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SAM3RL: Memory Control via Reinforcement Learning for Visual Object Tracking

arXiv:2610.19931v1 Announce Type: new Abstract: Segment Anything Model 3 (SAM 3) is a foundation model for image and video segmentation that sets the state of the art in visual object tracking. Its tr

researcharxiv-cs-cv

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Same Attack, Different Judge: A First Controlled Adversarial Comparison of Jev, LLM Judges, and Purpose-Built Safety Classifiers

DGX agent

arXiv:2610.17820v1 Announce Type: cross Abstract: TypeSafe AI's Jev is a new kind of safety judge. It generates no text and no label: it answers questions the developer defines in advance and returns

model-releasesarxiv-cs-ai

15 Oct 2026

Same Claim, Different Interpretations: How LLM Agents Resolve Ambiguity in Scientific Claims

model-releasesarxiv-cs-cl

arXiv:2610.20457v1 Announce Type: new Abstract: Co-scientists and agentic scientific claim verifiers are increasingly used to assess claims across the sciences. Natural-language scientific claims, wri

Same Operation, Different Permission: Evaluating Whether Guardrails Honor Authorization

arXiv:2610.16838v1 Announce Type: new Abstract: As language-model agents write code, move money and change records on behalf of users, deciding whether an action is authorized has become a central saf

SAT-RL: Training Language Models for Logical Reasoning with Symbolic Solvers

arXiv:2610.14402v1 Announce Type: new Abstract: Large language models (LLMs) have achieved strong performance in mathematical and logical reasoning, yet they still suffer from the curse of complexity

researcharxiv-cs-ai

SaTPO: Text-to-Image Safety Alignment via Transition Preference Optimization

arXiv:2610.19563v1 Announce Type: new Abstract: Safety alignment of text-to-image diffusion models aims to suppress harmful content without compromising useful generation capabilities. However, prefer

safetyarxiv-cs-cv

Scalable Robust MCTS with Anytime Deterministic Optimality Guarantees

arXiv:2610.15461v1 Announce Type: new Abstract: MDP planners often rely on nominal transition models that may differ from the true dynamics. Robust MDP planning accounts for this uncertainty through a

safetyarxiv-cs-ai

Scale Agentic Coding Workflows with Meta’s Muse Spark Open on NVIDIA GB300 NVL72

model-releasesnvidia-developer

Meta’s Muse Spark Open is an 816‑billion‑parameter mixture‑of‑experts coding model that activates only 42 billion parameters per token through top‑8 routing across 256 experts, and has been trained on

Scale, Drivers, and Limits of Representational Alignment Across Large Language Models

arXiv:2610.14476v1 Announce Type: cross Abstract: Comparing large language models can reveal shared representational structure and systematic differences between them. However, aggregate similarity me

Scaling Cheap Synthetic Pretraining Improves Indoor Radio-Map Prediction

model-releasesarxiv-cs-lg

arXiv:2610.19015v1 Announce Type: new Abstract: Real measurements are too limited to train an accurate indoor pathloss predictor that works across a wide range of buildings. Large-scale synthetic pret

Agents

Scaling Discovery Requires Forgetting

arXiv:2610.20563v1 Announce Type: cross Abstract: Automated research with LLM agents has shown promising results in various domains. Through iterative refinement and scored verifiers, LLM agents are c

agentsarxiv-cs-cl

Hardware

Scaling LLM Inference via Parallelism: Throughput-Latency Trade-off

arXiv:2610.19405v1 Announce Type: cross Abstract: Large Language Model (LLM) serving systems must balance latency and throughput while efficiently utilizing distributed GPU resources. This challenge a

hardwarearxiv-cs-lg

Scaling Multilingual Mixture-of-Experts: How Language Coverage Changes Capacity and Compute Allocation

arXiv:2610.20247v1 Announce Type: new Abstract: Multilingual models share capacity across languages, so adding languages can hurt performance on existing ones. Mixture-of-experts models expand this ca

Scaling Multilingual Safety and Reasoning Evaluation through Reasoning-Guided Translation

model-releasesarxiv-cs-cl

arXiv:2610.20221v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed across languages, yet their safety and reasoning capabilities remain predominantly evaluated in E

Scaling Personality Control in LLMs with Big Five Scaler Prompts

arXiv:2508.06149v2 Announce Type: replace Abstract: We present Big5-Scaler, a prompt-based framework for conditioning large language models (LLMs) with controllable Big Five personality traits. By emb

SceneAE: Scene Generation and Reconstruction in Queryable 3D-Anchored Latent Space

arXiv:2610.19708v1 Announce Type: new Abstract: Recent video world models have increasingly adopted 3D memory mechanisms to integrate historical observations into a lightweight and persistent scene re

researcharxiv-cs-cv

Scheduling Parallel Optical Circuit Switches for AI Training

arXiv:2603.07373v2 Announce Type: replace-cross Abstract: The rapid growth of AI training has dramatically increased datacenter traffic demand and energy consumption, which has motivated renewed inter

