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I can't verify this claim based on reliable sources. The post appears to make allegations about San Diego police withholding information regarding a mosque shooting and the identities of suspects, att

industryelon-musk--x

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Model Releases

KairosHope: A Next-Generation Time-Series Foundation Model for Specialized Classification via Dual-Memory Architecture

DGX agent

arXiv:2605.18657v1 Announce Type: cross Abstract: Time Series Foundation Models (TSFMs) have demonstrated notable success in general-purpose forecasting tasks; however, their adaptation to specialized

model-releasesarxiv-cs-ai

19 May 2026

Industry

.@karpathy at @AnthropicAI = more open-source from them? They're already contributing datasets: https://huggingface.co/Anthropic but would b…

.@karpathy at @AnthropicAI = more open-source from them? They're already contributing datasets: https://huggingface.co/Anthropic but would be super cool to see more (massive potential for impact obvio

industryclem-delangue--x

Applications

KASER: Knowledge-Aligned Student Error Simulator for Open-Ended Coding Tasks

arXiv:2601.06633v2 Announce Type: replace-cross Abstract: Open-ended tasks, such as coding problems that are common in computer science education, provide detailed insights into student knowledge. How

applicationsarxiv-cs-ai

Keeping an Eye on AI: A Framework for Effective Human Oversight of AI Systems

arXiv:2605.16278v1 Announce Type: cross Abstract: The use of Artificial Intelligence (AI) in high-risk, decision-making scenarios presents technical, safety, and normative challenges; problems that ma

safetyarxiv-cs-ai

Kelvin v1.0: A Neural Pre-Encoder for H.264: A standards-compliant learned preprocessor with -27.62% BD-VMAF on UVG

model-releasesarxiv-cs-cv

arXiv:2605.16376v1 Announce Type: cross Abstract: Kelvin is a lightweight learned pre-encoder that sits in front of an unmodified libx264 encoder. It applies content-adaptive pixel adjustments, bounde

Applications

Key-Gram: Extensible World Knowledge for Embodied Manipulation

arXiv:2605.18556v1 Announce Type: cross Abstract: Embodied control increasingly requires models to follow compositional language instructions while reasoning over dynamic visual states. However, curre

applicationsarxiv-cs-ai

KISS - Knowledge Infrastructure for Scientific Simulation: A Scaffolding for Agentic Earth Science

arXiv:2605.17856v1 Announce Type: new Abstract: Process-based simulation models encode decades of scientific understanding across the Earth sciences, yet the communities most exposed to climate risk a

Knowledge-to-Verification: Exploring RLVR for LLMs in Knowledge-Intensive Domains

arXiv:2605.18261v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has demonstrated promising potential to enhance the reasoning capabilities of large language model

researcharxiv-cs-cl

KPMG partners with Anthropic to embed Claude into its tax and advisory platforms; KPMG's tax and legal services unit saw revenue grow ~8% YoY to $9.3B in 2025 (Mark Maurer/Wall Street Journal)

Mark Maurer / Wall Street Journal: KPMG partners with Anthropic to embed Claude into its tax and advisory platforms; KPMG's tax and legal services unit saw revenue grow ~8% YoY to $9.3B in 2025 — The

model-releasestechmeme

KVCapsule: Efficient Sequential KV Cache Compression for Vision-Language Models with Asymmetric Redundancy

arXiv:2605.16439v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) have emerged as a critical and fast-growing extension of Large Language Models (LLMs) that enable multimodal reasoning t

Hardware

KVDrive: A Holistic Multi-Tier KV Cache Management System for Long-Context LLM Inference

arXiv:2605.18071v1 Announce Type: new Abstract: Supporting long-context LLMs is challenging due to the substantial memory demands of the key-value (KV) cache. Existing offloading systems store the ful

hardwarearxiv-cs-cl

Tutorials

L-Drive: Beyond a Single Mapping-Latent Context Drives Time Series Forecasting

arXiv:2605.17730v1 Announce Type: cross Abstract: Mainstream methods for multivariate time-series forecasting largely follow the Direct-Mapping paradigm. They learn a unified mapping from history to t

tutorialsarxiv-cs-ai

LACE: Latent Visual Representation for Cross-Embodiment Learning

arXiv:2605.16743v1 Announce Type: new Abstract: Cross-embodiment learning from human demonstrations is hindered by the visual gap between human and robot embodiments. While self-supervised learning (S

safetyarxiv-cs-ro

LaDi-RL: Latent Diffusion Reasoning Prevents Entropy Collapse in Reinforcement Learning

arXiv:2602.01705v3 Announce Type: replace-cross Abstract: Reinforcement learning has become a central paradigm for improving LLM reasoning, but most existing methods optimize policies over discrete to

Lambda’s NVIDIA HGX 8xB200 on STAC-AI™ LANG6

model-releaseslambda-labs

What the numbers mean for financial services Executive summary Lambda is the first to publish an audited STAC-AI™ LANG6 result on NVIDIA HGX 8xB200, with independently verified performance data that F

Lance: Unified Multimodal Modeling by Multi-Task Synergy

arXiv:2605.18678v1 Announce Type: cross Abstract: We present Lance, a lightweight native unified model supporting multimodal understanding, generation, and editing for both images and videos. Rather t

safetyarxiv-cs-ai

LangChain Applied AI Engineer @palashshah takes us under the hood of LangSmith Engine.

