Search: “models”

Going to cross 3M public models & 1M public datasets on @huggingface in a few days. Open-source AI is on fire!

Hugging Face was approaching milestones of 3 million public models and 1 million public datasets on its platform, reflecting rapid growth in open-source AI resources. The announcement highlights the e

industryclem-delangue--x

22 Jun 2026

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Industry

Is there a market where folk are predicting when Reflection AI will drop their first model This is probably as much compute as currently use…

DGX agent

Is there a market where folk are predicting when Reflection AI will drop their first model This is probably as much compute as currently used by all the Chinese open source companies together (more ad

industryemad-mostaque--x

22 Jun 2026

My version of AI mania is when I get a spidey feeling that the models have changed. Opus 4.8 feels very different today.

industryallie-k--miller--x

Allie K. Miller expresses subjective observations about perceiving changes in Claude Opus 4.8's behavior or capabilities, describing an intuitive sense ('spidey feeling') that the model feels notably

22 Jun 2026

Sources: Meta internally exposed data from its employee-tracking program meant to help train its AI models, including full prompts and private conversations (Wired)

Wired: Sources: Meta internally exposed data from its employee-tracking program meant to help train its AI models, including full prompts and private conversations — Employees had previously raised co

industrytechmeme

22 Jun 2026

Hardware

MaineCoon is the first video model that focuses on social interactions: facial expressions, emotions, fluid conversation, audio-lip sync, et…

hardwarefrancois-chollet--x

MaineCoon is the first video model that focuses on social interactions: facial expressions, emotions, fluid conversation, audio-lip sync, etc. Really impressive inference specs: 22B params, 47.5 FPS o

21 Jun 2026

API prices of key AI models: US vs China

This post likely compares the pricing of major AI model APIs between the United States and China, highlighting cost differences that reflect different market conditions, regulatory environments, and c

industryclem-delangue--x

19 Jun 2026

Adapting Vision-Language Models from Iconic to Inclusive for Multi-Label Recognition Without Labels

arXiv:2606.11626v1 Announce Type: new Abstract: Understanding multi-label images remains a challenging task in computer vision. With the rapid progress of vision-language multimodal learning, vision-l

safetyarxiv-cs-cv

Agents

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

agentsarxiv-cs-ai

AVIS: Adaptive Test-Time Scaling for Vision-Language Models

arXiv:2606.11576v1 Announce Type: cross Abstract: Modern Vision-Language Models (VLMs) benefit from chain-of-thought prompting and test-time scaling, but these gains often come with prohibitive infere

Can AI Reason Like an Urban Planner? Benchmarking Large Language Models Against Professional Judgment

arXiv:2606.11678v1 Announce Type: new Abstract: Problem, Research Strategy, and Findings: The rise of large language models (LLMs) raises a key question for urban planning: which forms of professional

Detecting AI-Generated Content on Social Media with Multi-modal Language Models

arXiv:2606.11200v1 Announce Type: new Abstract: Generative AI has enabled the creation of photorealistic images and videos that are increasingly disseminated on social media, often used for spam, misi

applicationsarxiv-cs-cl

Detecting Sensitive Personal Information in Japanese Pre-Training Corpora for Large Language Models

arXiv:2606.12114v1 Announce Type: new Abstract: Sensitive personal information can appear in large-scale pre-training corpora for large language models (LLMs). Detecting and filtering such information

researcharxiv-cs-cl

Diffusion-based Cumulative Adversarial Purification for Vision Language Models

arXiv:2506.03933v2 Announce Type: replace-cross Abstract: Vision Language Models (VLMs) have shown remarkable capabilities in multimodal understanding, yet their susceptibility to adversarial perturba

applicationsarxiv-cs-ai

Evaluating Bias in Phoneme-Based Automatic Speech Recognition Systems: An Analysis of IPA Transcription Models

arXiv:2606.11639v1 Announce Type: new Abstract: The popularization of automatic speech recognition (ASR) systems has increased exploration of the demographic biases related to race, age, gender, and a

I built a 100% local, CPU-only voice loop for Ollama — talk to your models hands-free (Silero VAD + Parakeet STT + Supertonic TTS 3)

A developer created a fully local, CPU-based voice interface for Ollama that enables hands-free conversation with AI models by combining three open-source components: Silero VAD (voice activity detect

local-air-ollama

Language Shapes Mental Health Evaluations in Large Language Models

arXiv:2603.06910v2 Announce Type: replace Abstract: Multilingual large language models (LLMs) are increasingly used in socially sensitive mental health contexts, including support chatbots, screening,

researcharxiv-cs-cl

On the Optimal Reasoning Length for RL-Trained Language Models

arXiv:2602.09591v3 Announce Type: replace-cross Abstract: Reinforcement learning substantially improves reasoning in large language models, but it also tends to lengthen chain-of-thought outputs and i

