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MULTI: Disentangling Camera Lens, Sensor, View, and Domain for Novel Image Generation

model-releasesarxiv-cs-cv

arXiv:2605.12134v1 Announce Type: new Abstract: Recent text-to-image models produce high-quality images, yet text ambiguity hinders precise control when specific styles or objects are required. There

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Multi-modal Bayesian Neural Network Surrogates with Conjugate Last-Layer Estimation

DGX agent

arXiv:2509.21711v2 Announce Type: replace-cross Abstract: As data collection and simulation capabilities advance, multi-modal learning, the task of learning from multiple modalities and sources of dat

tutorialsarxiv-cs-lg

13 May 2026

Multi-Narrow Transformation as a Single-Model Ensemble: Boundary Conditions, Mechanisms, and Failure Modes

arXiv:2605.11530v1 Announce Type: new Abstract: Single-model ensembles (SMEs) have attracted attention as a way to approximate some of the benefits of deep ensembles within a single network. However,

Multi-Stream LLMs: Unblocking Language Models with Parallel Streams of Thoughts, Inputs and Outputs

arXiv:2605.12460v1 Announce Type: cross Abstract: The continued improvements in language model capability have unlocked their widespread use as drivers of autonomous agents, for example in coding or c

agentsarxiv-cs-cl

Multi-Task Representation Learning for Conservative Linear Bandits

arXiv:2605.12176v1 Announce Type: new Abstract: This paper presents the Constrained Multi-Task Representation Learning (CMTRL) framework for linear bandits. We consider T linear bandit tasks in a d di

Multi-Timescale Conductance Spiking Networks: A Sparse, Gradient-Trainable Framework with Rich Firing Dynamics for Enhanced Temporal Processing

arXiv:2605.11835v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) promise low-power event-driven computation for temporally rich tasks, but commonly used neuron models often trade off g

researcharxiv-cs-lg

Multi-Variable Conformal Prediction: Optimizing Prediction Sets without Data Splitting

arXiv:2605.12341v1 Announce Type: cross Abstract: Conformal prediction constructs prediction sets with finite-sample coverage guarantees, but its calibration stage is structurally constrained to a sca

agentsarxiv-cs-lg

Multimodal Abstractive Summarization of Instructional Videos with Vision-Language Models

arXiv:2605.11959v1 Announce Type: cross Abstract: Multimodal video summarization requires visual features that align semantically with language generation. Traditional approaches rely on CNN features

safetyarxiv-cs-cl

Local Ai

Muon is Not That Special: Random or Inverted Spectra Work Just as Well

arXiv:2605.11181v1 Announce Type: new Abstract: The recent empirical success of the Muon optimizer has renewed interest in non-Euclidean optimization, typically justified by similarities with second-o

local-aiarxiv-cs-lg

MuonQ: Enhancing Low-Bit Muon Quantization via Directional Fidelity Optimization

arXiv:2605.11396v1 Announce Type: new Abstract: The Muon optimizer has emerged as a compelling alternative to Adam for training large language models, achieving remarkable computational savings throug

Musk v. Altman: Microsoft executive Michael Wetter testifies that Microsoft has spent $100B+ on OpenAI, including its investments and to build infrastructure (Bloomberg)

Bloomberg: Musk v. Altman: Microsoft executive Michael Wetter testifies that Microsoft has spent 100B+ on OpenAI, including its investments and to build infrastructure — Microsoft Corp. has spent more

industrytechmeme

Mythos Preview is the first AI model to complete both of AISI's cyber ranges, which measure models' cyberattack capabilities; GPT-5.5 solved only one of them (AI Security Institute)

AI Security Institute: Mythos Preview is the first AI model to complete both of AISI's cyber ranges, which measure models' cyberattack capabilities; GPT-5.5 solved only one of them — In February 2026,

model-releasestechmeme

NASA provides some details about Artemis III, but hard decisions remain

NASA is moving quickly to define next year's Artemis III mission in Earth orbit, a crewed flight that will test rendezvous and docking capabilities between the agency's Orion spacecraft and commercial

industryars-technica

Tutorials

Natural Language Processing in the Legal Domain

arXiv:2302.12039v2 Announce Type: replace Abstract: We summarize the current state of the field of NLP & Law with a specific focus on recent technical and substantive developments. To support our anal

tutorialsarxiv-cs-cl

Nautilus: From One Prompt to Plug-and-Play Robot Learning

model-releasesarxiv-cs-ro

arXiv:2605.11665v1 Announce Type: new Abstract: Robot learning research is fragmented across policy families, benchmark suites, and real robots; each implementation is entangled with the others in a c

NavOL: Navigation Policy with Online Imitation Learning

model-releasesarxiv-cs-ro

arXiv:2605.11762v1 Announce Type: new Abstract: Learning robust navigation policies remains a core challenge in robotics. Offline imitation learning suffers from distribution shift and compounding err

