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Satya Nadella says the public wouldn't tolerate a few AI labs 'doing all of the learning for the world', as Microsoft moves to provide low-c…

Satya Nadella says the public wouldn't tolerate a few AI labs 'doing all of the learning for the world', as Microsoft moves to provide low-cost models and tools (Wall Street Journal) (Visit Techmeme d

industryclem-delangue--x

22 Jun 2026

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Agents

A fundamental problem with extending Codex/Cowork/Code to all knowledge work is that they remain very 'software-brained' where the end resul…

DGX agent

A fundamental problem with extending Codex/Cowork/Code to all knowledge work is that they remain very 'software-brained' where the end result (the software) is what is important & that code serves as

agentsethan-mollick--x

21 Jun 2026

No Taxation Without Annihilation The Anti-Antimatter-Tax Party fights for our freedom. AATP LFG!

This appears to be a humorous or satirical post from an X account using a play on 'No Taxation Without Representation' to create a fictional 'Anti-Antimatter-Tax Party' (AATP). The post uses science f

industryelon-musk--x

>> Scalable Evaluation for AI Agents << If you run agent evaluation in production, this one is worth your time. It shows that front-loading …

>> Scalable Evaluation for AI Agents << If you run agent evaluation in production, this one is worth your time. It shows that front-loading human judgment into reusable evaluation assets is useful. Bu

agentsdair-ai--x

The MCP debate last November at AIE Code was a ton of fun. Does anything feel worth debating at @aiDotEngineer WF? Last time this came toget…

The MCP debate last November at AIE Code was a ton of fun. Does anything feel worth debating at @aiDotEngineer WF? Last time this came together in under a week… So if you want it let’s do it. What sho

model-releasesswyx--x

Toxic empathy looks at these stats and says, 'Let's give them all another chance.'

This post criticizes 'toxic empathy' as an approach that uses statistical data to justify giving repeated chances to individuals or groups, implying such compassion-driven decision-making may be count

industryelon-musk--x

Your data changes and your multi-hop RAG goes stale? This one updates with embed-and-append -> open-weights Llama-3.3-70B, your own vLLM endpoint, no graph rebuild

This post discusses a solution for keeping multi-hop retrieval-augmented generation (RAG) systems updated when data changes, using an embed-and-append approach with the open-weights Llama-3.3-70B mode

model-releasesr-ollama

Tools

@aiDotEngineer @brendanhunting @TedLasso @USMNT @philipkiely btw @philipkiely kinda proud we did this like 2 days after DWR 2025

This post references a recent achievement or project completion by @philipkiely that occurred approximately 2 days after DWR 2025 (likely a conference or event), with mentions of several accounts incl

toolsswyx--x

20 Jun 2026

@WR4NYGov We need an anti-antimatter-tax party 😂

This is a humorous tweet by Elon Musk making a joke about hypothetical taxation policies, using the scientific concept of antimatter as a comedic device. The tweet appears to be satirical commentary,

industryelon-musk--x

20 Jun 2026

A Five-Plane Reference Architecture for Runtime Governance of Production AI Agents

arXiv:2606.12320v1 Announce Type: new Abstract: Enterprise security was built to govern data boundaries: the protected surface was data at rest and in transit, and the controls -- access control, data

Adaptive Multi-Resolution Procedural Knowledge Compression for Large Language Models

arXiv:2606.12203v1 Announce Type: new Abstract: Large language models (LLMs) are widely used to tackle complex tasks with autonomous workflows. Recently, reusable natural language skills have emerged

AerialClaw: An Open-Source Framework for LLM-Driven Autonomous Aerial Agents

arXiv:2606.12142v1 Announce Type: cross Abstract: Unmanned aerial vehicles (UAVs) are increasingly used in inspection, search and rescue, environmental monitoring, and emergency response. However, mos

safetyarxiv-cs-cv

Tutorials

AGE-MIL: Anchor-Guided Evidence Learning for Patient-Level Prediction

arXiv:2606.12126v1 Announce Type: new Abstract: Existing computational pathology methods predominantly operate within whole-slide image (WSI)-level multiple instance learning (MIL) paradigms, while pa

tutorialsarxiv-cs-cv

Agents All the Way Down; A Methodology for Building Custom AI Agents from Substrate to Production

arXiv:2606.11869v1 Announce Type: cross Abstract: Custom AI agents areagents that live inside their own application, talk to their own data and tools, enforce their own security boundaries, and carry

An Ontology-Guided Multi-Anchor Graph Retrieval Framework for Traffic Legal Liability Determination

arXiv:2606.11910v1 Announce Type: new Abstract: Traffic law liability determination is critical for assigning legal penalties, requiring the simultaneous identification of interdependent statutory pro

