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arXiv:2608.31045v1 Announce Type: new Abstract: Rotational symmetry is one of the most important structural principles in machine learning on 3D data. In applications ranging from physics and material

tutorialsarxiv-cs-lg

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RouteSparse: Input-Conditional Pattern Routing for Budgeted Long-Context Prefilling

DGX agent

arXiv:2608.29058v1 Announce Type: new Abstract: Dynamic sparse attention can reduce the quadratic cost of long-context prefilling without changing model weights. MInference assigns each attention head

model-releasesarxiv-cs-cl

1 Sept 2026

RSLM: Training-Free Vector Quantization for Approximate Nearest Neighbor Search

arXiv:2608.30384v1 Announce Type: new Abstract: By introducing RSLM (Rotated Scaled Lloyd-Max), a family of training-free vector quantization codecs compressing embeddings to 1--4 bits per dimension,

RSPO: Regularized Self-Play Alignment of Large Language Models

arXiv:2503.00030v3 Announce Type: replace-cross Abstract: Self-play-based policy optimization has emerged as an effective approach for fine-tuning large language models (LLMs), formulating preference

Rubric-to-Code Credit Assignment for Reinforcement Learning

arXiv:2608.27906v2 Announce Type: replace Abstract: Interactive web application generation requires models to produce usable HTML, CSS, and JavaScript applications from natural language requests. Unli

Runtime Safety Filtering for Learned Small UAS Separation Policies under GNSS Degradation

arXiv:2607.10014v2 Announce Type: replace-cross Abstract: Learning-based separation assurance for small Unmanned Aircraft Systems (sUAS) achieves near-zero collision rates in simulation, but assumes a

safetyarxiv-cs-lg

RWKV-7 G1j (100% RNN) release 🙂 much better at agent/coding/STEM and everything. Demo: https://rwkv.com Weights: https://huggingface.co/Bli…

RWKV-7 G1j (100% RNN) release 🙂 much better at agent/coding/STEM and everything. Demo: https://rwkv.com Weights: https://huggingface.co/BlinkDL/rwkv7-g1 RWKV-7 G1i (100% RNN) release 🙂 Demo: https://r

agentsjeremy-howard--x

S3C-LLM: Skill-Code Guided Agentic Language Models for Spectrum-to-Structure Elucidation

arXiv:2608.30910v1 Announce Type: cross Abstract: Spectroscopic structure elucidation is central to molecular analysis, but recent Large Language Model (LLM)-based methods mostly formulate it as direc

agentsarxiv-cs-cl

S3Gym: Can LLMs Turn Self-Testing and Self-Judging into Self-Improvement?

model-releasesarxiv-cs-cl

arXiv:2608.31100v1 Announce Type: new Abstract: Large language models (LLMs) increasingly interact with external environments and accumulate substantial behavioral experience, yet existing agent bench

Safe to Resume? Breaking Execution Continuity of Agent Execution via Rollback

arXiv:2608.29381v1 Announce Type: cross Abstract: AI agents are moving toward persistent, stateful execution across various applications, accumulating execution state and external effects that are cos

agentsarxiv-cs-ai

SafeAtlas-VL: Beyond Binary Multimodal Safety with Large-Scale Data and Guard Models

arXiv:2608.29098v1 Announce Type: new Abstract: Multimodal safety moderation requires distinguishing risks arising from visual content, user intent, and assistant behavior. Existing safeguards, howeve

SafeMath: Inference-time Safety improves Math Accuracy

arXiv:2603.25201v2 Announce Type: replace Abstract: Recent research points toward LLMs being manipulated through adversarial and seemingly benign inputs, resulting in harmful, biased, or policy-violat

safetyarxiv-cs-cl

Safety Screening for Voltage Control in Active Distribution Grids via Distributionally Robust Conformal Screening

arXiv:2608.30889v1 Announce Type: cross Abstract: Deploying a new control policy for voltage control in active distribution grids requires evidence that physical limits will be satisfied before the po

safetyarxiv-cs-ai

SALT: Salience-Aware Lexical Trie for Long-Context Compression

arXiv:2607.17486v2 Announce Type: replace-cross Abstract: As large language models (LLMs) process increasingly longer prompts, computation and KV-cache memory costs have emerged as major bottlenecks i

researcharxiv-cs-ai

Sampling-based Certified Planning with Graphs of Convex Sets

model-releasesarxiv-cs-ro

arXiv:2608.29770v1 Announce Type: new Abstract: Planners on graphs of convex sets return trajectories that are collision-free by construction, provided the convex regions are collision-free. The regio

