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Simulation Distillation: Pretraining World Models in Simulation for Rapid Real-World Adaptation

arXiv:2603.15759v2 Announce Type: replace-cross Abstract: Robot learning requires adaptation methods that improve reliably from limited, mixed-quality interaction data. This is especially challenging

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Simulation-Ready Cluttered Scene Estimation via Physics-aware Joint Shape and Pose Optimization

DGX agent

arXiv:2602.20150v2 Announce Type: replace-cross Abstract: Estimating simulation-ready scenes from real-world observations is crucial for downstream planning and policy learning tasks. Regretfully, exi

safetyarxiv-cs-cv

13 May 2026

Single-Shot HDR Recovery via a Video Diffusion Prior

arXiv:2605.11628v1 Announce Type: new Abstract: Recent generative methods for single-shot high dynamic range (HDR) image reconstruction show promising results, but often struggle with preserving fidel

researcharxiv-cs-cv

SkillGen: Verified Inference-Time Agent Skill Synthesis

arXiv:2605.10999v1 Announce Type: new Abstract: Skills are a promising way to improve LLM agent capabilities without retraining, while keeping the added procedure reusable and controllable. However, h

agentsarxiv-cs-lg

SkillGraph: Skill-Augmented Reinforcement Learning for Agents via Evolving Skill Graphs

arXiv:2605.12039v1 Announce Type: new Abstract: Skill libraries enable large language model agents to reuse experience from past interactions, but most existing libraries store skills as isolated entr

safetyarxiv-cs-cl

SkillSafetyBench: Evaluating Agent Safety under Skill-Facing Attack Surfaces

arXiv:2605.12015v1 Announce Type: cross Abstract: Reusable skills are becoming a common interface for extending large language model agents, packaging procedural guidance with access to files, tools,

Slicing and Dicing: Configuring Optimal Mixtures of Experts

arXiv:2605.11689v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) architectures have become standard in large language models, yet many of their core design choices - expert count, granularit

Smart moves: Building resilient transportation systems with Google AI

What does transportation mean to you? For some, it’s making sure the train is on schedule so they can get to work on time. Maybe it’s making sure you have time connecting between flights. Maybe it’s a

safetygoogle-cloud-ai

Smooth-Rigid-Body Contact as a ReLCP: A Recursively Generated Linear Complementarity Problem

arXiv:2506.14097v2 Announce Type: replace Abstract: This paper reformulates complementarity-based time-stepping for frictionless nonsmooth contact between smooth rigid bodies as a recursively generate

researcharxiv-cs-ro

Tutorials

Smoothed Analysis of Learning from Positive Samples

arXiv:2504.10428v2 Announce Type: replace-cross Abstract: Binary classification from positive-only samples is a variant of PAC learning where the learner receives i.i.d. positive samples and aims to l

tutorialsarxiv-cs-lg

Tutorials

Smoothness Errors in Dynamics Models and How to Avoid Them

arXiv:2602.05352v2 Announce Type: replace Abstract: Modern neural networks have shown promise for solving partial differential equations over surfaces, often by discretizing the surface as a mesh and

tutorialsarxiv-cs-lg

so cool to see another blazing fast database built on vortex!

so cool to see another blazing fast database built on vortex! Just announced at Interrupt! SmithDB. Agent traces have outgrown the databases built to hold them. That’s why we built SmithDB, a purpose-

agentsharrison-chase--x

So many agent builders at Langchain Interrupt 2026 😍😍😍

At LangChain Interrupt 2026, multiple agent builder tools and frameworks were showcased, reflecting the growing ecosystem of agentic AI development. This post highlights the proliferation of agent-bui

agentsharrison-chase--x

so we built psql_bm25s. exact BM25 retrieval. native Postgres access method. ~23x faster than pg_search on the standard benchmark. retrieval…

model-releasesemad-mostaque--x

so we built psql_bm25s. exact BM25 retrieval. native Postgres access method. ~23x faster than pg_search on the standard benchmark. retrieval stops being a budget item. the harness stops rationing. the

SOAR: Regression-based LiDAR Relocalization for UAVs

model-releasesarxiv-cs-cv

arXiv:2602.13267v3 Announce Type: replace Abstract: Regression-based LiDAR relocalization has recently emerged as a promising solution for high-precision positioning in GNSS-denied environments. Howev

SOAR: Scale Optimization for Accurate Reconstruction in NVFP4 Quantization

arXiv:2605.12245v1 Announce Type: new Abstract: NVFP4 has recently emerged as an efficient 4-bit microscaling format for large language models (LLMs), offering superior numerical fidelity with native

Sobolev Regularized MMD Gradient Flow

arXiv:2605.11884v1 Announce Type: new Abstract: We propose Sobolev-regularized Maximum Mean Discrepancy (SrMMD) gradient flow, a regularized variant of maximum mean discrepancy (MMD) gradient flow bas