Prediction-Powered Risk Monitoring of Deployed Models for Detecting Harmful Distribution Shifts

arXiv:2602.02229v2 Announce Type: replace Abstract: We study the problem of monitoring model performance in dynamic environments where labeled data are limited. To this end, we propose prediction-powe

researcharxiv-cs-lg

Steering Where to Listen: Instruction-Based Activation Steering Redirects Temporal Attention in Large Audio-Language Models

arXiv:2606.11400v1 Announce Type: cross Abstract: Large Audio-Language Models (LALMs) excel at audio understanding but expose little about where in an audio signal they attend. We introduce instructio

Access OpenAI models and Codex through your Oracle cloud commitment

OpenAI models and Codex are available to Oracle Cloud customers through an integrated partnership, allowing users to access these AI capabilities within their existing Oracle cloud infrastructure and

applicationsopenai

An LLM-Native Psychometric Instrument Does Not Predict LLM Behavior: Evidence Across 25 Models

arXiv:2606.09843v1 Announce Type: cross Abstract: Large language models (LLMs) produce stable self-reports on personality inventories, but these self-reports do not predict observed behavior. Whether

Attention-Discounted Adaptive Sampler for Masked Diffusion Language Models

arXiv:2606.10829v1 Announce Type: cross Abstract: Masked diffusion language models can reduce inference steps by revealing multiple tokens per denoising iteration, but this parallelism is fragile: pos

Blind denoising diffusion models and the blessings of dimensionality

arXiv:2602.09639v2 Announce Type: replace Abstract: Denoising diffusion models (DDMs) are state-of-the-art methods for learning densities from data across numerous domains, yet many aspects of the tra

researcharxiv-cs-lg

Agents

Business World Model

arXiv:2606.10044v1 Announce Type: new Abstract: Businesses are increasingly adopting AI-enabled tools to improve productivity, reduce costs, and enhance products and services. However, the transformat

agentsarxiv-cs-ai

Model Releases

Can Multi-Agent LLMs Identify Their Peers? Stylometric Fingerprinting in Role-Constrained Political Analysis

model-releasesarxiv-cs-ai

arXiv:2606.09854v1 Announce Type: cross Abstract: Multi-agent large language model (LLM) pipelines for political statement analysis are vulnerable to peer-preservation bias: models tend to protect pee

Deep Generative Model for Human Mobility Behavior

arXiv:2510.06473v3 Announce Type: replace-cross Abstract: Understanding and modeling human mobility is central to challenges in transport planning, sustainable urban design, and public health. Despite

Improving PET/CT-Based Whole-Body Lesion Segmentation Using Prediction Uncertainty-Augmented Models

arXiv:2606.10115v1 Announce Type: new Abstract: Accurate lesion segmentation from whole-body Positron Emission Tomography (PET)/Computed Tomography (CT) scans is essential for cancer staging and treat

local-aiarxiv-cs-cv

Learning the Universe: Posterior Reliability of Neural Generative Models in High-Dimensional Field-Level Inference of Cosmic Initial Conditions

arXiv:2606.10023v1 Announce Type: cross Abstract: Accurate posterior estimation is central to scientific inference, as uncertainties determine what can be reliably learned from observational data. Whi

applicationsarxiv-cs-lg

Agents

Lium raises $5.5M to unlock complex scientific data for AI models

Lium, a startup formerly known as Astromind, today announced the launch of an “agentic harness” that helps large language models dig into the most complex and messiest datasets. The launch comes after

agentssiliconangle

Mean Flow Distillation: Robust and Stable Distillation for Flow Matching Models

arXiv:2606.11155v1 Announce Type: new Abstract: Flow Matching models have demonstrated strong performance across a wide range of generative tasks. However, their reliance on ODE-based iterative sampli

safetyarxiv-cs-cv

Mechanistic Analysis of Alignment Algorithms in Language Models

arXiv:2606.09850v1 Announce Type: cross Abstract: Post-training alignment algorithms are predominantly evaluated as black boxes, obscuring how they reshape language models' internal computations. We p

Null-Space Constrained Low-Rank Adaptation for Response-Specified Large Language Model Unlearning

arXiv:2606.10989v1 Announce Type: new Abstract: Large language model unlearning aims to suppress designated undesirable knowledge while preserving benign capabilities. Many unlearning objectives focus

local-aiarxiv-cs-ai

Routing-Aware Expert Calibration for Machine Unlearning in Mixture-of-Experts Language Models

arXiv:2606.10338v1 Announce Type: cross Abstract: Machine unlearning is increasingly important for large language models, yet unlearning in Mixture-of-Experts (MoE) architectures remains underexplored

