model releases

LOGOS: LiDAR-Only Gaussian Elevation Splatting for Unified Tiny Obstacle Segmentation

arXiv:2606.21527v1 Announce Type: cross Abstract: Robust obstacle segmentation is essential for the safety of intelligent robots, where LiDAR-based perception systems play a fundamental role in the ro

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(Look mom - I made it!) Learn more about configuring agent identity and some of the key decisions we made for Claude Tag- https://claude.com…

DGX agent

This post likely discusses configuration options for setting up Claude agent identity and explains the design decisions behind Claude Tag, Anthropic's tool for customizing Claude's behavior and person

model-releasesthariq--x

23 Jun 2026

Low-variance estimators overcome the phase-gradient bottleneck in complex-valued neural quantum states

arXiv:2606.13912v2 Announce Type: replace-cross Abstract: Complex neural quantum states are difficult to optimize when their wavefunction phase carries gauge, chiral, fermionic, or topological structu

LUMINA-26: Low-Light Understanding for Modeling and Interpreting Night-time Actions

arXiv:2606.23118v1 Announce Type: new Abstract: Low-light human action recognition remains a challenging problem due to poor illumination, amplified noise, motion ambiguity, and diverse real-world sce

LUQ: Layerwise Ultra-Low Bit Quantization for Multimodal Large Language Models

arXiv:2509.23729v3 Announce Type: replace Abstract: Large Language Models (LLMs) with multimodal capabilities have revolutionized vision-language tasks, but their deployment often requires huge memory

MammoExpert: Benchmarking Chain-of-Thought Reasoning in Mammography Diagnosis

arXiv:2606.21119v1 Announce Type: new Abstract: Mammography is an essential tool for breast cancer detection, with millions of examinations conducted annually. However, publicly available high-quality

MapReason-OSM: Can Vision-Language Models Make Graph-Verifiable Mobility Decisions from Street Maps ?

arXiv:2606.22597v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly used to read maps for logistics, delivery, and accessible navigation, where the output is an actionable d

Mat-Pref: Verifiable-Reward Training Improves Compositional Reasoning in Inorganic Materials

arXiv:2606.21830v1 Announce Type: new Abstract: Reinforcement learning from verifiable rewards (RLVR) has driven rapid progress in mathematical and code reasoning, but when extended to science, existi

Measuring Intent Comprehension in LLMs

arXiv:2506.16584v3 Announce Type: replace-cross Abstract: People judge interactions with large language models (LLMs) as successful when outputs match what they want, not what they type. Yet LLMs are

MEDLAYXPLAIN: Benchmarking the Expert-Lay Gap in Medical Vision-Language Models

arXiv:2606.21194v1 Announce Type: new Abstract: Medical Vision-Language Models (Med-VLMs) achieve strong expert-level performance, yet their ability to generate patient-accessible descriptions remains

MedTS-TTT: Test-Time Training for Medical Time Series Classification

arXiv:2606.21329v1 Announce Type: new Abstract: Medical time series (MedTS) signals such as electroencephalography (EEG) and electrocardiography (ECG) support many clinical applications. However, subs

Mesh2GS: White-Box 3DGS Construction via Plenoptic Sampling

arXiv:2606.21898v1 Announce Type: cross Abstract: 3D Gaussian Splatting (3DGS) has emerged as a promising method for high-quality, real-time 3D reconstruction. To associate 3DGS with mesh representati

Meta launches cheaper smart glasses without Ray-Ban

model-releasesthe-verge-ai

For the past three years, 'Meta' and 'Ray-Ban' have been synonymous in the smart glasses space. Not anymore. Yesterday, I slipped on several pairs of Meta Glasses - no Ray-Bans - in three different st

Mirage: a Clean-Label Backdoor against LiDAR 3D Object Detection

arXiv:2606.20752v1 Announce Type: new Abstract: Deep neural network-based LiDAR 3D object detection serves as a critical perception component in safety-critical autonomous systems. However, recent stu

Mistral debuts OCR 4, a model featuring structured document extraction with bounding boxes, block classification, and inline confidence scores, in 170 languages (Mistral AI Blog)

Mistral AI Blog: Mistral debuts OCR 4, a model featuring structured document extraction with bounding boxes, block classification, and inline confidence scores, in 170 languages — Today, we're releasi

model-releasestechmeme

Mitigating Measurement-Induced Training Instability in Hybrid Quantum Neural Networks for Protein Classification

arXiv:2606.22551v1 Announce Type: cross Abstract: Hybrid Quantum Neural Network (QNN) classifiers produce logits as expectation values of quantum measurement operators. For standard Pauli measurements