SoftBank reports Q4 net income up 3x to ~11.6B, above ~1.5B est., driven by a 25B gain in its OpenAI stake; by October, its OpenAI investment will hit 64.6B (David Keohane/Financial Times)

David Keohane / Financial Times: SoftBank reports Q4 net income up 3x to ~11.6B, above ~1.5B est., driven by a 25B gain in its OpenAI stake; by October, its OpenAI investment will hit 64.6B — Japanese

SoK: Unlearnability and Unlearning for Model Dememorization

arXiv:2605.11592v1 Announce Type: new Abstract: Advanced model dememorization methods, including availability poisoning (unlearnability) and machine unlearning, are emerging as key safeguards against

Solve the Loop: Attractor Models for Language and Reasoning

arXiv:2605.12466v1 Announce Type: cross Abstract: Looped Transformers offer a promising alternative to purely feed-forward computation by iteratively refining latent representations, improving languag

Local Ai

SOMA: Efficient Multi-turn LLM Serving via Small Language Model

arXiv:2605.11317v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in multi-turn dialogue settings where preserving conversational context across turns is essential

local-aiarxiv-cs-cl

Source: Cerebras priced its IPO at 185 per share, above the expected range of 150 to 160, raising at least 5.55B and valuing it at $56.4B fully diluted (Jordan Novet/CNBC)

Jordan Novet / CNBC: Source: Cerebras priced its IPO at 185 per share, above the expected range of 150 to 160, raising at least 5.55B and valuing it at 56.4B fully diluted — Cerebras Systems, a maker

Applications

Sources: Apollo Global, Morgan Stanley, and others are testing Grok internally as part of xAI's finance sector push, but financiers are rarely using it for work (Carmen Arroyo/Bloomberg)

Carmen Arroyo / Bloomberg: Sources: Apollo Global, Morgan Stanley, and others are testing Grok internally as part of xAI's finance sector push, but financiers are rarely using it for work — Elon Musk'

applicationstechmeme

Sources: Arm and SoftBank expressed preliminary interest in acquiring Cerebras weeks before its expected IPO; Cerebras rebuffed them (Bloomberg)

Bloomberg: Sources: Arm and SoftBank expressed preliminary interest in acquiring Cerebras weeks before its expected IPO; Cerebras rebuffed them — Arm Holdings Plc and its majority owner SoftBank Group

Sources: Google plans to announce a new Gemini model at its I/O conference next week; the model will land roughly in the class of GPT-5.5, but short of Mythos (Alex Heath/Sources)

Alex Heath / Sources: Sources: Google plans to announce a new Gemini model at its I/O conference next week; the model will land roughly in the class of GPT-5.5, but short of Mythos — Sources say that

model-releasestechmeme

Sources: Microsoft is in discussions to acquire LLM developer Inception; SpaceX also courted Inception, which is looking for a price of over $1B (Reuters)

Reuters: Sources: Microsoft is in discussions to acquire LLM developer Inception; SpaceX also courted Inception, which is looking for a price of over $1B — Microsoft (MSFT.O) is shopping for artificia

Sources: Mistral has been developing a cybersecurity-focused AI model and held discussions about it with European banks, which don't have access to Mythos (Bloomberg)

Bloomberg: Sources: Mistral has been developing a cybersecurity-focused AI model and held discussions about it with European banks, which don't have access to Mythos — French artificial intelligence s

model-releasestechmeme

Space Syntax-guided Post-training for Residential Floor Plan Generation

arXiv:2602.22507v2 Announce Type: replace-cross Abstract: Residential floor plan generation requires not only geometric fidelity but also spatial configurational logic: shared living spaces should be

safetyarxiv-cs-cv

Sparse Attention Remapping with Clustering for Efficient LLM Decoding on PIM

arXiv:2505.05772v2 Announce Type: replace Abstract: Transformer-based models are the foundation of modern machine learning, but their execution, particularly during autoregressive decoding in large la

researcharxiv-cs-cl

Sparse Offline Reinforcement Learning with Corruption Robustness

arXiv:2512.24768v3 Announce Type: replace-cross Abstract: We investigate robustness to strong data corruption in offline sparse reinforcement learning (RL). In our setting, an adversary may arbitraril

Sparsity and Out-of-Distribution Generalization

arXiv:2603.07388v2 Announce Type: replace Abstract: Explaining out-of-distribution generalization has been a central problem in epistemology since Goodman's 'grue' puzzle in 1946. Today it's a central

Sparsity-Constraint Optimization via Splicing Iteration

model-releasesarxiv-cs-lg

arXiv:2406.12017v2 Announce Type: replace-cross Abstract: Sparsity-constrained optimization underlies many problems in signal processing, statistics, and machine learning. State-of-the-art hard-thresh