Scaling Self-Supervised Speech Models Uncovers Deep Linguistic Relationships: Evidence from the Pacific Cluster

arXiv:2603.07238v2 Announce Type: replace Abstract: Similarities between language representations derived from Self-Supervised Speech Models (S3Ms) have been observed to primarily reflect geographic p

researcharxiv-cs-cl

SpeechJBB: Probing Safety Alignment and Comprehension in Large Audio Language Models under Code-Switched Speech

arXiv:2606.06037v2 Announce Type: cross Abstract: Large audio language models (LALMs) are increasingly deployed in real-world applications, yet their safety alignment is still primarily evaluated on m

TacForeSight: Force-Guided Tactile World Model for Contact-Rich Manipulation

arXiv:2606.11184v1 Announce Type: new Abstract: Contact-rich manipulation requires robots to continuously perceive and regulate evolving physical interactions under dynamic contact transitions or comp

local-aiarxiv-cs-ro

Uncovering Vulnerability of Vision-Language-Action Models under Joint-Level Physical Faults

arXiv:2606.10501v1 Announce Type: new Abstract: Deploying Vision-Language-Action (VLA) models in real robotic systems requires robustness not only to semantic and perceptual variations, but also to em

safetyarxiv-cs-ro

Using Probabilistic Programs to Train Inductive Reasoning in Large Language Models

arXiv:2606.09856v1 Announce Type: cross Abstract: Post-training Large Language Models (LLMs) for reasoning typically focuses on deductive tasks such as mathematics and coding where correctness is veri

What Should a Skill Remember? Quality--Cost Trade-offs in Cost-Aware Skill Rewriting for Language Model Agents

arXiv:2606.09421v2 Announce Type: replace Abstract: Large language model agents increasingly rely on skills: reusable procedural documents encoding workflows, tool use, implementation patterns, valida

Whisper-GPT -- Continuous Discrete Hybrid Representation Language Models For Speech And Music

arXiv:2412.11449v2 Announce Type: replace-cross Abstract: We propose WHISPER-GPT: A generative large language model (LLM) for speech and music that allows us to work with continuous audio representati

WorldKernel: A World Model is the Coupling Kernel of Admissible Possible Worlds

arXiv:2606.10934v1 Announce Type: new Abstract: A common assumption holds that enough observational and interventional data, given to a strong enough predictor, suffices. We report a failure mode that

A Theoretical Analysis of Memory and Overfitting Phenomena in Stochastic Interpolation Models

arXiv:2606.08554v1 Announce Type: new Abstract: This paper provides a theoretical account of memorization in stochastic interpolation models. By leveraging closed-form expressions for the optimal velo

researcharxiv-cs-lg

Active Learning with Foundation Model Priors: Efficient Learning under Class Imbalance

arXiv:2606.07630v1 Announce Type: cross Abstract: Real-world datasets across image and text domains are often characterized by skewed class distributions and noisy annotations, which jointly degrade m

applicationsarxiv-cs-ai

AMix-1: A Pathway to Test-Time Scalable Protein Foundation Model

arXiv:2507.08920v4 Announce Type: replace-cross Abstract: We introduce AMix-1, a powerful protein foundation model built on Bayesian Flow Networks and empowered by a systematic training methodology, e

AUCp: Pseudo-AUC for Inference Model Selection with Unlabeled Validation Data in Abnormality Detection

arXiv:2606.08742v1 Announce Type: new Abstract: Abnormality detection is a crucial yet challenging task in medical image analysis. Distinguishing abnormalities from normal data by learning to reconstr

researcharxiv-cs-cv

Beyond Additivity: Causal Discovery in Location-Scale Noise Models with Hidden Variables

arXiv:2606.08196v1 Announce Type: cross Abstract: We study causal discovery from observational data when some variables are hidden and the data-generating process follows a location-scale noise model

Hardware

BREAKING NEWS: Anthropic's latest model will NOT help you if it thinks your ML research/ML engineering is interesting, and/or will secretly …

BREAKING NEWS: Anthropic's latest model will NOT help you if it thinks your ML research/ML engineering is interesting, and/or will secretly degrade its IQ so that the average engineer won't notice. We

hardwareclem-delangue--x

Tutorials

C^3ache: Accelerating World Action Models with Cross Inference Chunk Cache

arXiv:2606.08962v1 Announce Type: cross Abstract: World Action Models (WAMs) generalize better than standard Vision-Language-Action (VLA) policies to novel motions and environments, because a video-mo

tutorialsarxiv-cs-cv