Search: “models”

FlowEval: Reference-Based Evaluation of Generated User Interfaces

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While large language models (LLMs) and coding agents are often applied to user interface (UI) development, developers find it difficult to reliably assess their proficiency in visual and interaction d

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From Gentlemen to Frontiermen: Masculine Formations in English-Language Fiction (1771--1930)

DGX agent

arXiv:2607.03323v1 Announce Type: new Abstract: Masculinity in nineteenth-century fiction is not a single ideal but a field of competing scripts. Drawing on 150 British and American canonical novels f

researcharxiv-cs-cl

7 Jul 2026

From Open Loop to Closed Loop: A Test-Time Iterative Optimization Framework for Reference-Consistent Image Generation

arXiv:2607.04691v1 Announce Type: new Abstract: While controllable image generation has made significant strides by incorporating visual reference conditions, existing methods predominantly operate as

GDBR: Label Recovery Attack Against Partial Gradient Encryption in Federated Learning

arXiv:2412.12640v2 Announce Type: replace Abstract: The increasing demand for data privacy, alongside the benefits of aggregating data from networked devices, has catalyzed the emergence of federated

Hardware

Generative wave propagator

arXiv:2607.04440v1 Announce Type: cross Abstract: Seismic wavefield simulation is fundamental to seismology, but conventional finite-difference (FD) methods remain limited by numerical dispersion and

hardwarearxiv-cs-ai

GlacierCastAI: Predicting Glacier Retreat from Multi-Modal Satellite Imagery and Climate Signals

arXiv:2607.04117v1 Announce Type: cross Abstract: ERA5 seasonal climate variables contain predictive information about future glacier retreat beyond what satellite imagery alone provides, yet existing

GlaKG: A Biomarker-Centric Fundus Knowledge Graph for Explainable Glaucoma Diagnosis and Risk Assessment

arXiv:2607.04673v1 Announce Type: new Abstract: Glaucoma is a leading cause of irreversible blindness worldwide, yet most automated diagnosis systems rely on opaque deep-learning models that offer lit

Global Logic and Local Search: Dual-Stream Multimodal In-Context Learning for Verifiable Industrial Anomaly Detection

arXiv:2607.03817v1 Announce Type: new Abstract: Large Multimodal Models (LMMs) show strong few-shot generalization, but industrial anomaly detection remains difficult because defects are small, input

local-aiarxiv-cs-cv

Tutorials

GrowFields: Compositional 4D Neural Fields for Topology-Changing Plant Growth

arXiv:2607.03330v1 Announce Type: new Abstract: Quantifying plant growth dynamics from sparse longitudinal 3D observations is fundamental for agriculture and plant sciences. Yet, plants pose unique ch

tutorialsarxiv-cs-cv

GUSH3R: Everyone Everywhere All at Once as Gaussians

arXiv:2607.05243v1 Announce Type: new Abstract: Reconstructing dynamic human-scene environments from monocular videos is a challenging problem that requires jointly modeling scene geometry, camera mot

HeartVolMesh: Cardiac Volumetric Mesh Reconstruction via Covariance-Guided Graph Deformation

arXiv:2607.04243v1 Announce Type: new Abstract: Accurate patient-specific tetrahedral cardiac meshes are essential for in-silico trials, yet common segmentation-then-modelling pipelines can blur thin-

Heterogeneous Graph Condensation via Role-Aware Clustering

arXiv:2607.03097v1 Announce Type: new Abstract: Heterogeneous Graph Neural Networks (HGNNs) have exhibited remarkable efficacy in modeling complex systems with multiple types of nodes and relations, y

Industry

Hugging Face Jobs sounds like an incredible addition to LeRobot🤗 https://huggingface.co/docs/lerobot/v0.6.0/hardware_guide#hugging-face-job…

Hugging Face Jobs integration with LeRobot enables users to run robotics tasks and training jobs on Hugging Face's infrastructure, streamlining the deployment and execution of robot learning models. T

industryclem-delangue--x

!Imperio, smolVLA: The Implications of Data Poisoning on Open Source Robotics

arXiv:2607.04146v1 Announce Type: cross Abstract: This work establishes that trigger-word data poisoning of vision language action models is practical, while at the same time the open-source robotics

applicationsarxiv-cs-ai

Integrated Forward-Inverse Network for Lensless Image Reconstruction

arXiv:2607.04608v1 Announce Type: new Abstract: Lensless imaging enables compact and versatile computational cameras by replacing bulky optics with thin coded elements. However, reconstruction from th