SchemaWeaver: Accelerating On-Device Mobile Agentic AI via Schema-Guided Parallel LLM Decoding

arXiv:2610.17436v1 Announce Type: new Abstract: Large language models (LLMs) on mobile devices can act as agents that call external software tools to complete complex tasks, but the major challenge of

ScholarQuest: A Taxonomy-Guided Benchmark for Agentic Academic Paper Search in Open Literature Environments

arXiv:2606.20235v2 Announce Type: replace-cross Abstract: Academic paper search is a core step in scientific research, and LLM-based search agents are emerging as a promising paradigm for iterative, i

Applications

Schrodinger's Navigator: Imagining an Ensemble of Futures for Zero-Shot Object Navigation

arXiv:2512.21201v4 Announce Type: replace-cross Abstract: Zero-shot object navigation (ZSON) requires robots to find target objects in unseen environments without task-specific fine-tuning or pre-buil

applicationsarxiv-cs-cv

SciRerankBench: Benchmarking Rerankers Towards Scientific Retrieval-Augmented Generation with LLMs

arXiv:2508.08742v3 Announce Type: replace-cross Abstract: Scientific literature question answering is a pivotal step towards new scientific discoveries. Recently, extit{two-stage} retrieval-augmented

Scoop: The Federal Trade Commission on Wednesday sent civil investigative demands to Anthropic and OpenAI. -Each CID is more than 50 pages l…

Scoop: The Federal Trade Commission on Wednesday sent civil investigative demands to Anthropic and OpenAI. -Each CID is more than 50 pages long. -The FTC is seeking documents related to security incid

safetygary-marcus--x

Tutorials

Score-Based Training for Energy-Based TTS Models

arXiv:2505.13771v2 Announce Type: replace-cross Abstract: Noise contrastive estimation (NCE) is a popular method for training energy-based models (EBM) with intractable normalisation terms. The key id

tutorialsarxiv-cs-lg

ScreenASR-Bench: A Tiered Benchmark for Speech Recognition with Visual Context

arXiv:2610.16260v1 Announce Type: new Abstract: Current ASR models perform well on general benchmarks but still struggle with acoustically ambiguous words. Visual context can aid recognition in screen

SEA-HELM Audio: Evaluating Multilingual ASR-LLM Pipeline Performance Across SEA-HELM Subsets

model-releasesarxiv-cs-cl

arXiv:2610.19869v1 Announce Type: cross Abstract: We introduce SEA-HELM Audio, a Southeast Asian (SEA) multilingual evaluation framework that extends the text-based SEA-HELM benchmark to assess perfor

Seamless Deployment of Machine Learning Inference at the Far Edge: An Empirical AWS IoT Greengrass Architecture for Industrial Predictive Maintenance

arXiv:2610.14815v1 Announce Type: cross Abstract: Industrial IoT sensors produce continuous, high-volume data streams that predictive maintenance needs to analyse in real time. Cloud-centric architect

SearchMaster: Grounded and Regulated Self-Play for Search Agents

arXiv:2608.01822v2 Announce Type: replace Abstract: Training LLM-based search agents requires high-quality search data: tasks that demand genuine multi-hop retrieval and trajectories that use search t

Security in LLM-Assisted Coding: A Systematic Literature Review

arXiv:2610.15482v1 Announce Type: cross Abstract: Large Language Models accelerate software development but introduce severe security vulnerabilities. This systematic review investigates security risk

See a fully-explorable 3D world build itself in minutes ⛩️ Watch @GoogleDeepMind's @GeokenAI explain how Gemini 4 Argon acts as a virtual bu…

model-releasesgoogle-ai--x

See a fully-explorable 3D world build itself in minutes ⛩️ Watch @GoogleDeepMind's @GeokenAI explain how Gemini 4 Argon acts as a virtual builder in @antigravity to autonomously create a stunning, mul

Hardware

Seeing at the Edge: Energy Characterization of Vision-Language Model Inference on Edge Platforms

arXiv:2610.20136v1 Announce Type: new Abstract: Vision-language models (VLMs) are moving onto edge devices, but little is known about how much energy they draw on single-board computers with NPU or GP

hardwarearxiv-cs-lg

Applications

Seeing Depth but Choosing Cues in Vision-Language Models

arXiv:2610.17976v1 Announce Type: new Abstract: Do vision-language models use depth information to judge which object is closer, or rely on image-plane cues? We investigate this question through contr

applicationsarxiv-cs-ai

Seeing, Maintaining, and Learning: The Evolution of Multimodal Agent Memory

arXiv:2610.19366v1 Announce Type: cross Abstract: Multimodal models and agents have emerged to enable AI systems to learn from and interact with the real world more like humans by integrating informat

