Search: “models”

ShopX: A Foundation Model for Intent-to-Item Fulfillment in Agentic Shopping

arXiv:2606.31693v1 Announce Type: cross Abstract: The wave of AI-native applications is moving shopping beyond page- and feed-based browsing toward intent-driven experiences orchestrated by LLM agents

agentsarxiv-cs-ai

1 Jul 2026

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Research

StemVLA:An Open-Source Vision-Language-Action Model with Future 3D Spatial Geometry Knowledge and 4D Historical Representation

DGX agent

arXiv:2602.23721v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models integrate visual observations and language instructions to predict robot actions, demonstrating promising

researcharxiv-cs-cv

1 Jul 2026

Symmetry in language statistics shapes the geometry of model representations

arXiv:2602.15029v3 Announce Type: replace-cross Abstract: The internal representations learned by language models consistently exhibit striking geometric structure: calendar months organize into a cir

1 Jul 2026

Tutorials

World Narrative Model for Highly Controllable Video Generation: A Paradigm Shift from Pixel Sampling to Physical World Orchestration

arXiv:2606.31946v1 Announce Type: new Abstract: The fundamental obstacle to industrial grade video generation is the lack of controllability: existing models treat video as a pixel distribution sampli

tutorialsarxiv-cs-cv

1 Jul 2026

A Cognition-Emotion-Personality Framework for Modeling Human-Like Awareness and Behavior in Emergency Evacuations

arXiv:2606.29212v1 Announce Type: new Abstract: Agent-based evacuation simulations are widely used to study crowd behavior during emergencies, but many models rely on assumptions such as perfect event

agentsarxiv-cs-ai

A Theoretical Interpretation of In-Context Learning via Probabilistic Modeling

arXiv:2606.28926v1 Announce Type: cross Abstract: In-context learning (ICL) is an emerging paradigm that employs the semantic information inherent in large language models (LLMs) for generating answer

Arko-T: A Foundation Model for Text-to-Structured 3D Generation

arXiv:2606.30429v1 Announce Type: new Abstract: Text-to-3D systems can now synthesize a mechanical part from a single sentence, yet the result is a shape to render, not a design to edit. We present Ar

ClusterStyle: Modeling Intra-Style Diversity with Prototypical Clustering for Stylized Motion Generation

arXiv:2512.02453v2 Announce Type: replace Abstract: Existing stylized motion generation models have shown their remarkable ability to understand specific style information from the style motion, and i

local-aiarxiv-cs-cv

Applications

Event-VLA: Action-Conditioned Event Fusion for Robust Vision-Language-Action Model

arXiv:2606.29384v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have become an important paradigm of embodied AI. However, existing VLA models typically assume well-lit and stable

applicationsarxiv-cs-cv

Field Order Should Not Matter: Permutation-Invariant Embedding Model Fine-Tuning for Structured Metadata Retrieval

arXiv:2606.30473v1 Announce Type: cross Abstract: We study retrieval over catalogs of structured metadata, where each record is a small schema whose fields answer different kinds of query. Embedding a

Model Predictive Current Control with Harmonic Correction for Single-Phase AC-DC EV Charging

arXiv:2606.30397v1 Announce Type: cross Abstract: The increasing integration of Electric Vehicles (EVs) has imposed a growing harmonic challenge on the power grid. For AC/DC Power Factor Correction (P

Tutorials

NIVA: A Multimodal Foundation Model for Actionable Earth System Intelligence

arXiv:2606.28546v1 Announce Type: new Abstract: Recent advances in AI-driven weather and climate modeling have improved forecast skill while reducing computational cost. However, existing data-driven

tutorialsarxiv-cs-lg

Tutorials

Physics-Grounded Disentangled Flow Modeling for Brain Disease Progression Trajectory

arXiv:2606.28630v1 Announce Type: new Abstract: Forecasting longitudinal brain lesion evolution is critical for disease monitoring and treatment planning. Existing approaches typically learn a direct

tutorialsarxiv-cs-cv

Surrogate Modeling for Explainable Predictive Time Series Corrections

arXiv:2412.19897v3 Announce Type: replace-cross Abstract: We introduce a local surrogate approach for explainable time-series forecasting. An initially non-interpretable predictive model to improve th

local-aiarxiv-cs-lg

Towards Generalizable and Evidential Nuclear Magnetic Resonance-Based Molecular Structure Elucidation via Large Language Model Agent

arXiv:2606.29776v1 Announce Type: cross Abstract: Nuclear Magnetic Resonance (NMR) spectroscopy is the gold standard for molecular structure elucidation, yet interpreting complex spectra for unknown m

