Search: “models”

Pre-Flight: A Benchmark for Evaluating Large Language Models on Aviation Operational Knowledge

arXiv:2607.01829v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed for aviation business operations, from documentation and training generation to customer facing a

3 Jul 2026

Research

CausalMix: Data Mixture as Causal Inference for Language Model Training

DGX agent

arXiv:2607.01104v1 Announce Type: cross Abstract: In Large Language Model (LLM) training, data mixing plays a pivotal role in determining model performance. Recent methods optimize mixture weights via

researcharxiv-cs-ai

2 Jul 2026

CoT-X: An Adaptive Framework for Cross-Model Chain-of-Thought Transfer and Optimization

arXiv:2511.05747v3 Announce Type: replace Abstract: Chain-of-Thought (CoT) reasoning enhances the problem-solving ability of large language models (LLMs) but leads to substantial inference overhead, l

Applications

Dario just declared war on open-source. Anthropic's message is clear: open source could destroy the entire AI business model, and Chinese op…

applicationsclem-delangue--x

Dario just declared war on open-source. Anthropic's message is clear: open source could destroy the entire AI business model, and Chinese open-source models are the cause. I sat down with @jasonlk & @

Seahorse: A Unified Benchmarking Framework for Spatiotemporal Event Modeling

arXiv:2607.01022v1 Announce Type: new Abstract: Spatiotemporal point processes (STPPs) model event data in continuous time and space, with applications in mobility, epidemiology, and public safety. Re

Tutorials

Self-conditioned Flow Map Language Models via Fixed-point Flows

arXiv:2607.00714v1 Announce Type: cross Abstract: Self-conditioning is a core technique that enhances continuous flow-based language models, where the model learns to denoise generated text by conditi

tutorialsarxiv-cs-ai

An Empirical Study of Security Calibration in Large Language Models for Code

arXiv:2606.31159v1 Announce Type: cross Abstract: Large Language Models (LLMs) are rapidly transforming software development, yet their use in security-critical contexts raises a key question: do mode

Calibration, Not Compilation: Detecting and Repairing Misspecified Probabilistic Programs Written by Language Models

arXiv:2606.31630v1 Announce Type: new Abstract: Language models increasingly write probabilistic programs (in NumPyro, Stan, or Pyro), but a program that compiles, runs, and passes every unit test can

Claude Fable 5 is available again in Cursor. It leads all models on CursorBench, but is the most expensive per task.

Claude Fable 5 has been re-enabled as an available model option within Cursor, where it achieves the highest performance scores on CursorBench among all supported models. However, it comes with the hi

model-releasescursor--x

Embodied CAD: Solver-Grounded LLM Agents for Parametric B-Rep Assembly Modeling

arXiv:2606.31252v1 Announce Type: new Abstract: Large language models can write plausible CAD scripts, but reliable industrial CAD modeling requires more than syntactically valid code: every feature,

LLM-as-a-judge validity in physics assessment depends more on the task than the model

arXiv:2603.14732v2 Announce Type: replace-cross Abstract: As large language models (LLMs) are increasingly considered for automated assessment and feedback, understanding when LLM marking is valid is

Physics-Constrained Fine-Tuning of Flow-Matching Models for Generation and Inverse Problems

arXiv:2508.09156v3 Announce Type: replace-cross Abstract: We present a framework for fine-tuning flow-matching generative models to enforce physical constraints and solve inverse problems in scientifi

TotalFM: An Organ-Separated 3D-CT Foundation Model Leveraging Large-Scale Routine Clinical Radiology Data

arXiv:2601.00260v2 Announce Type: replace Abstract: While foundation models in radiology are expected to be applied to various clinical tasks, computational cost constraints remain a major challenge w

researcharxiv-cs-cv

TSHA: A Benchmark for Visual Language Models in Trustworthy Safety Hazard Assessment Scenarios

arXiv:2603.29759v2 Announce Type: replace-cross Abstract: Recent advances in vision-language models (VLMs) have accelerated their application to indoor safety hazards assessment. However, existing ben

A Physics-Grounded Benchmark for Multi-Agent Dynamics in World Models

arXiv:2606.28757v1 Announce Type: new Abstract: Generative world models hold immense promise as scalable simulators for autonomous systems, particularly for synthesizing rare but safety-critical multi

Benchmarking Geospatial Foundation Models for Agriculture Applications

arXiv:2606.29664v1 Announce Type: new Abstract: Geospatial foundation models pretrained on satellite imagery promise broad generalization across remote sensing tasks and regions, but their geographic