Nebius snaps up Clarifai’s compute orchestration tech and talent to enhance AI inference

Dutch artificial intelligence infrastructure giant Nebius Group N.V. said today it’s recruiting the core engineering team from AI orchestration software firm Clarifai Inc. in an effort to boost its ma

industrysiliconangle

Netflix says its ad tier now has 250M monthly active viewers, up from 94M in 2025, and is expanding to 15 new countries, as it tests an ad personalization tool (Emma Roth/The Verge)

Emma Roth / The Verge: Netflix says its ad tier now has 250M monthly active viewers, up from 94M in 2025, and is expanding to 15 new countries, as it tests an ad personalization tool — The streaming s

industrytechmeme

Neural ARFIMA model for forecasting BRIC exchange rates with long memory

arXiv:2509.06697v2 Announce Type: replace-cross Abstract: Accurate forecasting of exchange rates remains a persistent challenge, particularly for emerging economies such as Brazil, Russia, India, and

Local Ai

Neural-Schwarz Tiling for Geometry-Universal PDE Solving at Scale

arXiv:2605.12343v1 Announce Type: new Abstract: Most learned PDE solvers follow a global-surrogate paradigm: a neural operator is trained to map full problem descriptions to full solution fields for a

local-aiarxiv-cs-lg

Neural Statistical Functions

arXiv:2605.11327v1 Announce Type: new Abstract: Classical deep learning typically operates on individual cases. Despite its success, real-world usage often requires repeated inference to estimate stat

applicationsarxiv-cs-lg

New paper in Nature. The more a government controls its domestic media, the more it dominates AI training data, the more pro-regime outputs …

New paper in Nature. The more a government controls its domestic media, the more it dominates AI training data, the more pro-regime outputs we get from AI. By scraping the open web, LLMs are unwitting

safetygary-marcus--x

New paper: research agenda for secret loyalties Imagine a frontier model that has been trained to covertly advance a specific actor's intere…

New paper: research agenda for secret loyalties Imagine a frontier model that has been trained to covertly advance a specific actor's interests (a nation-state, a CEO, an adversary). @joemkwon argues

industryemad-mostaque--x

Newton's Lantern: A Reinforcement Learning Framework for Finetuning AC Power Flow Warm Start Models

arXiv:2605.11102v1 Announce Type: new Abstract: Neural warm starts can sharply reduce the number of Newton-Raphson iterations required to solve the AC power flow problem, but existing supervised appro

NexOP: Joint Optimization of NEX-Aware k-space Sampling and Image Reconstruction for Low-Field MRI

arXiv:2605.11583v1 Announce Type: cross Abstract: Modern low-field magnetic resonance imaging (MRI) technology offers a compelling alternative to standard high-field MRI, with portable, low-cost syste

applicationsarxiv-cs-cv

@Nima292 LLMs are not AGI but will lead to some job losses; true AGI would likely lead to many more.

Gary Marcus argues that current large language models (LLMs) do not constitute artificial general intelligence (AGI), though they will cause some job displacement. He suggests that true AGI, if achiev

safetygary-marcus--x

No More, No Less: Task Alignment in Terminal Agents

arXiv:2605.12233v1 Announce Type: new Abstract: Terminal agents are increasingly capable of executing complex, long-horizon tasks autonomously from a single user prompt. To do so, they must interpret

no remorse, just further evasion. so slick; so dangerous.

no remorse, just further evasion. so slick; so dangerous. 🚨 SEVEN OPENAI INSIDERS HAVE ACCUSED SAM ALTMAN OF LYING Today on cross, Musk's lawyer walked Altman through all of them: >Ilya Sutskever (co-

safetygary-marcus--x

NOFE -- Neural Operator Function Embedding

arXiv:2605.11970v1 Announce Type: new Abstract: Most dimensionality reduction methods treat data as discrete point clouds, ignoring the continuous domain structure inherent to many real-world processe

applicationsarxiv-cs-lg

Not How Many, But Which: Parameter Placement in Low-Rank Adaptation

model-releasesarxiv-cs-cl

arXiv:2605.12207v1 Announce Type: cross Abstract: We study the extit{parameter placement problem}: given a fixed budget of k trainable entries within the B matrix of a LoRA adapter (A frozen), does th

Not to mention 7 blog posts dropped today, including a new Deep Agents version with significant improvements… Especially excited about the C…

Not to mention 7 blog posts dropped today, including a new Deep Agents version with significant improvements… Especially excited about the Code Interpreter feature which is a sneaky powerful feature e

agentsharrison-chase--x

Not Worth Mentioning? A Pilot Study on Salient Proposition Annotation

arXiv:2603.27358v2 Announce Type: replace Abstract: Despite a long tradition of work on extractive summarization, which by nature aims to recover the most important propositions in a text, little work

researcharxiv-cs-cl

Hardware

NVIDIA, Ineffable Intelligence Team Up to Build the Future of Reinforcement Learning Infrastructure