Mitigating LLM-based p-Hacking by Preregistering for the Next LLM

arXiv:2606.27687v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate, classify, and annotate data whose outputs feed downstream hypothesis tests. However, L

29 Jun 2026

Scaling limit of the Random Language Model

arXiv:2606.28105v1 Announce Type: cross Abstract: We develop a quantitative theory of the Random Language Model (RLM), an ensemble of stochastic context-free grammars, in a scaling limit where the num

29 Jun 2026

Stochastic Gradient Optimization with Model-Assisted Sampling

arXiv:2606.27171v1 Announce Type: new Abstract: This work addresses the problem of variance in stochastic gradient estimation for machine learning optimization. Deep learning relies on mini-batch meth

26 Jun 2026

Efficient and Trainable Language Model Test-Time Scaling via Local Branch Routing

arXiv:2606.25354v1 Announce Type: new Abstract: Test-time scaling improves language-model reasoning, but existing approaches often face a difficult trade-off: long chain-of-thought sampling remains si

local-aiarxiv-cs-cl

Learning Dynamical Systems from Multiple Sparse Datasets: A Hierarchical Bayesian Modeling Approach

arXiv:2606.24966v1 Announce Type: new Abstract: Estimating parameters of dynamical systems from sparse, noisy, and irregularly sampled data is often severely ill-conditioned. When multiple related dat

LEVIRDet: A Million-Scale 159-Category Dataset and Foundation Model for Universal Remote Sensing Object Detection

arXiv:2606.25312v1 Announce Type: new Abstract: Remote sensing object detection has advanced rapidly with the development of large-scale benchmarks and modern detection architectures. However, existin

SDE-Driven Spatio-Temporal Hypergraph Neural Networks for Irregular Longitudinal fMRI Connectome Modeling in Alzheimer's Disease

arXiv:2603.20452v2 Announce Type: replace Abstract: Longitudinal neuroimaging is essential for modeling disease progression in Alzheimer's disease (AD), yet irregular sampling and missing visits pose

SyncLoop: A Multimodal Dual-Loop Framework for Self-Improving Mathematical Reasoning

model-releasesarxiv-cs-cl

arXiv:2507.16518v3 Announce Type: replace-cross Abstract: Recent advances in multimodal large language models (MLLMs) have shown impressive reasoning capabilities. However, further enhancing existing

To Isolate or to Score? Model-Adaptive Assessment for Cost-Efficient Multi-Agent RAG

arXiv:2606.25191v1 Announce Type: cross Abstract: Multi-agent document assessment for retrieval-augmented generation is computationally expensive, driving practitioners toward smaller, deployable mode

agentsarxiv-cs-cl

Applications

What Does a Pathological Speech Assessment Model Know about Acoustic Features? A Case Study on Oral and Oropharyngeal Cancer Patients

arXiv:2606.24949v1 Announce Type: cross Abstract: This work investigates the interpretability of a Wav2Vec 2.0based speech intelligibility assessment model for oral and oropharyngeal cancer patients t

applicationsarxiv-cs-ai

Can Language Model Agents be Helpful Circuit Explainers in Mechanistic Interpretability?

arXiv:2606.24026v1 Announce Type: new Abstract: Mechanistic interpretability has made substantial progress in automatically localizing circuits, but explaining what localized components do remains lab

ErrorLLM: Modeling SQL Errors for Text-to-SQL Refinement

arXiv:2603.03742v2 Announce Type: replace Abstract: Despite the remarkable performance of large language models (LLMs) in text-to-SQL (SQL generation), correctly producing SQL queries remains challeng

Generating adversarial inputs for a graph neural network model of AC power flow

arXiv:2602.17975v2 Announce Type: replace Abstract: This work formulates and solves optimization problems to generate input points that yield high errors between a neural network's predicted AC power

Large-Language-Model Discovery of Quantum LDPC Codes through Structured Concept Evolution

arXiv:2606.24808v1 Announce Type: cross Abstract: Quantum computers could outperform classical machines on important problems, but only if the errors that pervade quantum hardware can be corrected at

Machine Learning Modeling for Real-Time Melt Pool Monitoring in Laser Powder Bed Fusion Additive Manufacturing: A Hybrid Approach

arXiv:2606.23851v1 Announce Type: cross Abstract: This work investigates the implementation of artificial intelligence and machine learning (AI/ML) for real-time monitoring in laser powder bed fusion

