Search: “models”

arXiv:2606.25368v1 Announce Type: new Abstract: Visual anomaly detection is often deployed with only normal training images. Most one-class detectors map test patches or features to a normal reference

local-aiarxiv-cs-cv

25 Jun 2026

Human

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Model Releases

AI-PAVE-Br: Leveraging Large Language Models for Enhanced Product Attribute Value Extraction through a Golden Set Approach

DGX agent

arXiv:2606.24655v1 Announce Type: cross Abstract: The explosive growth and complexity of product data within the dynamic Brazilian e-commerce landscape demand robust and specialized methods for struct

model-releasesarxiv-cs-ai

24 Jun 2026

EERLoss: A Novel Loss Function for Training Deep Biometric Models. A Case Study in Keystroke Dynamics

model-releasesarxiv-cs-cv

arXiv:2606.24586v1 Announce Type: new Abstract: Deep learning approaches to biometric verification are commonly trained by optimizing indirect objectives, creating a misalignment between the optimizat

Measuring User's Mental Models of Speech Translation in Human-AI Collaboration

arXiv:2606.24644v1 Announce Type: new Abstract: Millions of people use machine translation (MT) tools daily, yet little is known about their perception of what systems can and cannot do. This paper st

researcharxiv-cs-cl

Applications

Natural Identifiers for Privacy and Data Audits in Large Language Models

arXiv:2606.24408v1 Announce Type: new Abstract: Assessing the privacy of large language models (LLMs) presents significant challenges. In particular, most existing methods for auditing differential pr

applicationsarxiv-cs-lg

PHANTOM: A Large-Scale Dataset of Multimodal Adversarial Attacks for Vision-Language Models

arXiv:2606.24388v1 Announce Type: new Abstract: We introduce a large-scale, open-source dataset of pre-generated adversarial attacks for vision-language models (VLMs). The dataset is designed to be di

Probing the Misaligned Thinking Process of Language Models

arXiv:2606.24251v1 Announce Type: new Abstract: Large language models exhibit a growing range of misaligned behaviors such as strategic deception, sandbagging, and self-preservation. As they are incre

researcharxiv-cs-ai

Same Lesson, Different Story: Cross-Lingual Reconstruction of Cultural Narratives in Large Language Models

arXiv:2606.24610v1 Announce Type: new Abstract: The evaluation of cultural grounding context becomes complex when multiple cultures convey the same moral lesson. This challenge is particularly relevan

researcharxiv-cs-cl

Local Ai

World Models in Pieces: Structural Certification for General Agents

arXiv:2606.24842v1 Announce Type: new Abstract: In the big-world regime, agents cannot be universally capable and their ability is inevitably specialized across a world model in pieces. Consequently,

local-aiarxiv-cs-ai

HyperQuant: A Rate-Distortion-Optimal Quantization Pipeline for Large Language and Diffusion Models

model-releasesarxiv-cs-lg

arXiv:2606.23406v1 Announce Type: new Abstract: We present HyperQuant (Hadamard, optimallY Packing, Entropy Rice-coding), a unified post-training quantization pipeline for the weights and the KV cache

Learning Expressive Random Feature Models via Parametrized Activations

arXiv:2411.19468v4 Announce Type: replace Abstract: The random feature (RF) method is a powerful kernel approximation technique, but it typically uses fixed activation functions, limiting its adaptabi

Lightweight 3D Feature Pretraining by Bayesian Inversion of 2D Foundation Models

arXiv:2606.21292v1 Announce Type: new Abstract: We present Casper3D, a lightweight probabilistic framework for converting noisy multi-view 2D foundation-model embeddings into a latent 3D semantic repr

Mitigating Cross-Image Information Leakage in Multi-Image Understanding with Large Vision-Language Models

arXiv:2508.13744v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) exhibit strong performance on single-image tasks. However, their performance degrades significantly when handli

On the Limits of Prompt-Conditioned Language Models as General-Purpose Learners

arXiv:2606.23668v1 Announce Type: new Abstract: Large Language Models (LLMs) are frequently portrayed as general-purpose solvers capable of solving arbitrary tasks. We argue that this view overlooks a

safetyarxiv-cs-lg

One Image is All You Need: Agentic One-Shot Image Generation via Text-Based World Models for Long-Tail Spatial Perception

arXiv:2606.20764v1 Announce Type: new Abstract: Reliable spatial decision automation, such as autonomous driving and maritime surveillance, critically depends on robust visual perception. However, rea

PolicyTrim: Boosting Intrinsic Policy Efficiency of Vision-Language-Action Models

arXiv:2606.22540v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models provide a unified paradigm for robotic manipulation, yet their real-world deployment is often bottlenecked by execut