Spatial Adapter: Structured Spatial Decomposition and Closed-Form Covariance for Frozen Predictors

model-releasesarxiv-cs-lg

arXiv:2605.11394v1 Announce Type: cross Abstract: We present the Spatial Adapter, a parameter-efficient post-hoc layer that equips any frozen first-stage predictor with a structured spatial representa

SpatialForge: Bootstrapping 3D-Aware Spatial Reasoning from Open-World 2D Images

arXiv:2605.11462v1 Announce Type: new Abstract: Recent advancements in Large Vision-Language Models (VLMs) have demonstrated exceptional semantic understanding, yet these models consistently struggle

researcharxiv-cs-cv

Spectral-Adaptive Modulation Networks for Visual Perception

arXiv:2503.23947v2 Announce Type: replace Abstract: Recent studies have shown that 2D convolution and self-attention exhibit distinct spectral behaviors, and optimizing their spectral properties can e

safetyarxiv-cs-cv

Spectral Vision Transformer for Efficient Tokenization with Limited Data

arXiv:2605.12026v1 Announce Type: new Abstract: We propose a novel spectral vision transformer architecture for efficient tokenization in limited data, with an emphasis on medical imaging. We outline

researcharxiv-cs-cv

Spend less time on triaging Ship fixes faster Catch regressions earlier Introducing LangSmith Engine: an agent that works autonomously to fi…

Spend less time on triaging Ship fixes faster Catch regressions earlier Introducing LangSmith Engine: an agent that works autonomously to find patterns in your agent's failures 💻 Accelerate the agent

agentsharrison-chase--x

Split the Differences, Pool the Rest: Provably Efficient Multi-Objective Imitation

arXiv:2605.12000v1 Announce Type: new Abstract: This work investigates multi-objective imitation learning: the problem of recovering policies that lie on the Pareto front given demonstrations from mul

Applications

SplitFed-CL: A Split Federated Co-Learning Framework for Medical Image Segmentation with Inaccurate Labels

arXiv:2605.11060v1 Announce Type: cross Abstract: Split Federated Learning (SplitFed) combines federated and split learning to preserve privacy while reducing client-side computation. However, in medi

applicationsarxiv-cs-cv

Spurious Correlation Learning in Preference Optimization: Mechanisms, Consequences, and Mitigation via Tie Training

arXiv:2605.11134v1 Announce Type: new Abstract: Preference learning methods such as Direct Preference Optimization (DPO) are known to induce reliance on spurious correlations, leading to sycophancy an

SRG: Score-based Relaxation-guided Generation for Mixed Integer Linear Programming

arXiv:2603.24033v2 Announce Type: replace Abstract: We propose Score-based Relaxation-guided Generation (SRG), a generative framework based on an approximate formulation of relaxation-guided stochasti

STAGE: Tackling Semantic Drift in Multimodal Federated Graph Learning

model-releasesarxiv-cs-lg

arXiv:2605.11919v1 Announce Type: new Abstract: Federated graph learning (FGL) enables collaborative training on graph data across multiple clients. As graph data increasingly contain multimodal node

STAPO: Stabilizing Reinforcement Learning for LLMs by Silencing Rare Spurious Tokens

arXiv:2602.15620v4 Announce Type: replace Abstract: Reinforcement Learning (RL) has significantly improved large language model reasoning, but existing RL fine-tuning methods rely heavily on heuristic

Starlink is the top reason to fly United. It immediately makes every flight ten times better and it's free.

Elon Musk posted on X claiming that Starlink internet connectivity is United Airlines' top feature and significantly enhances the flight experience at no cost to passengers. The post suggests Starlink

industryelon-musk--x

Starship launch next week!

model-releaseselon-musk--x

Starship launch next week! Starship’s twelfth flight test will debut the next generation Starship and Super Heavy vehicles, powered by the next evolution of the Raptor engine and launching from a newl

Starting June 15, paid Claude plans can claim a dedicated monthly credit for programmatic usage. The credit covers usage of: - Claude Agent …

model-releasesboris-cherny--x

Starting June 15, paid Claude plans can claim a dedicated monthly credit for programmatic usage. The credit covers usage of: - Claude Agent SDK - claude -p - Claude Code GitHub Actions - Third-party a

Tools

Starting today, you can run cloud agents inside fully configured development environments. Set them up the same way you'd set up a laptop fo…

Starting today, you can run cloud agents inside fully configured development environments. Set them up the same way you'd set up a laptop for an engineer: cloned repos, installed dependencies, and too

toolscursor--x

Stationary MMD Points

arXiv:2505.20754v3 Announce Type: replace-cross Abstract: Approximation of a target probability distribution using a finite set of points is a problem of fundamental importance in numerical integratio