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Motion Artifact-Aware Self-Supervised Representation Learning for 3D Brain MRI Motion Artifact Reduction

arXiv:2608.10170v1 Announce Type: new Abstract: Patient motion remains a source of image degradation in brain MRI, leading to signal loss, blurring, and geometric distortion that compromise quantitati

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MRIComp4Flow: Compression of 3D Brain MRI for Training Multi-Modal Generative Models

DGX agent

arXiv:2608.10291v1 Announce Type: cross Abstract: Large-scale multi-modal MRI datasets impose substantial storage and I/O costs, limiting the training of 3D generative models on commodity infrastructu

tutorialsarxiv-cs-ai

12 Aug 2026

MT-PingEval: Evaluating Multi-Turn Collaboration with Private Information Games

arXiv:2602.24188v2 Announce Type: replace Abstract: We present a scalable and verifiable methodology for evaluating language models in multi-turn interactions, using a suite of collaborative games tha

agentsarxiv-cs-cl

Multi-Granular Rationale-Guided Molecular LLM for Property Prediction

arXiv:2608.10480v1 Announce Type: new Abstract: Large language models (LLMs) are widely applied across chemical tasks, such as molecular property prediction, which underpins drug discovery. Molecular

Multi-Level Evidence Aggregation for Robust Facial Phenotype Retrieval in Rare Genetic Disorder Prioritization

arXiv:2608.11037v1 Announce Type: new Abstract: AI-assisted facial phenotyping supports rare genetic disorder prioritization by retrieving visually similar diagnosed cases from facial image reference

Multi-View Relational Distillation for Spatial Reasoning with Vision-Language Models

arXiv:2608.10864v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved strong image and video understanding, yet their visual-spatial representations remain geometrically fragile,

safetyarxiv-cs-cv

Multiclass Sentiment Analysis for Identifying Political Viewpoints

arXiv:2608.11049v1 Announce Type: cross Abstract: The rapid growth of social media has created vast amounts of political discourse, which provides valuable opportunities to analyze public opinions and

Multilingual Embedding Probes Fail to Generalize Across Learner Corpora

arXiv:2604.07095v2 Announce Type: replace Abstract: Do multilingual embedding models encode a language-general representation of proficiency? We investigate this by training linear and non-linear prob

researcharxiv-cs-cl

Multimodal Ambivalence and Hesitancy Recognition via Cross-Attention and Gated Fusion

arXiv:2607.15779v2 Announce Type: replace Abstract: We present a multimodal framework for Ambivalence/Hesitancy (A/H) recognition in video, developed for the ABAW11 challenge at ECCV 2026. The propose

Local Ai

MultiModal Code-Switching: Interleaving Visual Objects into Language for Explicit Object-Level Alignment

arXiv:2608.11167v1 Announce Type: cross Abstract: Existing Multimodal Large Language Models (MLLMs) predominantly rely on image-text pairs for modality alignment pretraining, mapping global image repr

local-aiarxiv-cs-cl

Multimodal Item Parameter Estimation using Simulated Response Probabilitie

arXiv:2608.10154v1 Announce Type: cross Abstract: We present results from reconstructing multiple-choice model (MCM) and three-parameter logistic (3PL) model curves using a fine-tuned multimodal large

Multiplayer Nash Preference Optimization

arXiv:2509.23102v4 Announce Type: replace Abstract: Reinforcement learning from human feedback (RLHF) has emerged as the standard paradigm for aligning large language models with human preferences. Ho

Multiple Scale Latents for Learned Image Compression

arXiv:2608.10952v1 Announce Type: new Abstract: Most learned image compression systems rely on a single latent representation combined with a hyperprior, which limits their ability to efficiently capt

MUSE: A Full-Text Cross-Domain Knowledge Base of Scientific Problems, Solutions, and Rationales

arXiv:2608.10974v1 Announce Type: new Abstract: Scientific papers contain fine-grained records of problem solving: authors mention technical obstacles and methods that were used to address them, often

researcharxiv-cs-cl

Muse Glimmer is live on Fireworks. The new open-weight model from Meta Superintelligence Labs is a 30B dense model built for always-on agent…

Muse Glimmer is live on Fireworks. The new open-weight model from Meta Superintelligence Labs is a 30B dense model built for always-on agents that reason across many sequential tool calls and can reco

agentsfireworks-ai--x

MVTrack: Ultrafast Appearance-Free Moving Object Tracking from Compressed Bitstreams

arXiv:2608.10790v1 Announce Type: cross Abstract: Deploying modern video trackers at scale is bottlenecked by the computational cost of RGB-based object detectors. To this end, we present MVTrack, an

myMediWhisper: Construction of Burmese Medical Speech Corpus and Whisper Fine-Tuning for Clinical Dialogue ASR

model-releasesarxiv-cs-cl

arXiv:2608.11036v1 Announce Type: new Abstract: Although Whisper models benefit from large-scale multilingual pre-training, their performance on Burmese medical speech remains limited. This work prese