LangSmith Engine is a tool within the LangChain ecosystem that provides visibility and debugging capabilities for AI applications built with LangChain. This technical deep-dive likely covers how the e

agentsharrison-chase--x

LangGraph.js Long-Term Memory Store is now generally available. This integration brings long-term memory across sessions, across users, and …

LangGraph.js Long-Term Memory Store is now generally available. This integration brings long-term memory across sessions, across users, and across time, with Atlas as the unified backend for checkpoin

agentsharrison-chase--x

Language Acquisition Device in Large Language Models

arXiv:2605.16758v1 Announce Type: new Abstract: Large Language Models (LLMs) remain substantially less data-efficient than humans. Pre-pretraining (PPT) on synthetic languages has been proposed to clo

researcharxiv-cs-cl

Language Game: Talking to Non-Human Systems

model-releasesarxiv-cs-lg

arXiv:2605.16321v1 Announce Type: new Abstract: Language carries thought and coordination among humans but rarely reaches further along the spectrum of diverse intelligence. Yet non-neural systems --

Language Models as Efficient Reward Function Searchers for Custom-Environment Multi-Objective Reinforcement

arXiv:2409.02428v4 Announce Type: replace-cross Abstract: Achieving the effective design and improvement of reward functions in reinforcement learning (RL) tasks with complex custom environments and m

Language-Switching Triggers Take a Latent Detour Through Language Models

model-releasesarxiv-cs-cl

arXiv:2605.18646v1 Announce Type: new Abstract: Backdoor attacks on language models pose a growing security concern, yet the internal mechanisms by which a trigger sequence hijacks model computations

LaPA^2: Length-Aware Prefix and Prompt Attention Augmentation for Long-Form Controllable Text Generation

model-releasesarxiv-cs-cl

arXiv:2508.04047v2 Announce Type: replace Abstract: Prefix-based methods have emerged as a promising paradigm for Controllable Text Generation (CTG) due to their parameter efficiency. However, while e

Large Language Models and Impossible Language Acquisition: 'False Promise' or an Overturn of our Current Perspective towards AI

arXiv:2602.08437v5 Announce Type: replace Abstract: In Chomsky's provocative critique 'The False Promise of CHATGPT,' Large Language Models (LLMs) are characterized as mere pattern predictors that do

researcharxiv-cs-cl

LARGER: Lexically Anchored Repository Graph Exploration and Retrieval

arXiv:2605.16352v1 Announce Type: cross Abstract: Repository-level coding agents must first localize the files and symbols relevant to a task; failures at this stage can cascade across downstream obje

agentsarxiv-cs-ai

LASAR: Towards Spatio-temporal Reasoning with Latent Cognitive Map

arXiv:2605.16899v1 Announce Type: new Abstract: A fundamental challenge in embodied AI is verifying if agents build internal models of spatial structure or merely learn to mimic task-specific expert t

agentsarxiv-cs-cv

LAST-RAG: Literature-Anchored Stochastic Trajectory Retrieval-Augmented Generation for Knowledge-Conditioned Degradation Model Selection

arXiv:2605.17902v1 Announce Type: new Abstract: Stochastic-process-based degradation modeling is a core approach for estimating the distribution of remaining useful life (RUL); however, the selection

Latency-Aware Deep Learning Benchmark for Real-Time Cyber-Physical Attack and Fault Classification in Inverter-Dominated Power Grids

arXiv:2605.17256v1 Announce Type: cross Abstract: This work introduces a latency-aware benchmarking framework for evaluating deep learning models in power system anomaly detection using high-fidelity,

Latent Action Control for Reasoning-Guided Unified Image Generation

arXiv:2605.16961v1 Announce Type: cross Abstract: Unified multimodal models can encode visual understanding and image generation within a shared backbone, yet understanding does not automatically tran

safetyarxiv-cs-ai

Latent Action Reparameterization for Efficient Agent Inference

arXiv:2605.18597v1 Announce Type: new Abstract: Large language model (LLM) agents often rely on long sequences of low-level textual actions, resulting in large effective decision horizons and high inf

agentsarxiv-cs-ai

Latent Heuristic Search: Continuous Optimization for Automated Algorithm Design

arXiv:2605.17137v1 Announce Type: new Abstract: The integration of Large Language Models (LLMs) into evolutionary frameworks has established a new paradigm for automated heuristic discovery. Despite t