Compressed Sensing for Capability Localization in Large Language Models

arXiv:2603.03335v2 Announce Type: replace Abstract: Large language models (LLMs) exhibit a wide range of capabilities, including mathematical reasoning, code generation, and linguistic behaviors. We s

Agents

Evaluating Newtonian Mechanics in Video Generative Models with Real Physical Systems

arXiv:2504.02918v3 Announce Type: replace Abstract: Recent advances in image and video generation raise hopes that these models possess world modeling capabilities-the ability to generate realistic, p

agentsarxiv-cs-cv

Flow Reasoning Models: Scaling Reasoning Through Iterative Self-Refinement

arXiv:2606.29150v1 Announce Type: new Abstract: Discrete flow models have recently shown promising performance on few-step text generation; however, when naively applied to structured reasoning tasks

Kriging and neural network models for pressure losses across perforated plates

arXiv:2606.29628v1 Announce Type: cross Abstract: In this paper, two novel data-driven models based on kriging and neural networks (NN) are proposed to predict pressure losses across perforated plates

Safety

Learning Transferable Dynamics Priors from Action to World Modeling

arXiv:2606.29501v1 Announce Type: new Abstract: We study action-conditioned world modeling as a scalable way to learn transferable dynamics priors for robot learning. By pretraining a model to predict

safetyarxiv-cs-ro

Nonlinear mixture model motivated subspace clustering

arXiv:2606.29261v1 Announce Type: cross Abstract: We derive the linear union-of-subspaces (UoS) model for subspace clustering (SC) from the nonlinear mixture model (NMM) used in blind source separatio

Obliviate: Erasing Concepts from Autoregressive Image Generation Models

arXiv:2606.28643v1 Announce Type: new Abstract: The widespread adoption of generative AI models has intensified concerns about misuse, including the creation of unsafe or disturbing imagery. To mitiga

Applications

Pairwise Comparisons without Stochastic Transitivity: Model, Theory and Applications

arXiv:2501.07437v3 Announce Type: replace-cross Abstract: Most statistical models for pairwise comparisons, including the Bradley-Terry (BT) and Thurstone models and many extensions, make a relatively

applicationsarxiv-cs-lg

Hardware

SSM Meets Video Diffusion Models: Efficient Long-Term Video Generation with Structured State Spaces

arXiv:2403.07711v5 Announce Type: replace-cross Abstract: Given the remarkable achievements in image generation through diffusion models, the research community has shown increasing interest in extend

hardwarearxiv-cs-ai

Structural Certification for Reliable Physical Design with Language Models

arXiv:2606.30107v1 Announce Type: new Abstract: An unreliable language model can be made to produce reliable physical designs if the authority to assert is moved out of the model: the model proposes,

Travel-Oriented Reasoning Large Language Model via Domain-Specific Knowledge Graphs

arXiv:2606.29254v1 Announce Type: new Abstract: Large language models (LLMs) demonstrate broad reasoning abilities but struggle with accuracy and reliability in specialized domains such as travel, whe

We’re shipping two major updates to streamline your creative workflow, allowing you to generate high-speed images with one model and then in…

model-releasesgoogle-ai--x

We’re shipping two major updates to streamline your creative workflow, allowing you to generate high-speed images with one model and then instantly animate them with the other—all at a fraction of the

Diffusion Model Attribution via Spectral Coupling of Denoiser Responses

arXiv:2606.28092v1 Announce Type: new Abstract: Attributing a generated image to its source diffusion model is a fundamental challenge in provenance verification and intellectual property protection.

researcharxiv-cs-cv

From Tokens to States: LLMs as a Special Case of World Models and the Continuous Path Beyond

arXiv:2606.28127v1 Announce Type: cross Abstract: The AI community has framed the relationship between large language models (LLMs) and world models as a dichotomy: LLMs predict tokens; world models s

HybridCodec: Modeling Discrete and Continuous Representations for Efficient Speech Language Models

arXiv:2606.27627v1 Announce Type: cross Abstract: Discrete audio representations have become increasingly popular for building multimodal text-audio systems and integrating audio capabilities into Lar

Towards Benign Memory Forgetting for Selective Multimodal Large Language Model Unlearning

arXiv:2511.20196v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) can inadvertently memorize privacy-sensitive information during training. While existing unlearning methods

Yuvion LLM: An Adversarially-Aware Large Language Model for Content And AI Safety

arXiv:2606.27632v1 Announce Type: new Abstract: As large language models are increasingly deployed in real-world systems, safety failures can still lead to harmful outputs and dangerous misuse. We arg