Narrative Keyframing for Generative Creative Writing

arXiv:2608.10337v1 Announce Type: cross Abstract: We introduce narrative keyframing, an interaction technique for AI-assisted creative writing that lets writers specify different types of narrative co

Applications

Navigating in Uncertain Environments with Heterogeneous Visibility

arXiv:2603.03495v2 Announce Type: replace Abstract: Navigating an environment with uncertain connectivity requires a strategic balance between minimizing the cost of traversal and seeking information

applicationsarxiv-cs-ro

Navigating the Proximity-Safety Balance: Constraint Decomposition for Human Following in Pedestrian Crowds

arXiv:2608.10056v1 Announce Type: cross Abstract: Following a target human in crowded environments involves an inherent conflict between staying close to the target and navigating safely among surroun

Navigation Alone Is Not Enough: Evaluating Explanatory Assistive UI Agents

arXiv:2608.09944v1 Announce Type: cross Abstract: Modern web interfaces are increasingly difficult to use with screen readers, particularly when pages update dynamically or hide important structure be

Neural Introspection Gating for Adaptive KV-Cache Reuse in Vision-Language-Action Models

model-releasesarxiv-cs-cv

arXiv:2608.10824v1 Announce Type: cross Abstract: Vision-Language-Action(VLA) models map camera images and language instructions directly to motor commands through a single autoregressive transformer.

Hardware

Neuroevolution Arena: Nested Ecological Evaluation of Update-and-Inheritance Regimes across Neural Architectures

arXiv:2608.10323v1 Announce Type: new Abstract: Competitive artificial-life systems can rank trained controllers differently under training and ecological evaluation. We present Neuroevolution Arena,

hardwarearxiv-cs-ai

Never Stop Speaking: a Denial-of-Service Attack on End-to-End Speech Language Models

arXiv:2608.10405v1 Announce Type: cross Abstract: Many studies have shown that specially crafted inputs can induce large language models (LLMs) to generate excessively long outputs, resulting in signi

New Muse-Glimmer-30B SoTA Quants - hopefully a new lineup :)

model-releasesr-localllama

Hey Folks, I've been making quants for a while - recently I took a short break to get into hardcore research (submitted my first EMNLP paper during it!). Along the way, I built up a little arsenal of

No Free Labels: Limitations of LLM-as-a-Judge Without Human Grounding

model-releasesarxiv-cs-cl

arXiv:2503.05061v3 Announce Type: replace Abstract: Reliable evaluation of large language models (LLMs) is critical as their deployment rapidly expands, particularly in high-stakes domains such as bus

Nonlinear Model Predictive Control via Sequential Convex Programming for Drone-to-Drone Docking

arXiv:2608.10542v1 Announce Type: new Abstract: Autonomous mid-air docking of multi-rotor vehicles under disturbance-driven target motion poses a constrained non-linear trajectory optimization challen

agentsarxiv-cs-ro

Nonlinear multi-study sparse factor analysis

arXiv:2601.18128v2 Announce Type: replace-cross Abstract: High-dimensional data often exhibit variation that can be captured by lower-dimensional factors. For high-dimensional data from multiple studi

tutorialsarxiv-cs-lg

NullEdit: Stealthy Image Protection via VLM Condition Redirection

model-releasesarxiv-cs-cv

arXiv:2608.10870v1 Announce Type: new Abstract: Modern image editors combine vision-language models (VLMs) with diffusion transformer backbones to modify a single reference image according to instruct

Nutrition Data Infrastructure for the AI Era: Operationalizing FAIR for Agent-Mediated Research

arXiv:2608.10363v1 Announce Type: new Abstract: AI agents can accelerate nutrition research, but their analyses inherit the identity, semantic, and release ambiguities of the underlying data. We prese

Hardware

NVIDIA AI Factory Compute Is Becoming an Investable Asset Class

We announced partnerships with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR to establish independent financing platforms designed to mobilize over $500 billion of third-party capit

hardwarenvidia-blog

NVIDIA CEO Tops Glassdoor’s 2026 List of Best CEOs

model-releasesnvidia-blog

NVIDIA founder and CEO Jensen Huang is ranked No. 1 on Glassdoor’s Best CEOs list for 2026. In the just-released ranking, recognition is earned directly from the people who know their leadership the b