Latent-IMH: Efficient Bayesian Inference for Inverse Problems with Approximate Operators

arXiv:2601.20888v3 Announce Type: replace-cross Abstract: We study sampling from posterior distributions in Bayesian linear inverse problems where A, the parameters to observables operator, is computa

researcharxiv-cs-lg

LatentUMM: Dual Latent Alignment for Unified Multimodal Models

arXiv:2605.17766v1 Announce Type: new Abstract: Unified multimodal models (UMMs) achieve strong performance in both understanding and generation by learning a shared latent space, yet they often exhib

safetyarxiv-cs-cv

LaunchDarkly launches runtime control layer for the agentic AI era

model-releasessiliconangle

LaunchDarkly, a feature control platform that helps developers and software engineers launch and manage products, today announced the launch of AgentControl, a new solution providing real-time managem

LEAF: A Living Benchmark for Event-Augmented Forecasting

arXiv:2605.16358v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly applied to forecasting. To evaluate this capability while mitigating pre-training data contamination, se

Lean Meets Theoretical Computer Science: Scalable Synthesis of Theorem Proving Challenges in Formal-Informal Pairs

arXiv:2508.15878v2 Announce Type: replace-cross Abstract: Formal theorem proving (FTP) has emerged as a critical foundation for evaluating the reasoning capabilities of large language models, enabling

Hardware

LEAP: Learnable End-to-End Adaptive Pruning of Large Language Models

arXiv:2605.17289v1 Announce Type: cross Abstract: Unstructured sparsity is now natively accelerated by recent GPU kernels and dataflow hardware, shifting the bottleneck from inference execution to the

hardwarearxiv-cs-ai

Learned Memory Attenuation in Sage-Husa Kalman Filters for Robust UAV State Estimation

model-releasesarxiv-cs-lg

arXiv:2605.18704v1 Announce Type: cross Abstract: Unmanned Aerial Vehicles in dynamic environments face telemetry outages, structural vibrations, and regime-dependent noise that invalidate the station

Learning-Based Adaptive Control for Surgical Robotic Exposure Task on Deformable Tissues

arXiv:2605.17927v1 Announce Type: new Abstract: In various surgical procedures, regions of interest (ROIs) such as organs or lesions are often occluded by overlying tissues, requiring surgeons to achi

safetyarxiv-cs-ro

Learning Displacement-Aware WiFi Representations for Weakly Supervised Relative Localization

arXiv:2605.16357v1 Announce Type: cross Abstract: WiFi fingerprint-based indoor localization has been widely studied, but most existing approaches focus on absolute positioning and rely on dense coord

Learning Displacement-Robust Representations for Landslide Early Warning under Rainfall Forecast Uncertainty

arXiv:2605.17419v1 Announce Type: cross Abstract: Rainfall-induced landslides pose a growing risk worldwide as climate change intensifies extreme rainfall events. To provide sufficient evacuation time

Learning Faster with Better Tokens: Parameter-Efficient Vocabulary Adaptation for Specialized Text Summarization

arXiv:2605.17379v1 Announce Type: cross Abstract: Large language models pretrained on general-domain corpora often exhibit tokenization inefficiencies when applied to specialized domains. Although con

Learning Fill-in Reduction Ordering via Graph Policy Optimization for Sparse Matrices

arXiv:2605.17362v1 Announce Type: new Abstract: Matrix reordering in large sparse solvers seeks a permutation that minimizes factorization fill-in to reduce memory and computation. Because the minimum

safetyarxiv-cs-lg

Tutorials

Learning from Historical Activations in Graph Neural Networks

arXiv:2601.01123v2 Announce Type: replace-cross Abstract: Graph Neural Networks (GNNs) have demonstrated remarkable success in various domains such as social networks, molecular chemistry, and more. A

tutorialsarxiv-cs-ai

Learning from Self-Debate: Preparing Reasoning Models for Multi-Agent Debate

arXiv:2601.22297v2 Announce Type: replace Abstract: The reasoning abilities of large language models (LLMs) have been substantially improved by reinforcement learning with verifiable rewards (RLVR). A

agentsarxiv-cs-cl

Learning Higher-Order Structure from Incomplete Spatiotemporal Data: Multi-Scale Hypergraph Laplacians with Neural Refinement

arXiv:2605.17316v1 Announce Type: cross Abstract: Sensor networks increasingly govern modern infrastructure, yet the data they lose are rarely missing in the uniform-random patterns assumed by standar

Learning How to Cube

arXiv:2605.16632v1 Announce Type: cross Abstract: Despite the effectiveness of Cube-and-Conquer (C&C) for solving challenging Boolean Satisfiability (SAT) problems, no prior work has shown that transf