Scaling State-Space Models from Lines to Paragraphs: An Ablation of Mamba-based OCR

arXiv:2606.23524v1 Announce Type: new Abstract: End-to-end OCR increasingly relies on autoregressive sequence models, where the quadratic cost of Transformer attention limits efficient transcription o

Scheduling Thoughts: Learning the Order of Thought in Diffusion Language Models

arXiv:2606.23567v1 Announce Type: new Abstract: Masked diffusion language models decode by iteratively unmasking tokens, where the unmasking order defines an 'order of thought' that strongly influence

safetyarxiv-cs-lg

SPAR: Semantic-Pixel Self-Alignment and Adaptive Routing for Unified Multimodal Models

arXiv:2606.23041v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable success in visual understanding but remain constrained in visual generation due to the

Substitution-Based Analysis of Structural Novelty for Generative Models of Materials

arXiv:2606.23166v1 Announce Type: new Abstract: There has been rapid progress in generative artificial intelligence (AI) models for inorganic crystal design, which can efficiently generate large numbe

safetyarxiv-cs-lg

Towards CSI-Native Foundation Models: A Channel-Adaptive Roadmap for 6G

arXiv:2606.20670v1 Announce Type: new Abstract: Wireless foundation models offer a path toward reusable channel state information (CSI) intelligence for sixth-generation (6G) systems. However, existin

Wh0: Generative World Models as Scalable Sources of Egocentric Human Hand Manipulation Data

arXiv:2606.22136v1 Announce Type: new Abstract: Scaling dexterous manipulation requires generalization across objects, scenes, and tasks, yet existing data sources face a trade-off between scale and s

safetyarxiv-cs-ro

Agents

Guess which is Fugu Ultra? This is how recent models compare when generating endless procedural terrain (using Three.js). All of these are o…

Guess which is Fugu Ultra? This is how recent models compare when generating endless procedural terrain (using Three.js). All of these are one-shotted! Just wild! Trying a few more examples. Will shar

agentsdair-ai--x

22 Jun 2026

Tools

We got local models to triage the OpenClaw repo for FREE!*

This article discusses using local language models to automatically triage pull requests in the OpenClaw repository at no cost, eliminating the need for expensive API-based solutions. The post likely

toolshugging-face

22 Jun 2026

Augmenting Molecular Language Models with Local n-gram Memory

arXiv:2606.12113v1 Announce Type: cross Abstract: Transformer-based language models for SMILES strings suffer from a locality gap: standard character-level tokenization fragments chemically meaningful

Beyond representational alignment with brain-guided language models for robust reasoning

arXiv:2606.11893v1 Announce Type: cross Abstract: The correspondence between large language models (LLMs) and the neural mechanisms underlying human higher-order cognition remains insufficiently chara

Compatibility-Aware Dynamic Fine-Tuning for Large Language Models

arXiv:2606.11206v1 Announce Type: new Abstract: Supervised Fine-Tuning (SFT) is the predominant paradigm for aligning large language models (LLMs), yet it suffers from optimization instability and lim

safetyarxiv-cs-cl

From Correspondence to Actions: Human-Like Multi-Image Spatial Reasoning in Multi-modal Large Language Models

arXiv:2602.08735v3 Announce Type: replace Abstract: While multimodal large language models (MLLMs) have made substantial progress in single-image spatial reasoning, multi-image spatial reasoning, whic

InternVideo3: Agentify Foundation Models with Multimodal Contextual Reasoning

arXiv:2606.12195v1 Announce Type: new Abstract: Recent progress in foundation models has shifted toward agentic behavior involving multi-step reasoning and tool use. However, open-source efforts large

Hardware

Litespark Inference For CPUs: Ultra-Fast SIMD Framework for Ternary (1.58-bit) Language Models

arXiv:2605.06485v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have transformed artificial intelligence, but their computational requirements remain prohibitive for most users.

hardwarearxiv-cs-ai

Local Ai

MultiToP: Learning to Patch Visual Tokens to Mitigate Hallucinations in Video Large Multimodal Models

arXiv:2606.11792v1 Announce Type: cross Abstract: Video Large Multimodal Models have achieved remarkable progress in video understanding, yet they remain prone to hallucinations, where generated respo

local-aiarxiv-cs-ai

Neuron-based Personality Trait Induction in Large Language Models

arXiv:2410.12327v2 Announce Type: replace Abstract: Large language models (LLMs) have become increasingly proficient at simulating various personality traits, an important capability for supporting re

researcharxiv-cs-cl

Scenario-based Probing and Steering Cultural Values in Large Language Models--Extended Version

arXiv:2606.11399v1 Announce Type: new Abstract: Large Language Models (LLMs) are deployed across cultural contexts but often reflect homogenized values inherited from training data. Evaluations of cul

safetyarxiv-cs-cl

Slots, Transitions, Loops: Learning Composable World Models for ARC

arXiv:2606.12316v1 Announce Type: new Abstract: ARC tests in-context rule induction: given a few input-output demonstrations, a model must infer the hidden rule and apply it to a new query. While many