OAA: Three Phases of Vocal Guidance in Human-Drone Teleoperation

arXiv:2608.10651v1 Announce Type: new Abstract: Voice-guided teleoperation requires systems that adapt to the evolving dynamics of human guidance. Yet most voice-controlled robot systems treat spoken

tutorialsarxiv-cs-ro

Observational Policy Ranking for SMB Financial Guidance from Multi-Action Accounting Logs

arXiv:2608.10050v1 Announce Type: new Abstract: Small and medium-sized businesses need timely financial guidance, yet historical accounting logs record self-selected and often co-occurring business ch

safetyarxiv-cs-lg

Of course the ChatGPT dog cancer vaccine spawned a startup

Remember that much-hyped story about an Australian tech entrepreneur using ChatGPT, Grok, and other AI tools to craft a personalized cancer vaccine for his dog? Well, surprise: he's launched a startup

tutorialsthe-verge-ai

Off-Axis, On Purpose: Where a Transformer Computes Concepts and Why it Does So

arXiv:2608.10251v1 Announce Type: new Abstract: A transformer's answer lives on one axis: the direction its unembedding reads. Its intermediate states largely do not, and that off-axis position is usu

researcharxiv-cs-cl

OmniVTA: Visuo-Tactile World Modeling for Contact-Rich Robotic Manipulation

arXiv:2603.19201v3 Announce Type: replace Abstract: Contact-rich manipulation tasks, such as wiping and assembly, require accurate perception of contact forces, friction changes, and state transitions

safetyarxiv-cs-ro

On Solomonoff Induction in Large Language Models and the Limits of Self-Improving: The Singularity Is Not Near Without Symbolic Model Synthesis

arXiv:2601.05280v3 Announce Type: replace-cross Abstract: On the one hand, the question of whether large language models (LLMs) are Solomonoff induction estimators has become an explicit question at t

On the Importance of Geometric Nonlinearity and Temperature-Dependent Properties in Multi-Material Thermo-Mechanical Topology Optimization

arXiv:2608.10344v1 Announce Type: cross Abstract: Thermo-mechanical compliant devices are commonly designed with small-strain linear elasticity and temperature-independent material properties, even th

safetyarxiv-cs-lg

On the Limitations of Cross-Lingual Consistency in Multilingual Text-to-image Generation

arXiv:2608.11002v1 Announce Type: cross Abstract: Text-to-image (T2I) generation has achieved remarkable progress in recent years. However, existing research has largely focused on English-only settin

On The Statistical Limits of Self-Improving Agents

arXiv:2510.04399v3 Announce Type: replace Abstract: We develop a learning-theoretic framework for analyzing self-improving agents by decomposing self-modification into five axes. Within this framework

On Understanding, Identifying, and Mitigating Vulnerabilities in Agentic Large Language Models

arXiv:2608.10530v1 Announce Type: cross Abstract: Large Language Models (LLMs) have undergone a shift from stateless conversational interfaces to autonomous agents capable of multi-step planning, tool

agentsarxiv-cs-ai

Once Poisoned, Arbitrarily Controlled: A Programmable Backdoor in VLMs

arXiv:2608.10959v1 Announce Type: new Abstract: Existing vision-language model (VLM) backdoors are usually treated as static vulnerabilities: one-to-one and N-to-N attacks bind one or more triggers to

tutorialsarxiv-cs-cv

OpenAI VP of Global Policy Ann O'Leary says AI policy in the US is anchored in the states and informed by California's AI transparency law passed in 2025 (Chase DiFeliciantonio/Politico)

Chase DiFeliciantonio / Politico: OpenAI VP of Global Policy Ann O'Leary says AI policy in the US is anchored in the states and informed by California's AI transparency law passed in 2025 — SACRAMENTO

safetytechmeme

OpenDPDv2: A Unified Learning and Optimization Framework for Neural Network Digital Predistortion

arXiv:2507.06849v3 Announce Type: replace-cross Abstract: Neural network (NN)-based Digital Predistortion (DPD) improves linearization for wideband radio frequency (RF) power amplifiers (PAs) but ofte

OpenPM: Auditable Point-in-Time Evaluation for LLM Portfolio-Management Agents

arXiv:2608.09988v1 Announce Type: cross Abstract: Large language models are increasingly used to read markets, assess risk, and allocate capital. However, reported results for LLM trading agents can b

agentsarxiv-cs-cl

Operationalising Relative Causal Knowledge: Backbone Identifiability from Private Reports on a Shared Outcome

arXiv:2608.10664v1 Announce Type: new Abstract: The Relativity of Causal Knowledge (RCK) explains how a network of agents with different structural causal models can exchange causal knowledge through

Optimal Stopping of Self-Refining Foundation Models

arXiv:2608.10729v1 Announce Type: cross Abstract: Foundation models can improve their outputs through a self-refinement process driven by external feedback. In this process, the model is embedded in a