Local Ai

ScaffoldAgent: Utility-Guided Dynamic Outline Optimization for Open-Ended Deep Research

arXiv:2606.20122v2 Announce Type: replace Abstract: Open-ended deep research (OEDR) requires systems to acquire knowledge through multi-round retrieval and generate coherent long-form reports. The out

local-aiarxiv-cs-ai

Scaffolding Foundation Models into Physical-World Agents Pushes the Frontier of Long-Horizon Navigation

arXiv:2608.30396v1 Announce Type: new Abstract: Long-horizon physical-world agents must reason over distant goals while grounding decisions in reliable closed-loop behavior. Today's foundation models

agentsarxiv-cs-ai

Scalable Clinical Data Infrastructure and Comparative ML Evaluation for Hospitalisation Risk Prediction in Elderly Patients with Multiple Long-Term Conditions using CPRD

arXiv:2608.29419v1 Announce Type: cross Abstract: Deep learning architectures are increasingly proposed for patient trajectory modeling in electronic health records (EHRs), yet their advantage over si

Scale-Plan: Scalable Language-Enabled Task Planning for Heterogeneous Multi-Robot Teams

arXiv:2603.08814v2 Announce Type: replace-cross Abstract: Long-horizon task planning for heterogeneous multi-robot systems is essential for deploying collaborative teams in real-world environments; ye

ScalePRM: Training Process Reward Models by Scaling Verification Compute Without Ground Truth

arXiv:2512.03244v2 Announce Type: replace-cross Abstract: Training process reward models (PRMs) requires step-level correctness labels, obtained either through expensive human annotation or by relying

Scaling Large Reasoning Models beyond Human Supervision: A Path toward Superintelligence

arXiv:2608.31075v1 Announce Type: new Abstract: Recent advances in large reasoning models (LRMs) have shown that reinforcement learning with verifiable rewards (RLVR) can substantially improve reasoni

safetyarxiv-cs-ai

ScenePilot: Grow-and-Repair Policy for Text-Driven 3D Indoor Scene Generation

arXiv:2608.30307v1 Announce Type: cross Abstract: Text-driven 3D indoor scene generation has advanced from dataset-bound layout modeling to open-vocabulary synthesis with large language and vision-lan

safetyarxiv-cs-ai

Science sandboxes measure the scientific capability of AI agents

arXiv:2608.30165v1 Announce Type: cross Abstract: Scientific progress depends not only on finding solutions, but on learning the rules that explain why they work and using that understanding to design

agentsarxiv-cs-ai

ScienceArena: Benchmarking LLMs on Latest Scientific Olympiad Competitions

arXiv:2608.30517v1 Announce Type: new Abstract: Benchmark saturation and data contamination increasingly obscure genuine scientific reasoning in frontier LLMs. We introduce extsc{ScienceArena}, an oly

SciOrch: Learning to Orchestrate Expert LLMs for Solving Frontier Multimodal Scientific Reasoning Tasks

arXiv:2606.15872v2 Announce Type: replace Abstract: Frontier scientific reasoning remains a major challenge for large language models (LLMs), where even the strongest commercial systems fall short of

agentsarxiv-cs-cl

SCoPE-Reg: Efficient Rigid Ultrasound Slice-to-Volume Registration via State-Space Correlation and Closed-Form Pose Estimation

model-releasesarxiv-cs-cv

arXiv:2608.28715v1 Announce Type: cross Abstract: Ultrasound-guided interventions can require localization of an untracked 2D frame within a 3D anatomical reference. Rigid slice-to-volume registration

SearchWiki: Learning to Build and Navigate Knowledge Wikis for Active Information Seeking

arXiv:2608.29953v1 Announce Type: new Abstract: Flat retrieval-augmented generation treats a corpus as a bag of chunks, discarding document hierarchy and cross document structure. We introduce SearchW

Local Ai

Season-Aware Hybrid Convolutional-Transformer for Antarctic Sea Ice Concentration Forecasting

arXiv:2608.30654v1 Announce Type: new Abstract: Antarctic sea ice concentration (SIC) forecasting is an important yet challenging task due to the coexistence of complex spatial structure, long-range t

local-aiarxiv-cs-lg

Securing Amazon Quick from POC to production: Agents, Flows, and Spaces

Amazon Quick proof-of-concept projects often stall when security teams review the production plan. This post walks through designing dashboards, Spaces, knowledge bases, agents, and Flows with securit

agentsaws-ml-blog

See the Change, Keep the Flow: Unsupervised Action Segmentation via Spectral-Temporal Representation Learning

arXiv:2608.29611v1 Announce Type: new Abstract: Unsupervised action segmentation aims to discover latent action categories and their temporal organization without action annotations. Optimal transport

Seeing the Unseen: Camouflaged Object Detection Beyond the Visible Spectrum

arXiv:2608.30355v1 Announce Type: new Abstract: Recent advances in camouflaged object detection (COD) have led to substantial progress in challenging low-visibility scenarios, with pioneering studies