Augmenting Molecular Language Models with Local n-gram Memory

arXiv:2606.12113v1 Announce Type: cross Abstract: Transformer-based language models for SMILES strings suffer from a locality gap: standard character-level tokenization fragments chemically meaningful

safetyarxiv-cs-ai

Automated Creativity Evaluation of Language Models Across Open-Ended Tasks

arXiv:2606.11762v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved remarkable progress in language understanding, reasoning, and generation, sparking growing interest in thei

Beyond Fully Random Masking: Attention-Guided Denoising and Optimization for Diffusion Language Models

arXiv:2606.12273v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) offer an efficient alternative to autoregressive models through parallel decoding, yet existing post-training me

researcharxiv-cs-cl

Local Ai

Compiler-First State Space Duality and Portable O(1) Autoregressive Caching for Inference

arXiv:2603.09555v2 Announce Type: replace-cross Abstract: High-throughput Mamba-2 inference is usually tied to fused CUDA and Triton kernels, limiting portability across accelerator backends. We show

local-aiarxiv-cs-ai

Applications

DIRECT: When and Where Should You Allocate Test-Time Compute in Embodied Planners?

arXiv:2606.12402v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly deployed as high-level planners for embodied agents, with an emerging strategy of scaling test-time com

applicationsarxiv-cs-ai

DrivingAgent: Design and Scheduling Agents for Autonomous Driving Systems

arXiv:2606.12236v1 Announce Type: cross Abstract: Many autonomous driving systems are increasingly incorporating foundation models to improve generalization and handle long-tail scenarios. However, th

agentsarxiv-cs-cv

Evaluating and Combating the Impact of Concept Drift on the Performance of Machine Learning-Based Phishing Detection Systems

arXiv:2606.11471v1 Announce Type: cross Abstract: The expansion of the digital domain has resulted in a substantial increase in digital communication, with email emerging as one of the most prominent

EverydayGPT: Confidence-Gated Routing for Efficient and Safe Hybrid GPT-RAG Conversational QA

arXiv:2606.11212v1 Announce Type: new Abstract: Standard Retrieval-Augmented Generation (RAG) pipelines route every query through retrieval and generation unconditionally, incurring unnecessary comput

Family-Aware Residual Architecture for Predicting Quantum Circuit Simulation Performance

arXiv:2606.11620v1 Announce Type: cross Abstract: Approximate tensor-network simulators enable classical simulation of quantum circuits beyond the reach of exact methods, but selecting optimal approxi

Finding Multiple Interpretations in Datasets

arXiv:2606.12277v1 Announce Type: new Abstract: In this paper, we propose an approach to finding sets of similar-performing models (in terms of loss/accuracy measurements) with highly different contex

Applications

FOCUS on Contamination: Hydrology-Informed Noise-Aware Learning for Geospatial PFAS Mapping

arXiv:2502.14894v5 Announce Type: replace-cross Abstract: Per- and polyfluoroalkyl substances (PFAS) are persistent environmental contaminants with significant public health impacts, yet large-scale m

applicationsarxiv-cs-ai

Generalization Hacking: Models Can Game Reinforcement Learning by Preventing Behavioral Generalization

arXiv:2606.12016v1 Announce Type: cross Abstract: Model post-training, and in particular reinforcement learning (RL), is one of the primary mechanisms by which developers can shape models' values and

researcharxiv-cs-ai

Goal-Autopilot: A Verifiable Anti-Fabrication Firewall for Unattended Long-Horizon Agents

arXiv:2606.11688v1 Announce Type: cross Abstract: Long-horizon LLM agents are not trusted to run unattended: with no human watching, they confidently report success they never verified. We treat hones

HERO: Hindsight-Enhanced Reflection from Environment Observations for Agentic Self-Distillation

arXiv:2606.11559v1 Announce Type: new Abstract: Reinforcement learning typically improves multi-turn agent capabilities through the terminal outcome of the trajectories, which makes it difficult to de

safetyarxiv-cs-ai

How Seemingly Inconsequential Design Choices Dictate Performance of LLMs in Pathology

model-releasesarxiv-cs-cv

arXiv:2606.12407v1 Announce Type: new Abstract: General-purpose large language models (LLMs) are routinely used as baselines when evaluating specialized pathology models on whole-slide images (WSIs).

