Search: “models”

Edge AI Deployment Beyond Models: A BSP-Aware Systems Framework for Industrial Embedded Platforms

arXiv:2605.26119v1 Announce Type: cross Abstract: Industrial Edge AI programs often begin with the model and only later confront the platform. That sequencing is attractive because it allows early dem

local-aiarxiv-cs-ai

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Research

Emergent Causal-Geometric Dynamics Across Depth in Large Language Models

DGX agent

arXiv:2602.04931v2 Announce Type: replace-cross Abstract: Geometric analyses of large language model (LLM) representations reveal structured variation across depth but remain fundamentally correlation

researcharxiv-cs-ai

27 May 2026

Great to see @poolsideai (US lab) committing to open sourcing their foundation models going forward Laguna is an interesting release, check …

Great to see @poolsideai (US lab) committing to open sourcing their foundation models going forward Laguna is an interesting release, check it out @Shaughnessy119 https://poolside.ai/blog/introducing-

industryemad-mostaque--x

If the Founder of Hugging Face asks, you gotta do it. Models and dataset now live: https://huggingface.co/papers/2605.22391 Also built an ex…

If the Founder of Hugging Face asks, you gotta do it. Models and dataset now live: https://huggingface.co/papers/2605.22391 Also built an explorer: https://huggingface.co/spaces/Kaikaku/epicure-explor

industryclem-delangue--x

Learning Energy-Based Models from Stochastic Interpolants using Spatiotemporal Differences

arXiv:2605.26850v1 Announce Type: new Abstract: Learning an energy-based model from data samples is a central problem in machine learning. Many recent and popular methods, such as denoising score matc

tutorialsarxiv-cs-lg

Learning to Diagnose and Correct Errors: Towards Moral Sensitivity Acquisition in Large Language Models

arXiv:2601.03079v4 Announce Type: replace Abstract: Moral sensitivity is the most fundamental capability underlying human moral competence. Although many approaches aim to align large language models

tutorialsarxiv-cs-cl

Left-Right Symmetry Breaking in CLIP-style Vision-Language Models Trained on Synthetic Spatial-Relation Data

arXiv:2601.12809v2 Announce Type: replace-cross Abstract: Spatial understanding remains a key challenge in vision-language models. Yet it is still unclear whether such understanding is truly acquired,

LUCoS: Latent Unsupervised Context Selection for Tabular Foundation Models

arXiv:2605.27254v1 Announce Type: cross Abstract: Selecting which instances to label is a key challenge in low-label tabular learning. For recent Tabular Foundation Models such as TabPFN, context sele

Respecting Modality Gap in Post-hoc Out-of-distribution Detection with Pre-trained Vision-Language Models

arXiv:2605.26661v1 Announce Type: cross Abstract: Out-of-distribution (OOD) detection has emerged as a popular technique to enhance the reliability of machine learning models by identifying unexpected

The Constraint Tax: Measuring Validity-Correctness Tradeoffs in Structured Outputs for Small Language Models

arXiv:2605.26128v1 Announce Type: new Abstract: Production LLM systems increasingly require machine-readable outputs: JSON objects, typed traces, regex-constrained fields, and tool-call schemas. This

local-aiarxiv-cs-lg

Capability and Robustness Cannot Both Be Free: An Information-Theoretic Bound for Vision-Language-Action Models

arXiv:2605.25889v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models are increasingly deployed on real robots, where each predicted action is executed and each failure carries a safet

safetyarxiv-cs-lg

Comfy will be at @aionthelot Our CEO @yoland_yan is joining a panel of AI video leaders for a progress report on the state of video models -…

Comfy will be at @aionthelot Our CEO @yoland_yan is joining a panel of AI video leaders for a progress report on the state of video models - where they excel, where they fall short, and what's coming

local-aicomfyui--x

Confidence Calibration in Large Language Models

arXiv:2605.23909v1 Announce Type: new Abstract: We investigate the calibration of large language models' (LLMs') confidence across diverse tasks. The results of our preregistered study show that the c

Dynamic Optimization and Safety Indicator Injection for Jailbreaking Text-to-Image Models with Multimodal Safety Filters

arXiv:2505.18979v2 Announce Type: replace Abstract: Text-to-image (T2I) models can generate not-safe-for-work (NSFW) content, motivating multi-stage safety pipelines with both text and image filters.

safetyarxiv-cs-lg

EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models

arXiv:2605.25477v1 Announce Type: cross Abstract: The ability to efficiently and reliably learn new tasks has been a foundational challenge in robotics. Vision-Language-Action (VLA) models have demons

tutorialsarxiv-cs-ai

Applications

Hypothesis Generation and Inductive Inference in Children and Language Models

arXiv:2605.24528v1 Announce Type: new Abstract: Real world decision-making requires constructing mental models under uncertainty over evidence, over the underlying causal rules, and over the state of

applicationsarxiv-cs-ai

Jailbreak to Protect: Buffering and Reinforcing via Temporary Jailbreaking for Safe Fine-Tuning in Large Language Models

arXiv:2605.24550v1 Announce Type: new Abstract: Fine-tuning-as-a-Service (FaaS) enables personalization of large language models (LLMs), but it can weaken safety-alignment under harmful fine-tuning at

safetyarxiv-cs-ai

// Language Models Need Sleep // Let your agents 'sleep', folks. On a serious note, this is a fascinating paper on getting the most from lon…