A Generative Model for Closed-Loop Microsimulation of Signalized Intersections

arXiv:2606.23588v1 Announce Type: new Abstract: Traffic microsimulators rely on hand-crafted behavior models that reproduce aggregate flow but miss the heterogeneous interactions between vehicles at s

safetyarxiv-cs-ro

B[FM]^2: Brain Foundation Model via Flow Matching with SplitUNet

arXiv:2606.20812v1 Announce Type: new Abstract: EEG foundation models can learn generalizable representations from large-scale EEG corpora to enable single-backbone transfer across diverse clinical an

safetyarxiv-cs-lg

CLIP-guided Diffusion Model for Backdoor Generation in Sensor-based Human Activity Recognition

arXiv:2606.22837v1 Announce Type: new Abstract: Sensors are critical components of modern intelligent devices. The proliferation of the Internet of Things (IoT) and wearable mobile devices has enabled

Cluster-Specific Localized Drift Detection for Efficient Batch Model Adaptation under Controlled Distribution Shift

arXiv:2606.22026v1 Announce Type: new Abstract: Machine learning systems deployed in dynamic environments frequently operate under nonstationary data distributions, where controlled distribution shift

Discrete Geometric Modeling and Extended State Estimation of Continuum Robots

arXiv:2606.21205v1 Announce Type: cross Abstract: In this paper, we present a fully discrete approach for the accurate and numerically efficient dynamical modeling and state estimation of continuum ro

researcharxiv-cs-ro

Distributed Model Predictive Control with Adaptive Safety Zones for Multi-Fleet Drone Operations

model-releasesarxiv-cs-ro

arXiv:2606.20651v1 Announce Type: cross Abstract: Autonomous drone swarms in space-constrained environments such as warehouses, inspection corridors, and urban delivery routes must share limited airsp

Embedding Linear Equality Constraints in Probabilistic Neural Networks for Dynamic Modelling

arXiv:2606.21728v1 Announce Type: new Abstract: Machine learning models are increasingly used to model chemical process systems, yet they often lack principled uncertainty quantification and mechanism

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

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

MemoryVAM: Integrating Memory into Video Action Model for Robot Manipulation

arXiv:2606.20679v1 Announce Type: cross Abstract: Video-world-model policies learn action-relevant representations by predicting future observations. However, they condition on only a short observatio

safetyarxiv-cs-cv

Pose Anything Anywhere:Model-free Object Poses from Arbitrary References

arXiv:2606.23634v1 Announce Type: new Abstract: Estimating the 6D pose of unseen objects is a fundamental yet challenging problem for open-world robotics and embodied perception. Model-based methods a

safetyarxiv-cs-cv

Stationary Robust Mean-Field Games under Model Mismatches

arXiv:2606.22579v1 Announce Type: new Abstract: Deploying multi-agent reinforcement learning (MARL) in the real world is often limited by model mismatches between the training simulators and the true

safetyarxiv-cs-lg

Applications

TaLK: Text-attributed Graph Dataset Distillation via Coupling Language Model with Graph-Aware Kernel

arXiv:2606.22975v1 Announce Type: new Abstract: Text-attributed graphs (TAGs) are widely used in many real-world domains, and learning on TAGs requires jointly modeling text semantics and graph struct

applicationsarxiv-cs-lg

Damage-TriageFormer: A Foundation-Model Framework for Typology-Based Building Damage Assessment from Mono-Temporal Imagery

arXiv:2606.12248v1 Announce Type: new Abstract: Decision-relevant building damage assessment is critical for prioritizing resources and recovery after a disaster, yet most automated methods either fla

Frozen Foundation-Model Embeddings Discard Small-Lesion Signal in Chest Radiography: Implications for Pre-Deployment Evaluation

arXiv:2606.11606v1 Announce Type: new Abstract: Frozen vision-transformer (ViT) foundation-model embeddings increasingly serve as the substrate for downstream chest-radiography (CXR) pipelines, yet wh

local-aiarxiv-cs-cv

Lius: Translation Model Based Instructional Lingustic Using Continual Instruction Tuning In Kupang Malay

arXiv:2606.11786v1 Announce Type: new Abstract: Large Language Models (LLMs) offer new potential for translation tasks but often experience performance degradation when handling low-resource languages

OmniLoc: A Geometry-Aware Foundation Model for Anchor-Free UE Localization Across Diverse Indoor Environments

arXiv:2606.11490v1 Announce Type: new Abstract: Indoor localization from wireless measurements remains challenging in large-scale deployments due to substantial variation in building geometry, the set

PRInTS: Reward Modeling for Long-Horizon Information Seeking

arXiv:2511.19314v2 Announce Type: replace Abstract: Information-seeking is a core capability for AI agents, requiring them to gather and reason over tool-generated information across long trajectories

agentsarxiv-cs-ai