Applications

Seeing the Unseen: Visual Similarity for Pixel Language Model Adaptation

arXiv:2608.30541v1 Announce Type: new Abstract: Pixel-based language models (LMs) replace traditional tokenizers by processing rendered images of text, making cross-lingual transfer heavily dependent

applicationsarxiv-cs-cl

Seeing Through Extreme Visual Sparsity: Surface Understanding from a Single Random Visual Patch

arXiv:2608.29475v1 Announce Type: new Abstract: Surface material recognition from incomplete visual observations remains a challenging problem in robotic perception and environmental understanding. Th

seems like it

model-releasesclem-delangue--x

seems like it I hadn’t realized it until now, but could Microduck actually be the biggest launch of a new consumer robot ever? 10,500 robots ordered and $4.54M in sales in just 4 days. It’s surprising

Segmentation of Bovid Dentition Under Imperfect Annotations: A Comparative Study of Convolutional and Attention Models

arXiv:2608.31052v1 Announce Type: new Abstract: Semantic segmentation decomposes an image into distinct mask regions corresponding to different object categories, such as people, cars, signs or buildi

safetyarxiv-cs-cv

SegWave: Wavelet-Driven Segmentation of Tampered Regions

model-releasesarxiv-cs-cv

arXiv:2608.30714v1 Announce Type: new Abstract: Verifying image authenticity is increasingly difficult, posing serious risks across journalism, law enforcement, and political domains. Most existing fo

SELECT: SELEctive Context Transfer for Class-Incremental Semantic Segmentation

arXiv:2608.30281v1 Announce Type: new Abstract: Class-Incremental Semantic Segmentation (CISS) is fundamentally challenged by catastrophic forgetting and background shift, where learning new concepts

Selection-Aware Stress Testing for Interactive Agents

arXiv:2608.30916v1 Announce Type: new Abstract: Agent evaluations often use one benchmark to choose a workflow and then search for task types where its advantage weakens, so both conclusions are selec

Selection, Representation, and Execution in Sparse Fourier Neural Operators

arXiv:2608.30070v1 Announce Type: new Abstract: Sparse representations are often expected to make models smaller and also reduce inference cost. For Fourier Neural Operators (FNOs), these objectives a

Selective Disclosure of Hidden Directives in Reasoning Models: Behavioral Asymmetry and Steering

arXiv:2608.29070v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning traces are increasingly proposed as a mechanism for AI oversight: a monitor inspecting a model's reasoning can, in prin

Selective Forgetting: A Graph-Based Memory Framework for Long-Term LLM Agents

arXiv:2608.28978v1 Announce Type: new Abstract: Knowledge graphs have been proposed as a structured alternative to flat retrieval-augmented generation for long-term agent memory, on the assumption tha

Self-Aware Active Learning Enables Continual Improvement in Autonomous Driving

arXiv:2608.29772v1 Announce Type: new Abstract: Learning-based autonomous driving (AD) systems can perform reliably in familiar conditions, yet rare distribution shifts and long-tail events remain a m

safetyarxiv-cs-ro

Self-Evolving Skills via Surrogate-Guided Solve-and-Reproduce

arXiv:2608.28638v1 Announce Type: new Abstract: Agent skills are portable packages of instructions and resources an agent consults at deployment. Self-evolving them fails in two ways today. First, ski

Self-Specialized Teachers for Domain Post-Training

arXiv:2608.28647v1 Announce Type: new Abstract: Target-only post-training can improve performance in a specialized domain while degrading behaviors that a general-purpose base model acquired before ad

Self-Supervised Pretext Tasks for Infant Cry Analysis: A Controlled Comparison and a Cautionary Result on Donateacry

arXiv:2608.30456v1 Announce Type: new Abstract: We compare six self-supervised pretext tasks for infant cry analysis under a fixed budget, meaning the same compact encoder of 1.17M parameters, the sam

Semantic-Spatial Discriminability Enhancement for Generalized Visual Grounding

arXiv:2608.30233v1 Announce Type: new Abstract: Generalized Visual Grounding (GVG) task aims to localize targets in an image based on referring expressions, extends the classical visual grounding para

Applications

Semi-supervised CAPP Transformer Learning via Pseudo-labeling

arXiv:2602.01419v2 Announce Type: replace-cross Abstract: High-level Computer-Aided Process Planning (CAPP) generates manufacturing process plans from part specifications. It suffers from limited data

applicationsarxiv-cs-ai

SemKV: Semantic Mixed-Precision KV Cache Quantization Guided by the Quality Cliff for Long-Context LLM Inference

model-releasesarxiv-cs-cl

arXiv:2608.28911v1 Announce Type: cross Abstract: The key-value (KV) cache is the dominant memory bottleneck of long-context large language model (LLM) inference, growing linearly with context length.