Internal Pluralism and the Limits of Pairwise Comparisons

arXiv:2607.02672v1 Announce Type: new Abstract: Local pairwise comparisons are a standard tool for learning how people want decision rules to work, e.g., in participatory design or alignment. However,

Interpretable Nanoporous Materials Design with Symmetry-Aware Networks

arXiv:2509.15908v3 Announce Type: replace-cross Abstract: Nanoporous materials hold promise for diverse sustainable applications, yet their vast chemical space poses challenges for efficient design. M

KAN vs LSTM Performance in Time Series Forecasting

arXiv:2511.18613v2 Announce Type: replace-cross Abstract: This study presents a controlled comparison of baseline Kolmogorov-Arnold Networks (KAN), implemented via PyKAN, and Long Short-Term Memory (L

Knowledge Knows, Verbalization Tells: Disentangling Latent Directions for Mathematical Solvability in LLMs

arXiv:2607.05013v1 Announce Type: new Abstract: Although LLMs have made significant progress in mathematical reasoning, determining whether a mathematical problem is solvable remains a fundamental yet

researcharxiv-cs-cl

Agents

Latent Programming Horizons in Coding Agents

arXiv:2607.05188v1 Announce Type: new Abstract: A coding agent solving a software-engineering task spends dozens of steps reasoning, editing code, and running tests, yet little is known about what the

agentsarxiv-cs-lg

Latent Visual Cache for Video Reasoning

arXiv:2607.02607v1 Announce Type: cross Abstract: Video reasoning requires Large Multimodal Models (LMMs) to remain grounded in dense evidence, yet existing systems largely adopt 'read-once, generate-

safetyarxiv-cs-cl

Layer-Parallel Inference Reduces Encrypted Nonlinear Depth in Transformers

arXiv:2607.04819v1 Announce Type: new Abstract: Fully homomorphic encryption (FHE) enables computation on encrypted data, but practical encrypted Transformer inference is bottlenecked by the sequentia

Learning on the Manifold: Unlocking Standard Diffusion Transformers with Representation Encoders

arXiv:2602.10099v2 Announce Type: replace-cross Abstract: Leveraging representation encoders for generative modeling offers a path for efficient, high-fidelity synthesis. However, standard diffusion t

Learning with the Nash-Sutcliffe loss

arXiv:2603.00968v2 Announce Type: replace-cross Abstract: The Nash-Sutcliffe efficiency (ext{NSE}) is a widely used, positively oriented relative measure for evaluating forecasts across multiple time

Leveraging Natural Language Processing to Unravel the Mystery of Life: A Review of NLP Approaches in Genomics, Transcriptomics, and Proteomics

arXiv:2506.02212v2 Announce Type: replace-cross Abstract: Natural Language Processing (NLP) has transformed various fields beyond linguistics by applying techniques originally developed for human lang

LLM-based Human Simulations Have Not Yet Been Reliable

arXiv:2501.08579v3 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly employed for simulating human behaviors across diverse domains. However, our position is that current

safetyarxiv-cs-cl

LLM-Enhanced Hierarchical Heterogeneous Graph Representation Learning for Malicious Python Package Detection

arXiv:2607.03350v1 Announce Type: cross Abstract: Malicious Python packages have become a major threat to software supply chain ecosystems due to the widespread adoption of open-source repositories su

applicationsarxiv-cs-ai

Agents

Mask-based Predictive Representations for Reinforcement Learning

arXiv:2607.04153v1 Announce Type: cross Abstract: Vision-based deep reinforcement learning involves dealing with high-dimensional inputs of image information. It is crucial to abstract effective state

agentsarxiv-cs-ai

Measuring 3D Spatial Geometric Consistency in Dynamic Video Generation

arXiv:2603.19048v2 Announce Type: replace Abstract: Recent generative models can produce high-fidelity videos, yet they often exhibit 3D spatial geometric inconsistencies. Existing evaluation methods

Missing Data Imputation under Manifold Hypothesis

arXiv:2607.03641v1 Announce Type: cross Abstract: The manifold hypothesis posits that high-dimensional data are concentrated near a low-dimensional embedded manifold. Recent advances in mixture variat

local-aiarxiv-cs-lg

Multi-Way Representation Alignment

arXiv:2602.06205v2 Announce Type: replace-cross Abstract: The Platonic Representation Hypothesis suggests that independently trained neural networks converge to increasingly similar latent spaces. How

safetyarxiv-cs-ai

Next-Gen Sponsored Search: Crafting the Perfect Query with Inventory-Aware RAG (InvAwr-RAG) Based GenAI

arXiv:2607.03880v1 Announce Type: cross Abstract: Sponsored search plays a crucial role in e-commerce revenue generation, where advertisers strategically bid on keywords to capture the attention of us