// Language Models Need Sleep // Let your agents 'sleep', folks. On a serious note, this is a fascinating paper on getting the most from long-horizon agents. Here is the problem with agents today: Att

tutorialsdair-ai--x

MAGIC: Multimodal Alignment & Grounding-aware Instruction Coreset for Vision-Language Models

arXiv:2605.26004v1 Announce Type: cross Abstract: Instruction tuning of large vision-language models (LVLMs) increasingly depends on massive multimodal corpora, yet these datasets contain samples with

safetyarxiv-cs-cl

Mitigating Object Hallucinations in Vision-Language Models through Region-Aware Attention Recalibration

arXiv:2605.24957v1 Announce Type: new Abstract: The generation of factually incorrect objects, commonly known as object hallucination, remains a persistent challenge in Large Vision-Language Models (L

OpenRouter raised 113M led by CapitalG, a source says at a 1.3B valuation, and now processes 25T tokens across 400+ models weekly, up from 5T six months ago (Michael J. de la Merced/New York Times)

Michael J. de la Merced / New York Times: OpenRouter raised 113M led by CapitalG, a source says at a 1.3B valuation, and now processes 25T tokens across 400+ models weekly, up from 5T six months ago —

industrytechmeme

Side-by-side Comparison Amplifies Dialect Bias in Language Models

arXiv:2605.24384v1 Announce Type: cross Abstract: Language models (LMs) can exhibit systematic biases against speakers based on variations in their dialects, even in the absence of a dialect label, a

safetyarxiv-cs-ai

Sources: Fireworks AI, which helps companies run AI models, is in talks to raise funding at a 15B valuation after being valued at 4B in October 2025 (Rebecca Torrence/Bloomberg)

Rebecca Torrence / Bloomberg: Sources: Fireworks AI, which helps companies run AI models, is in talks to raise funding at a 15B valuation after being valued at 4B in October 2025 — Fireworks AI, a sta

industrytechmeme

Squeezing Capacity from Multimodal Large Language Models for Subject-driven Generation

arXiv:2605.26111v1 Announce Type: cross Abstract: Subject-driven image generation aims to synthesize new images that preserve the identity of the given subject while following textual instructions. Ex

The Impact of Large Language Models on Open-source Innovation: Evidence from GitHub Copilot

arXiv:2409.08379v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are reshaping knowledge work, yet their impact on voluntary, self-guided open innovation forums (contributors cho

When In-Distribution Gains Fail: Evaluating Weak-to-Strong Reward Models under Preference Shift

arXiv:2605.25629v1 Announce Type: new Abstract: Weak-to-strong (W2S) generalization is a promising framework for scalable oversight, yet existing evaluations often test students under matched train--t

researcharxiv-cs-cl

Agents

Why Agentic Theorem Prover Works: A Statistical Provability Theory of Mathematical Reasoning Models

arXiv:2602.10538v3 Announce Type: replace-cross Abstract: Agentic theorem provers combine a reasoning model, retrieval, search, and a proof assistant verifier, yet it remains unclear which components

agentsarxiv-cs-lg

Zero-Shot Parkinson's Disease Detection from Speech: Comparing Large Audio and Language Models

arXiv:2605.24806v1 Announce Type: cross Abstract: Large audio and language models have recently demonstrated zero-shot reasoning capabilities across various domains. However, it remains unclear how th

A look at the UK's AI Safety Institute, whose researchers probe AI models for safety gaps, as its work becomes a blueprint for other governments' AI policies (New York Times)

New York Times: A look at the UK's AI Safety Institute, whose researchers probe AI models for safety gaps, as its work becomes a blueprint for other governments' AI policies — The government's A.I. Se

safetytechmeme

ChainFlow-VLA: Causal Flow Planning with Vision-Language Models

arXiv:2605.23270v1 Announce Type: cross Abstract: Current end-to-end autonomous driving systems are fundamentally limited by a mismatch between temporal causal reasoning and global trajectory consiste

safetyarxiv-cs-ai

Convex Compositional Reasoning Models

arXiv:2605.23395v1 Announce Type: new Abstract: Compositional energy-based models can generalize to larger combinatorial reasoning problems by reusing a learned factor energy across many local constra

Model Releases

Hierarchical Concept Geometry in Language Models Emerges from Word Co-occurrence

model-releasesarxiv-cs-cl

arXiv:2605.23821v1 Announce Type: new Abstract: We propose a distributional theory of how hypernymy -- the ``is-a'' relation between general and specific concepts -- is encoded geometrically in langua