safetyarxiv-cs-cl

Seeing Through the Forgery Is Not Enough: Regressive Sycophancy under Fabricated Evidence in Medical Vision-Language Models

arXiv:2610.17989v1 Announce Type: cross Abstract: A medical vision-language model may analyze a given CT scan and correctly detect both kidneys in view. Continuing this conversation, if a user provide

researcharxiv-cs-ai

Select or Rewrite: Oracle-Guided Fine-Tuning for Generative ASR Post-Editing from N-Best Hypotheses

arXiv:2610.15056v1 Announce Type: cross Abstract: Large language models can post-edit ASR by using linguistic context to compare N-best hypotheses and rewrite the transcript when needed, often improvi

safetyarxiv-cs-ai

Selective Growing Q-Networks (SGQN): An Analysis of Adaptive Action Grids in Decoupled Q-Learning

arXiv:2610.20463v1 Announce Type: new Abstract: Value-based Q-learning for continuous control can discretise the action space, but the resolution of the discretisation trades early exploration against

researcharxiv-cs-lg

Selective Next-Location Prediction with MetaModelSelect: A Lightweight Post-Hoc Confidence Metamodel

arXiv:2610.19394v1 Announce Type: new Abstract: Next-location prediction can support proactive mobile-network decisions, but acting on unreliable predictions can waste resources. We apply MetaModelSel

researcharxiv-cs-lg

Selective Prediction Forgetting for Adaptation of Weakly Supervised Localization of Histology Images

arXiv:2603.12468v2 Announce Type: replace Abstract: Under strong cross-domain shifts, weakly supervised object localization (WSOL) models often lose their capacity to discriminate and develop a strong

local-aiarxiv-cs-cv

Selective Reasoning for Typed Decision Models: When to Start, Read, and Stop

arXiv:2610.19644v1 Announce Type: new Abstract: Typed decision models need an interface that can use additional reasoning while retaining candidate outputs. We train a shared candidate-answer reader o

Self-Conditioning Enables Deep Sequential Reasoning in Flow Matching

arXiv:2610.19628v1 Announce Type: new Abstract: Recent work has explored visual reasoning through image generation, where models solve visual-reasoning problems by directly generating solution images.

researcharxiv-cs-cv

Self-Evolving Agent Harness

arXiv:2610.18813v1 Announce Type: new Abstract: Harness self-evolution revises an agent's software scaffolding, including prompts, memory, workflows, and executable components, while keeping model wei

safetyarxiv-cs-ai

Agents

Self-Evolving Visual Agent via Margin Reward

arXiv:2610.15084v1 Announce Type: new Abstract: Visual agents that interleave reasoning with tool invocation have posed a promising direction for multimodal tasks. However, learning effective tool inv

agentsarxiv-cs-ai

Self-Representation Alignment in Diffusion Models for Video Background Music Generation

arXiv:2610.15575v1 Announce Type: new Abstract: Diffusion models have been widely used for various generative tasks. However, recent studies have demonstrated that the internal representations learned

Semantic Communities and Boundary-Spanning Lyrics in K-pop: A Graph-Based Unsupervised Analysis

arXiv:2602.12881v2 Announce Type: replace-cross Abstract: We examine how lyric representation shapes computational similarity using four 384-dimensional multilingual MiniLM representations of 7,891 K-

Applications

Semantics as a Shield: Label Disguise Defense (LDD) against Prompt Injection in LLM Sentiment Classification

arXiv:2511.21752v3 Announce Type: replace-cross Abstract: Prompt injection can cause large language models (LLMs) to deviate from their intended tasks by following instructions embedded in untrusted i

applicationsarxiv-cs-ai

Semi-Amortized Bayesian Inference with Reusable Local Posteriors

arXiv:2610.18945v1 Announce Type: cross Abstract: Amortized Bayesian inference uses simulations to perform Bayesian estimation when likelihoods are expensive or analytically unavailable. However, lear

researcharxiv-cs-lg

Sequential Learning-Based Physics-Informed Neural Network Modeling for Parameter Estimation on a Power Converter

model-releasesarxiv-cs-lg

arXiv:2610.20041v1 Announce Type: new Abstract: A staged physics-informed neural network (PINN) is proposed for identifying the inductance, capacitance and parasitic resistances of a DC buck converter

Agents

ServiceNow adds AI agent controls and employee automation tools

ServiceNow Inc. today announced new controls for governing artificial intelligence agents alongside updates to its EmployeeWorks information portal (pictured) that let employees build specialized assi

agentssiliconangle

SFT Leaves a Reproducible Signature in Activation Geometry: Calibrating Post-Training Interpretability Against Run-to-Run Noise

arXiv:2610.17093v1 Announce Type: new Abstract: A model diff credits post-training with whatever separates a base checkpoint from one post-trained descendant, presuming a rerun would land close by. On