KinematicRL: A Sim-to-Real Reinforcement Learning Framework For Social Navigation With Kinodynamic Feasibility

arXiv:2606.12042v1 Announce Type: new Abstract: Deep Reinforcement Learning (DRL) has shown promise for social navigation, yet its real-world deployment remains hindered by a persistent sim-to-real ga

safetyarxiv-cs-ro

LLMs+Graphs: Toward Graph-Native, Synergistic AI Systems

arXiv:2606.11560v1 Announce Type: cross Abstract: Large Language Models (LLMs) have advanced rapidly, but their limitations in structured and multi-hop reasoning underscore the need for graph-native,

Lung-SRAD: Spectral-Aware Regularized Audio DASS with Dual-Axis Patch-Mix Contrastive Learning for Respiratory Sound Classification

arXiv:2606.11922v1 Announce Type: cross Abstract: Recent respiratory sound classification (RSC) studies largely rely on CLS-token driven self-attention architectures such as the Audio Spectrogram Tran

Applications

M4FC: a Multimodal, Multilingual, Multicultural, Multitask Real-World Fact-Checking Dataset

arXiv:2510.23508v3 Announce Type: replace Abstract: Existing real-world datasets for multimodal fact-checking have multiple limitations: they contain few instances, cover on only one or two languages,

applicationsarxiv-cs-cl

Modelling magnetic material properties with uncertainty-aware neural networks

model-releasesarxiv-cs-lg

arXiv:2606.11870v1 Announce Type: cross Abstract: Machine learning is increasingly applied to accelerate the discovery of novel materials by exploring large compositional and structural design spaces.

Multi-Agent Reasoning with Adaptive Worker Allocation for Stance Detection

arXiv:2606.11609v1 Announce Type: new Abstract: Stance detection requires identifying an author's position toward a target, often from short-form texts where stance is implicit, indirect, or rhetorica

Local Ai

MultiToP: Learning to Patch Visual Tokens to Mitigate Hallucinations in Video Large Multimodal Models

arXiv:2606.11792v1 Announce Type: cross Abstract: Video Large Multimodal Models have achieved remarkable progress in video understanding, yet they remain prone to hallucinations, where generated respo

local-aiarxiv-cs-ai

Overcoming State Inertia in Full-Duplex Spoken Language Models via Activation Steering

arXiv:2606.11386v1 Announce Type: cross Abstract: Full-duplex spoken language models (FD-SLMs) enable seamless speech interaction by allowing models to listen and speak simultaneously, yet the interna

Tutorials

Probabilistic Salary Prediction with Graph Attention Networks and a Mixture Density Network

arXiv:2606.11663v1 Announce Type: cross Abstract: Accurate salary prediction is critical for bridging the information gap between employers and job seekers in modern labor markets. Existing approaches

tutorialsarxiv-cs-lg

RelayFormer: A Unified Local-Global Attention Framework for Scalable Image and Video Manipulation Localization

arXiv:2508.09459v3 Announce Type: replace-cross Abstract: Visual manipulation localization (VML) aims to identify tampered regions in images and videos, a task that has become increasingly challenging

researcharxiv-cs-ai

Reminder that profiles are still one of the most powerful features in Hermes Agent that not everyone seems to have fully grasped. It's one o…

Reminder that profiles are still one of the most powerful features in Hermes Agent that not everyone seems to have fully grasped. It's one of those things that's obvious in hindsight, but yeah - tryin

agentsnous-research--x

RLCSD: Reinforcement Learning with Contrastive On-Policy Self-Distillation

arXiv:2606.11709v1 Announce Type: cross Abstract: On-policy self-distillation (OPSD) provides dense, token-level supervision for reasoning models by aligning a model's own distribution with the distri

safetyarxiv-cs-cl

Runtime Skill Audit: Targeted Runtime Probing for Agent Skill Security

arXiv:2606.11671v1 Announce Type: cross Abstract: Agent skills let LLM agents reuse instructions, resources, tools, and workflows, but they also create a new place for malicious behavior to hide. A sk

Semantic Grading of Written Answers in Low-Resource Language Bangla Using a Fine-Tuned Lightweight Language Model

arXiv:2606.11931v1 Announce Type: new Abstract: Bangla is among the world's most widely spoken languages, yet it remains underserved in educational NLP research. In many remote and rural regions, acce

researcharxiv-cs-cl

Sovereign Assurance Boundary: Certificate-Bound Admission for Agentic Infrastructure

arXiv:2606.11632v1 Announce Type: cross Abstract: Agentic infrastructure introduces a critical control-plane authorization problem: non-deterministic reasoning systems can propose high-stakes mutation

safetyarxiv-cs-ai

Space-sampled Value Decay: Forgetting Mechanisms for Non-stationary Deep Reinforcement Learning

arXiv:2606.11797v1 Announce Type: new Abstract: Studies on rodents such as mice have shown the capabilities to adapt their behavior when dealing with changing parameters (``drift'') of the environment

Steering Multirobot Behavior via Closed-Loop Affine Activation Editing

arXiv:2606.11489v1 Announce Type: new Abstract: Real-world robots need to adapt their behavior beyond the envelope of their pre-trained policy. Policy finetuning or retraining are options, but they ri

safetyarxiv-cs-ro

Towards Fully Automated Exam Grading: Fairness-Aware Recognition of Handwritten Answers with Foundation Models

arXiv:2606.11477v1 Announce Type: cross Abstract: Correcting handwritten exams by hand is time-consuming and error-prone, particularly for large cohorts, while fully digital exams tend to force a dida