-resolving large-ed

SharedKV-BT: Node-Local Typed Decisions for Behavior-Tree Agents

arXiv:2610.07327v1 Announce Type: cross Abstract: Agent tasks require sequences of interdependent decisions. Autoregressive models support more flexible decision interfaces than conventional classifie

safetyarxiv-cs-cl

Sherpa: Teaching LLMs to Teach Adaptively

arXiv:2610.08778v1 Announce Type: new Abstract: Large language models (LLMs) have become increasingly capable problem solvers, but being able to solve a problem is not the same as being able to teach

Tutorials

Should We Skip Diffusion?

arXiv:2610.07002v1 Announce Type: cross Abstract: Diffusion models learn semantic representations while generating images. In the Decoupled Diffusion Transformer (DDT), a condition encoder provides fe

tutorialsarxiv-cs-cv

Applications

SIFT: Search Intent-to-Filter Transformer for Multi-Task Personalized Filter Ranking at Airbnb

arXiv:2610.07810v1 Announce Type: new Abstract: Search filters help guests navigate vast catalogs in two-sided marketplaces like Airbnb, and recommending the right filters can meaningfully lift bookin

applicationsarxiv-cs-lg

SIGMA: Self-Improving Alignment Generalization from a Model Spec

arXiv:2610.07935v1 Announce Type: new Abstract: LLM agents are increasingly capable of executing complex tasks and of recursively improving themselves on easy-to-verify objectives such as software eng

Silicon Language: A Robot-Native Knowledge Exchange Framework for Heterogeneous Robots

arXiv:2610.07650v1 Announce Type: new Abstract: Reusing a capability across heterogeneous robots still requires substantial human adaptation and verification: transferring a skill often means re-engin

safetyarxiv-cs-ro

Local Ai

Sim-to-Real Transfer of Vision-Language Navigation in Continuous Environments Using an Ackermann-Steered Mobile Robot

arXiv:2610.07192v1 Announce Type: new Abstract: Vision-Language Navigation (VLN) enables robots to navigate through environments using natural language instructions, making human-robot interaction int

local-aiarxiv-cs-ai