MMGist: A Comprehensive Multimodal Benchmark for 2027

arXiv:2606.22437v1 Announce Type: new Abstract: We conduct a systematic study of 18 widely used vision-language benchmarks and identify three major issues: 1) many items do not rely on visual cues and

MMOU: A Massive Multi-Task Omni Understanding and Reasoning Benchmark for Long and Complex Real-World Videos

arXiv:2603.14145v2 Announce Type: replace-cross Abstract: Multimodal Large Language Models (MLLMs) have shown strong performance in visual and audio understanding when evaluated in isolation. However,

Model Merging in the Essential Subspace

arXiv:2602.20208v2 Announce Type: replace Abstract: Model merging aims to integrate multiple task-specific fine-tuned models derived from a shared pre-trained checkpoint into a single multi-task model

MoECodec: Image Compression for joint human and machine perception via Mixture-of-Experts

arXiv:2606.21033v1 Announce Type: cross Abstract: Image compression for machines calls for a unified codec that serves multiple downstream vision tasks. Existing approaches either adopt task-specific

MOOZY: A Patient-First Foundation Model for Computational Pathology

arXiv:2603.27048v3 Announce Type: replace Abstract: Computational pathology needs whole-slide image (WSI) foundation models that transfer across diverse clinical tasks, yet current approaches remain l

MORL-A2C: Multi-Objective Reinforcement Learning Reranker for Optimizing Healthiness in MOPI-HFRS

arXiv:2606.23603v1 Announce Type: new Abstract: Unhealthy dietary behavior continues to be a persistent public health issue in the United States, exacerbated by recommendation systems that prioritize

Morphology-Aware Multimodal Representation Learning for Insect Phylogenetic Reconstruction

arXiv:2606.22077v1 Announce Type: new Abstract: Morphological traits provide important evidence for phylogenetic reconstruction and evolutionary relationship analysis. Recent image-based approaches ha

MotionHalluc: Diagnosing Kinematic Hallucinations in Fine-Grained Motion Reasoning

arXiv:2606.23061v1 Announce Type: new Abstract: Motion instruction generation in cross-video comparison aims to produce corrective feedback that describes the differences between a query and a referen

Multigrid Training for Molecular Generation using Graph Neural Networks

arXiv:2606.22377v1 Announce Type: new Abstract: Deep learning has demonstrated significant success for modeling biochemical molecular systems, where inputs are commonly represented as graphs or 3D gri

Muown Implicitly Performs Angular Step-size Decay

arXiv:2606.23637v1 Announce Type: new Abstract: Matrix-aware optimizers such as Muon and Muown have recently shown strong empirical performance for pre-training Transformers. In particular, Muown sepa

Neural Parameter Calibration for Finite-State Mean Field Games

arXiv:2606.23155v1 Announce Type: cross Abstract: Mean field games efficiently approximate a very large population of strategic agents. While these games can aid the understanding of complex systems,

Next-Gen CAPTCHAs: Leveraging the Cognitive Gap for Scalable and Diverse GUI-Agent Defense

arXiv:2602.09012v2 Announce Type: replace Abstract: The rapid evolution of GUI-enabled agents has rendered traditional CAPTCHAs obsolete. While previous benchmarks like OpenCaptchaWorld established a

NNiT: Width-Agnostic Neural Network Generation with Structurally Aligned Weight Spaces

arXiv:2603.00180v2 Announce Type: replace Abstract: Generative modeling of neural network parameters is often tied to architectures because standard parameter representations rely on known weight-matr

Non-asymptotic estimates of the minimal risk in statistical learning

arXiv:2606.23295v1 Announce Type: new Abstract: In this paper we prove some concentration inequalities for two types of error probabilities in the Empirical Risk Principle (ERP) in statistical learnin

Nous: A Predictive World Model for Long-Term Agent Memory

arXiv:2606.22030v1 Announce Type: cross Abstract: We present Nous, a novel agent memory architecture grounded in the principle that knowledge is prediction, not storage. Rather than persisting facts a

OGD4All: A Framework for Accessible Interaction with Geospatial Open Government Data Based on Large Language Models

arXiv:2602.00012v3 Announce Type: replace Abstract: We present OGD4All, a transparent, auditable, and reproducible framework based on Large Language Models (LLMs) to enhance citizens' interaction with