Reinforcement-learning agents — AI systems that learn by trial and error — can convert computation into new knowledge. That’s the focus of a new engineering-level collaboration between NVIDIA and Inef

hardwarenvidia-blog

@nvidia Nemotron native support in Deep Agents 0.6 #interrupt #langchain

model-releasesharrison-chase--x

NVIDIA Nemotron models received native support integration in Deep Agents version 0.6, enabling improved language model capabilities within the LangChain framework. This update allows developers to le

Observability going from 'read the traces' to 'the traces read themselves and tell you what to fix.' That's the feedback loop most agent tea…

Observability going from 'read the traces' to 'the traces read themselves and tell you what to fix.' That's the feedback loop most agent teams are missing. 🚀Launching: LangSmith Engine LangSmith Engin

agentsharrison-chase--x

Ofcom fines an unnamed suicide forum £950K, the largest OSA fine so far, for hosting illegal content accessible in the UK; the forum is linked to 130+ deaths (Sam Tabahriti/Reuters)

Sam Tabahriti / Reuters: Ofcom fines an unnamed suicide forum £950K, the largest OSA fine so far, for hosting illegal content accessible in the UK; the forum is linked to 130+ deaths — Britain's commu

industrytechmeme

Off-Policy Learning with Limited Supply

arXiv:2603.18702v3 Announce Type: replace Abstract: We study off-policy learning (OPL) in contextual bandits, which plays a key role in a wide range of real-world applications such as recommendation s

Off to an amazing start at @LangChain Interrupt 🪁🦜 Including: 📣 Shoutout from @hwchase17 during the opening keynote! 🪁 CopilotKit booth …

Off to an amazing start at @LangChain Interrupt 🪁🦜 Including: 📣 Shoutout from @hwchase17 during the opening keynote! 🪁 CopilotKit booth with the best staff, demos and merch 🍸 Agents After Dark Happy H

agentsharrison-chase--x

Offline Constrained Reinforcement Learning under Partial Data Coverage

arXiv:2505.17506v2 Announce Type: replace-cross Abstract: We study offline constrained reinforcement learning with general function approximation in discounted constrained Markov decision processes. P

Offline Policy Evaluation for Manipulation Policies via Discounted Liveness Formulation

arXiv:2605.11479v1 Announce Type: new Abstract: Policy evaluation is a fundamental component of the development and deployment pipeline for robotic policies. In modern manipulation systems, this probl

safetyarxiv-cs-ro

OGLS-SD: On-Policy Self-Distillation with Outcome-Guided Logit Steering for LLM Reasoning

arXiv:2605.12400v1 Announce Type: new Abstract: We study {on-policy self-distillation} (OPSD), where a language model improves its reasoning ability by distilling privileged teacher distributions alon

OmniHumanoid: Streaming Cross-Embodiment Video Generation with Paired-Free Adaptation

arXiv:2605.12038v1 Announce Type: new Abstract: Cross-embodiment video generation aims to transfer motions across different humanoid embodiments, such as human-to-robot and robot-to-robot, enabling sc

applicationsarxiv-cs-cv

OmniNFT: Modality-wise Omni Diffusion Reinforcement for Joint Audio-Video Generation

arXiv:2605.12480v1 Announce Type: new Abstract: Recent advances in joint audio-video generation have been remarkable, yet real-world applications demand strong per-modality fidelity, cross-modal align

safetyarxiv-cs-cv

OmniThoughtVis: A Scalable Distillation Pipeline for Deployable Multimodal Reasoning Models

arXiv:2605.11629v1 Announce Type: new Abstract: Recent multimodal large language models (MLLMs) have shown strong chain-of-thought (CoT) reasoning ability on vision-language tasks, but their direct de

applicationsarxiv-cs-cl

On my way to Beijing in Air Force One

Elon Musk posted on X about traveling to Beijing aboard Air Force One, indicating a trip to China's capital. The post suggests either an official government delegation or a significant business visit

industryelon-musk--x

On Predicting the Post-training Potential of Pre-trained LLMs

arXiv:2605.11978v1 Announce Type: new Abstract: The performance of Large Language Models (LLMs) on downstream tasks is fundamentally constrained by the capabilities acquired during pre-training. Howev

researcharxiv-cs-cl

On Problems of Implicit Context Compression for Software Engineering Agents

arXiv:2605.11051v1 Announce Type: cross Abstract: LLM-based Software Engineering agents face a critical bottleneck: context length limitations cause failures on complex, long-horizon tasks. One promis

agentsarxiv-cs-cl

On the Approximation Complexity of Matrix Product Operator Born Machines

arXiv:2605.11471v1 Announce Type: new Abstract: Matrix product operator Born machines (MPO-BMs) are tractable tensor-network models for probabilistic modeling, but their efficient approximation capabi

researcharxiv-cs-lg