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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 😍😍😍

Content type

All Blog X Post Paper YouTube Reddit GitHub

DGX agent

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

13 May 2026

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

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

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

safetyarxiv-cs-lg

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

safetyarxiv-cs-lg

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

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

safetyarxiv-cs-lg

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

Steerable Neural ODEs on Homogeneous Spaces

arXiv:2605.11133v1 Announce Type: new Abstract: We introduce steerable neural ordinary differential equations on homogeneous spaces M=G/H. These models constitute a novel geometric extension of manifo

Steering Without Breaking: Mechanistically Informed Interventions for Discrete Diffusion Language Models

arXiv:2605.10971v1 Announce Type: cross Abstract: Discrete diffusion language models (DLMs) generate text by iteratively denoising all positions in parallel, offering an alternative to autoregressive

StepCodeReasoner: Aligning Code Reasoning with Stepwise Execution Traces via Reinforcement Learning

arXiv:2605.11922v1 Announce Type: cross Abstract: Existing code reasoning methods primarily supervise final code outputs, ignoring intermediate states, often leading to reward hacking where correct an

Stochastic Minimum-Cost Reach-Avoid Reinforcement Learning

arXiv:2605.11975v1 Announce Type: new Abstract: We study stochastic minimum-cost reach-avoid reinforcement learning, where an agent must satisfy a reach-avoid specification with probability at least p

agentsarxiv-cs-lg

StoicLLM: Preference Optimization for Philosophical Alignment in Small Language Models

arXiv:2605.11483v1 Announce Type: new Abstract: While large language models excel at factual adaptation, their ability to internalize nuanced philosophical frameworks under severe data constraints rem

Stop Marginalizing My Dreams: Model Inversion via Laplace Kernel for Continual Learning

arXiv:2605.11804v1 Announce Type: cross Abstract: Data-free continual learning (DFCIL) relies on model inversion to synthesize pseudo-samples and mitigate catastrophic forgetting. However, existing in

researcharxiv-cs-cv

Stop turning prompting into magic spells (and yes, this includes random slash commands with obscure outcomes). Let this one area of working …

applicationsethan-mollick--x

Stop turning prompting into magic spells (and yes, this includes random slash commands with obscure outcomes). Let this one area of working with AI not be weird. Just ask for stuff, in well-specified

Stopping Computation for Converged Tokens in Masked Diffusion-LM Decoding

arXiv:2602.06412v3 Announce Type: replace Abstract: Masked Diffusion Language Models generate sequences via iterative sampling that progressively unmasks tokens. However, they still recompute the atte

Stories in Space: In-Context Learning Trajectories in Conceptual Belief Space

arXiv:2605.12412v1 Announce Type: new Abstract: Large Language Models (LLMs) update their behavior in context, which can be viewed as a form of Bayesian inference. However, the structure of the latent

STRABLE: Benchmarking Tabular Machine Learning with Strings

arXiv:2605.12292v1 Announce Type: new Abstract: Benchmarking tabular learning has revealed the benefit of dedicated architectures, pushing the state of the art. But real-world tables often contain str

applicationsarxiv-cs-lg

Tutorials

Strategically Deceptive Model Deployment in Performative Prediction

arXiv:2506.09044v2 Announce Type: replace Abstract: Machine Learning systems are increasingly deployed in decision-making settings that shape user behavior and, in turn, the data on which future decis

tutorialsarxiv-cs-lg