Search: “models”

Generative Modeling via Kernelized Stochastic Interpolants

arXiv:2602.20070v3 Announce Type: replace Abstract: We develop a kernel method for generative modeling within the stochastic interpolant framework, replacing neural network training with linear system

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

DGX agent

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

model-releasesarxiv-cs-lg

23 Jun 2026

Local Ai

Latent Goal Prediction from Language for Model-Based Planning

arXiv:2606.20627v1 Announce Type: cross Abstract: Planning with world models is bottlenecked by compounding prediction errors and the difficulty of defining optimizable goals. Visual targets provide p

local-aiarxiv-cs-lg

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

Model Releases

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

model-releasesarxiv-cs-lg

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

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

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

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

Stable Transformer-Actor-Critic Model Predictive Control: A Contraction Analysis Approach

arXiv:2606.20197v2 Announce Type: replace Abstract: Actor-Critic Model Predictive Control (MPC) effectively addresses complex, non-convex control problems, but guaranteeing the closed-loop stability o

safetyarxiv-cs-ro

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

The Unseen Hand: Manipulating Model Fairness and SHAP with Targeted Identity Re-Association Attacks

arXiv:2606.22858v1 Announce Type: new Abstract: As machine learning models grow more influential and opaque, algorithmic fairness and explainability are critical for ensuring accountability. However,

Topological Neural Dynamics: A Neuron-wise Framework for Sequence Modeling

arXiv:2606.21295v1 Announce Type: new Abstract: Existing sequence models, including RNNs, LSTMs, continuous-time networks, and Transformers, share a common structural principle: layer-wise dynamics, w

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

Unified Motion-Action Modeling for Heterogeneous Robot Learning

arXiv:2606.16917v3 Announce Type: replace Abstract: We present Unified Motion-Action (UMA) Model, an approach that uses 3D object motion trajectories as a shared interface to bridge visuomotor control

researcharxiv-cs-ro

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

Applications

What should a world model for agile quadrotor control actually provide? 📄 Arxiv: https://arxiv.org/pdf/2606.23444 🌐 Project: https://praty…

applicationsyann-lecun--x

What should a world model for agile quadrotor control actually provide? 📄 Arxiv: https://arxiv.org/pdf/2606.23444 🌐 Project: https://pratyaksh10.github.io/skyjepa-project-page/ 💻 Code: https://github.

When Is an LLM Worth It for Hyperparameter Optimization? A Budget-Matched Study on Tabular Data Finds the Warm-Start Is a Default Configuration, Not the Model

arXiv:2606.21641v1 Announce Type: new Abstract: Large language models (LLMs) have been proposed as hyperparameter-optimization (HPO) advisors that 'warm-start' search from prior knowledge, proposing s

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

3D-CBM: A Framework for Concept-Based Interpretability in Generative 3D Modeling

arXiv:2606.11446v1 Announce Type: new Abstract: This research introduces a framework for incorporating Concept Bottleneck Models (CBMs) into 3D generative architectures to address the inherent 'semant

A prior-free blind detection of information leakage from model predictions

arXiv:2606.11267v1 Announce Type: new Abstract: Data leakage -- contamination of a model with information unavailable at baseline -- is the dominant reproducibility failure in machine-learning-based s

Model Releases

Adapting Prithvi-EO for Fallow Detection for Food-Water Nexus: ViT-Adapter Necks and Parameter-Efficient Backbone tuning of Geospatial Foundation Model

model-releasesarxiv-cs-ai

arXiv:2606.12218v1 Announce Type: cross Abstract: Understanding spatial distribution of fallow land is important for optimizing the food-water (FW) nexus, given fallowing's role in crop rotation and w

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

safetyarxiv-cs-ai

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

safetyarxiv-cs-ai

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

DiffCold: A Diffusion-based Generative Model for Cold-Start Item Recommendation

arXiv:2606.12245v1 Announce Type: cross Abstract: Cold-start item recommendation remains a persistent challenge in real-world systems due to the absence of interaction histories. While prior models at

safetyarxiv-cs-ai

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

Learning What to Say to Your VLA: Mostly Harmless Vision Language Action Model Steering

arXiv:2606.12299v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models provide a natural language interface to robot control, but the mapping from language to behavior is often brittle

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

Model-based Optimization of Anguilliform Swimming Gaits for Soft Robotic Applications

arXiv:2606.11278v1 Announce Type: new Abstract: In this paper, we introduce the Soft Lamprey-Inspired Dual Environment Robot (SLIDER) and a proper modeling and optimization procedure employed to desig

researcharxiv-cs-ro

Multimodal Ordinal Modeling of Alzheimer's Disease Severity Using Structural MRI and Clinical Data

arXiv:2606.11794v1 Announce Type: cross Abstract: Neurodegenerative diseases such as Alzheimer's disease (AD) require accurate and scalable tools for assessing disease severity, yet current clinical s

researcharxiv-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

VIA-SD: Verification via Intra-Model Routing for Speculative Decoding

arXiv:2606.12243v1 Announce Type: cross Abstract: Speculative decoding (SD) addresses the high inference costs of LLMs by having lightweight drafters generate candidates for large verifiers to validat

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

Agents

A Survey on Semantic Modeling for Building Energy Management

arXiv:2404.11716v2 Announce Type: replace Abstract: Building Energy Management (BEM) is central to reducing energy use and CO2 emissions in the building sector. Although IoT technologies now provide e

agentsarxiv-cs-ai

10 Jun 2026

ARM: An AutoRegressive Large Multimodal Model with Unified Discrete Representations

arXiv:2606.11188v1 Announce Type: new Abstract: This paper introduces ARM, a discrete representation-based AutoRegressive Model that unifies image understanding, generation, and editing within a next-

10 Jun 2026

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