Open Annotations and Synthetic Data for Field Localisation in Indian Bank Cheques

arXiv:2606.20682v1 Announce Type: new Abstract: Automated cheque processing requires localising key fields (date, legal amount, IFSC code, account number, signature, and payee name) before any recogni

Open models, global networks: How AT&T and GSMA are accelerating telecom innovation with Gemma

model-releasesgoogle-cloud-ai

Telecommunications is an incredibly complex, highly specialized domain. Modern mobile networks are inherently multi-vendor, featuring diverse and often proprietary data structures. While AI has made m

Open Problem: Is AdamW Effective Under Heavy-Tailed Noise?

arXiv:2606.23676v1 Announce Type: new Abstract: AdamW is the de facto optimizer for training large language models (LLMs), yet the theory behind it still lives mostly in finite-variance regimes. This

OpenAI DevDay 2026 applications are now open! Our biggest developer event gets even bigger. 📍 San Francisco 📅 September 29 Apply by July 1…

OpenAI DevDay 2026, the company's major developer conference, will take place in San Francisco on September 29, 2026, with applications opening for attendees. The application deadline is July 1, 2026.

model-releasesopenai--x

OPFS + Pyodide test harness

model-releasessimon-willison

Tool: OPFS + Pyodide test harness I've been pondering if Datasette Lite - the Python Datasette application run entirely in the browser using Pyodide and WebAssembly - might be able to edit persistent

Oracle-RLAIF: An Improved Fine-Tuning Framework for Multi-modal Video Models using Reinforcement Learning from Ranking Feedback

arXiv:2510.02561v2 Announce Type: replace Abstract: Recent advances in large video-language models (VLMs) rely on extensive fine-tuning techniques that strengthen alignment between textual and visual

ORBIT: Training-Free Multi-Attribute Behavioral Steering via Orthogonal Subspace Rotation

arXiv:2606.22357v1 Announce Type: cross Abstract: Language models are widely used in assistant settings, where controlling behavioral attributes is often essential. Activation steering modifies hidden

Orthogonal Discrepancy Kernels for Learning with Partial Physics

arXiv:2606.21199v1 Announce Type: cross Abstract: We introduce a semi-parametric framework for nonlinear system identification, which decouples discrepancy functions from physics-based components. Ort

OVIG: Optimistic Verification of AI Training Integrity via Gradient Signals

arXiv:2606.21045v1 Announce Type: cross Abstract: The rapid growth of AI has increased the demand for domain-specific post-training, while the cost and specialization of accelerator infrastructure pus

Parameterized Representations via Implicit Stochastic Modulation for High-Dimensional and High-Order Neural PDE Solvers

arXiv:2606.22150v1 Announce Type: new Abstract: Solving high-dimensional and high-order PDEs is challenged by the coupled growth of spatial dimensionality and derivative order. Recent stochastic deriv

PHOEBI: An Open-World Benchmark for Bacterial Identification in Phase-Contrast Microscopy

arXiv:2606.22890v1 Announce Type: new Abstract: Optical microscopy enables rapid, label-free imaging of live bacteria and is the standard instrument for species identification across clinical, environ

PhysFlow: Frequency Decoupled with Dual-Field Rectified Flow for Remote Photoplethysmography

arXiv:2606.23226v1 Announce Type: new Abstract: Remote Photoplethysmography (rPPG) enables contactless pulse estimation from facial videos, serving as a vital tool for health monitoring. However, curr

Physics-Guided Dual-Stream Heterogeneous Graph Neural Network for Predicting Full-Field Structural Response of Stiffened Panels

arXiv:2606.20916v1 Announce Type: new Abstract: Iterative design and optimization of large, complex structures require fast and accurate prediction of stress, displacement, and other fields. Finite el

Physics-Informed Neural Networks for Computing the Morse Index of the Critical Catenoid

arXiv:2606.21725v1 Announce Type: cross Abstract: The Morse index of a free boundary minimal surface is encoded in its Jacobi-Steklov spectrum, and we test how faithfully a physics-informed neural net

Physiology-Aware CNN and Zero-Shot Multimodal LLMs for ECG Image Classification: A Comparative Study

arXiv:2606.22889v1 Announce Type: new Abstract: Multimodal large language models (LLMs) are increasingly adopted to interpret 12-lead ECG images, though the interpretations often lack validation. Howe

Policy4OOD: A Knowledge-Guided World Model for Policy Intervention Simulation against the Opioid Overdose Crisis

arXiv:2602.12373v2 Announce Type: replace Abstract: The opioid epidemic remains one of the most severe public health crises in the United States, yet evaluating policy interventions before implementat