The take that frontier models aren't ready for use in medicine is dead wrong. I've been using Opus 4.x in my clinical workflow every day for…

model-releasesjeremy-howard--x

The take that frontier models aren't ready for use in medicine is dead wrong. I've been using Opus 4.x in my clinical workflow every day for 6 months. I'm a deep sub-sub-specialist in dermatology - th

27 Jun 2026

Do Image Editing Models Understand Lighting?

arXiv:2606.26738v1 Announce Type: new Abstract: While recent advancements in generative image editing models have achieved stunning visual fidelity, it remains an open question whether these systems p

26 Jun 2026

Unison: Benchmarking Unified Multimodal Models via Synergistic Understanding and Generation

arXiv:2606.26984v1 Announce Type: new Abstract: Unified multimodal models capable of both understanding and generation have achieved remarkable strides. However, despite their unified designs, existin

26 Jun 2026

Surrogate models for Rock-Fluid Interaction: A Grid-Size-Invariant Approach

arXiv:2602.22188v2 Announce Type: replace Abstract: Modelling rock-fluid interaction requires solving a set of partial differential equations (PDEs) to predict the flow behaviour and the reactions of

25 Jun 2026

Uncertainty Quantification for Computer-Use Agents: A Benchmark across Vision-Language Models and GUI Grounding Datasets

arXiv:2606.25760v1 Announce Type: cross Abstract: Computer-use agents turn vision-language model (VLM) predictions into executable GUI clicks, so reliable uncertainty estimates are essential for rejec

25 Jun 2026

BenchX: Benchmarking AI Models for Cancer Detection and Localization with Demographic and Protocol Biases

arXiv:2606.24883v1 Announce Type: new Abstract: Artificial intelligence (AI) has achieved remarkable success in medical imaging, but it is widely recognized that these models often perform inconsisten

Safety

DriveStack-VLA: Render-Teacher Alignment for BEV-Based DeepStack Vision-Language-Action Model

arXiv:2606.24051v1 Announce Type: new Abstract: Vision-Language-Action driving models convert a pretrained Vision-Language Model into a driving policy, allowing them to use world knowledge and follow

safetyarxiv-cs-cv

Local Ai

Federated Survival Analysis in Healthcare: A Multi-Model Evaluation on Cross-Institutional Heterogeneous Breast Cancer Data

arXiv:2606.23871v1 Announce Type: new Abstract: Survival analysis is central to clinical decision-making, yet reliable time-to-event models require large, diverse cohorts that are rarely available at

local-aiarxiv-cs-lg

Lightweight Transformer Models for On-Device Fault Detection: A Benchmark Study on Resource-Constrained Deployment

arXiv:2606.24173v1 Announce Type: cross Abstract: On-device fault detection enables real-time diagnostics without cloud dependency, but deploying machine learning models on resource-constrained hardwa

LoMime: Query-Efficient Membership Inference using Model Extraction in Label-Only Settings

arXiv:2602.18934v2 Announce Type: replace Abstract: Membership inference attacks (MIAs) threaten the privacy of machine learning models by revealing whether a specific data point was used during train

Model selection with proper scoring rules on data sets of time series

arXiv:2606.24715v1 Announce Type: cross Abstract: We consider the problem of model selection between probabilistic models on data sets of time series. Chosen a proper scoring rule, we denote by the te

Assistron: Bayesian Shared Autonomy with Off-the-shelf Vision-Language-Action Models

model-releasesarxiv-cs-ro

arXiv:2606.23147v1 Announce Type: new Abstract: We propose Assistron, a shared autonomy model that leverages Vision-Language-Action (VLA) models to assist the user in daily activities. Our approach is

Bayesian Adaptation Gym: A Benchmark for the Bayesian Low-Rank Adaptation of Multi-Modal Language Models

arXiv:2606.22188v1 Announce Type: new Abstract: Large multi-modal language models are increasingly deployed in high-stakes domains, making well-calibrated uncertainty essential. Traditional Bayesian m

Applications

CAT-Translate: Building Compact Open-Source Models for Japanese-English Translation

arXiv:2606.21413v1 Announce Type: cross Abstract: Nowadays, large multilingual translation models demonstrate impressive translation capabilities in the machine translation benchmarks. This raises a p

applicationsarxiv-cs-lg

Frequency-Domain Neural ODEs for Modeling Non-Linear Dynamical Systems

arXiv:2606.22075v1 Announce Type: new Abstract: Standard continuous-depth models, such as Neural Ordinary Differential Equations (NODEs), offer significant advantages in modeling physical systems by l