Is Dimensionality a Barrier for Retrieval Models?

arXiv:2605.23556v1 Announce Type: new Abstract: Why does the low dimensionality of representations, typically dapprox 1000, not prevent modern embedding-based retrieval models from scaling to billions

Model Releases

MadEvolve: Evolutionary Optimization of Trading Systems with Large Language Models

model-releasesarxiv-cs-ai

arXiv:2605.23007v1 Announce Type: cross Abstract: We explore the application of LLM-driven algorithm optimization to several common tasks in quantitative finance. MadEvolve, a general-purpose algorith

Next-Latent Prediction Transformers Learn Compact World Models

arXiv:2511.05963v2 Announce Type: replace Abstract: Transformers replace recurrence with a memory that grows with sequence length and self-attention that enables ad-hoc lookups over past tokens. Conse

safetyarxiv-cs-lg

A 6-person team is building task-specific AI models that are 4-8x faster than anything from OpenAI or Anthropic. 500K downloads on HuggingFa…

A 6-person team is building task-specific AI models that are 4-8x faster than anything from OpenAI or Anthropic. 500K downloads on HuggingFace. No hype. Just better engineering winning on the merits.

industryclem-delangue--x

Disentanglement Beyond Generative Models with Riemannian ICA

arXiv:2605.22531v1 Announce Type: new Abstract: There is a gap between the theoretical foundations of disentanglement and the practice of modern representation learning. Existing theoretical framework

local-aiarxiv-cs-lg

Finite-Particle Convergence Rates for Conservative and Non-Conservative Drifting Models

arXiv:2605.22795v1 Announce Type: cross Abstract: We propose and analyze a conservative drifting method for one-step generative modeling. The method replaces the original displacement-based drifting v

SepsisAI Orchestrator: A Containerized and Scalable Platform for Deploying AI Models and Real-Time Monitoring in Early Sepsis Detection

arXiv:2605.22331v1 Announce Type: new Abstract: Despite strong predictive results in the clinical machine learning literature, the translation of these models into bedside use remains limited by syste

A Tutorial on Diffusion Theory: From Differential Equations to Diffusion Models

arXiv:2605.22586v1 Announce Type: cross Abstract: This tutorial develops diffusion models from the viewpoint of differential equations. We begin with the conditional Gaussian forward process and show

tutorialsarxiv-cs-cl

Conceptualizing Embeddings: Sparse Disentanglement for Vision-Language Models

arXiv:2605.22679v1 Announce Type: new Abstract: Vision-language models learn powerful multimodal embeddings, yet their internal semantics remain opaque. While sparse autoencoders (SAEs) can extract in

tutorialsarxiv-cs-cv

From Correlation to Cause: A Five-Stage Methodology for Feature Analysis in Transformer Language Models

arXiv:2605.22462v1 Announce Type: new Abstract: We propose a five-stage methodology for causal feature analysis in transformer language models (probe design, feature extraction, causal validation, rob

researcharxiv-cs-cl

i need someone at @OpenAI and @AnthropicAI to teach the models that while prototyping, backwards compatibility is just a bad idea

tutorialsjeremy-howard--x

Jeremy Howard argues that AI model developers at OpenAI and Anthropic should prioritize breaking backwards compatibility during the prototyping phase rather than maintaining it, suggesting that backwa

3D Reconstruction and Knowledge Distillation to Improve Multi-View Image Models to Explore Spike Volume Estimation in Wheat

arXiv:2605.20940v1 Announce Type: new Abstract: Accurate estimation of wheat spike volume is important for yield component analysis and stress resilience assessment, yet field-based measurement remain

safetyarxiv-cs-cv

Hardware

Accelerating Video Inverse Problem Solvers with Autoregressive Diffusion Models

arXiv:2605.20624v1 Announce Type: new Abstract: Diffusion models provide powerful priors for zero-shot video inverse problems, but their real-time deployment is hindered by two inefficiencies: high in

hardwarearxiv-cs-cv

Efficient Learning of Deep State Space Models via Importance Smoothing

arXiv:2605.21108v1 Announce Type: new Abstract: Latent state space systems are ubiquitous in statistical modelling, arising naturally when a time series is observed through a noisy measurement functio

Focus-then-Context: Subject-Centric Progressive Visual Token Reduction for Vision-Language Models

arXiv:2605.20950v1 Announce Type: new Abstract: Vision-Language Models (VLMs) face a bottleneck of prohibitive computational costs arising from massive visual token sequences during inference. Existin

researcharxiv-cs-cv

Agents

How Well Do Vision-Language Models Understand Sequential Driving Scenes? A Sensitivity Study

arXiv:2604.06750v2 Announce Type: replace Abstract: Vision-Language Models (VLMs) are increasingly proposed for autonomous driving tasks, yet their performance on sequential driving scenes remains poo

agentsarxiv-cs-cv