Tabular Foundation Models for Clinical Survival Analysis via Survival-Aware Adaptation

arXiv:2606.12006v1 Announce Type: cross Abstract: Predicting time-to-event outcomes such as mortality is a fundamental task in clinical decision-making, commonly addressed through survival analysis. W

researcharxiv-cs-ai

VLGA: Vision-Language-Geometry-Action Models for Autonomous Driving

arXiv:2606.12396v1 Announce Type: new Abstract: Vision-language-action (VLA) models can describe scenes and reason about them in language, yet still struggle to ground their actions in the dense 3D wo

VOID: Defeating Unauthorized Mimicry in Latent Diffusion Models

arXiv:2606.12263v1 Announce Type: new Abstract: While Latent Diffusion Models (LDMs) have revolutionized visual synthesis, they are increasingly exploited for unauthorized mimicry of individuals. Exis

Can we trust our models? Epistemic calibration in second-order classification

arXiv:2606.10777v1 Announce Type: new Abstract: Uncertainty estimation is critical for deploying machine learning models in high-stakes settings. However, classical calibration only assesses the relia

Industry

Dario Amodei says frontier models should face mandatory third-party testing for cyber, bio, and autonomy risks, in addition to overall transparency requirements (Dario Amodei/@darioamodei)

Dario Amodei / @darioamodei: Dario Amodei says frontier models should face mandatory third-party testing for cyber, bio, and autonomy risks, in addition to overall transparency requirements — In addit

industrytechmeme

GaussTrace: Provenance Analysis of 3D Gaussian Splatting Models with Evidence-based LLM Reasoning

arXiv:2606.10612v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) is a powerful technique for creating high-fidelity 3D assets. However, the widespread sharing and iterative modification of

Tutorials

In Defense of Information Leakage in Concept-based Models

arXiv:2606.10669v1 Announce Type: cross Abstract: Concept-based models (CMs), deep neural networks that ground their predictions on representations aligned with human-understandable concepts (e.g., 'r

tutorialsarxiv-cs-ai

PhysMetrics.Weather: An Evaluation Framework for Physical Consistency in ML Weather Models

arXiv:2606.10642v1 Announce Type: new Abstract: Machine learning weather prediction (MLWP) models have achieved impressive forecasting performance at a small fraction of the computational costs requir

Tutorials

QDepth-VLA: Quantized Depth Prediction as Auxiliary Supervision for Vision-Language-Action Models

arXiv:2510.14836v3 Announce Type: replace Abstract: Spatial perception and reasoning are crucial for Vision-Language-Action (VLA) models to accomplish fine-grained manipulation tasks. However, existin

tutorialsarxiv-cs-cv

Beyond Accuracy: Interpreting Topic Representation in Suicide Ideation Detection Models

arXiv:2606.07714v1 Announce Type: cross Abstract: Suicide ideation detection models are typically evaluated using aggregate performance metrics, yet little is known about how they internally represent

Beyond Spherical Harmonics: Rethinking Appearance Models for Radiance Reconstruction

arXiv:2606.09794v1 Announce Type: new Abstract: View-dependent appearance modeling remains a challenging problem in novel-view synthesis and reconstruction. Accurately representing complex angular eff

Community-Specific Slang and Entity Detection via Semantic Shift in Fine-Tuned Language Models

arXiv:2606.07522v1 Announce Type: cross Abstract: We propose an unsupervised method of resolving slang, unique entities, and folklore from online communities by isolating words in the lexicon that hav

Conan-embedding-v3: Fusing Modality-Specific Models for Omni-Modal Embedding

model-releasesarxiv-cs-ai

arXiv:2606.09331v1 Announce Type: cross Abstract: Omni-modal retrieval promises a single embedding space for text, image, video, document, and audio inputs, but building such a unified retriever is di

Discovering heuristics in a complex SAT solver with large language models

model-releasesarxiv-cs-ai

arXiv:2507.22876v2 Announce Type: replace Abstract: The Satisfiability problem (SAT) is fundamental in computational complexity theory and has a wide range of industrial applications. Optimizing moder