Online Linear Programming for Multi-Objective Routing in LLM Serving

arXiv:2607.03948v1 Announce Type: new Abstract: We study the online routing problem in large language model serving, where requests arrive sequentially and must be dispatched to parallel decode worker

safetyarxiv-cs-ai

Hardware

Open-source robotics just leveled up. 🦾 @HuggingFace's LeRobot 0.6 now includes NVIDIA Isaac GR00T 1.7 and Isaac Teleop, bringing the lates…

Open-source robotics just leveled up. 🦾 @HuggingFace's LeRobot 0.6 now includes NVIDIA Isaac GR00T 1.7 and Isaac Teleop, bringing the latest Isaac models and frameworks to the open robotics community.

hardwareclem-delangue--x

OpFlow: Learning Opportunity-Conditioned Choice Potentials for Robust OD Flow Prediction

arXiv:2607.03200v1 Announce Type: new Abstract: Origin-destination (OD) flow prediction is central to urban analytics, yet deep models trained on raw counts remain vulnerable to distribution shift. Th

applicationsarxiv-cs-lg

Personalized Causal Recourse: A Human-In-The-Loop Approach

arXiv:2607.03425v1 Announce Type: new Abstract: Algorithmic recourse addresses the challenge of providing tailored recommendations to users affected by unfavorable machine learning decisions, in poten

Phase-Preserving Trimodal Transformer for Tropical Forest Biomass Estimation Using Optical and PolInSAR Data

arXiv:2607.03663v1 Announce Type: cross Abstract: The accurate estimation of Above-Ground Biomass (AGB) in mature tropical forests remains a critical challenge in remote sensing, primarily due to the

Piecewise Dynamic Diffusion Regularization for Reconstruction of Cardiac Cine MRI

arXiv:2607.03299v1 Announce Type: cross Abstract: Real-time cardiac cine MRI enables visualization of the beating heart during free breathing, but severe undersampling and motion make reconstruction h

PLGSA-Transformer: Periocular Landmark-Guided Attention with Occlusion-Adaptive Cosine Thresholding for Cross-Modal Masked and Unmasked Face Recognition

arXiv:2607.03581v1 Announce Type: cross Abstract: The widespread adoption of facial masks, accelerated by COVID-19 and mandated in security-sensitive settings, has exposed limitations of conventional

applicationsarxiv-cs-ai

PotatoGANs: Utilizing Generative Adversarial Networks, Instance Segmentation, and Explainable AI for Enhanced Potato Disease Identification and Classification

arXiv:2405.07332v2 Announce Type: cross Abstract: Numerous applications have resulted from the automation of agricultural disease segmentation using deep learning techniques. However, when applied to

PRISM: Personalized Robotic Dataset Generation via Image-based Scene and Motion Synthesis

arXiv:2607.04880v1 Announce Type: new Abstract: Recent advances in large-scale pretrained vision-language-action models have improved robot policy learning, but directly deploying such policies in use

safetyarxiv-cs-ro

Probabilistic Robustness in Medical Image Classification

arXiv:2607.03797v1 Announce Type: new Abstract: Deep learning (DL) has shown strong performance in medical image classification, but its trustworthy deployment remains challenging in safety-critical c

Progress- and Reliability-Oriented Group Policy Optimization for Agentic Reinforcement Learning

arXiv:2607.04242v1 Announce Type: new Abstract: Group-based reinforcement learning (RL) has become an effective paradigm for improving large language model agents on long-horizon interactive tasks. To

safetyarxiv-cs-ai

Progressive Refinement: An Iterative Pseudo-Labeling Approach for Mandarin-English Code-Switching ASR

arXiv:2607.05224v1 Announce Type: new Abstract: Code-switching (CS), alternating languages within the same utterance, poses significant challenges for automatic speech recognition (ASR) due to limited

researcharxiv-cs-cl

PulmoSight-XAI: An Explainable Multi-View Attention Ensemble with Gradient Boosting Meta-Learning for Multi-Label Chest X-Ray Classification

arXiv:2607.04478v1 Announce Type: cross Abstract: Automated chest X-ray classification remains challenging due to severe class imbalance, co-occurring pathologies, and the loss of localized features i

RADIANCE: Relative Adaptive Denoising with IP-Adapter for Novel Concept Enhancement

arXiv:2607.05088v1 Announce Type: new Abstract: Text-to-image (T2I) diffusion models have achieved striking progress but still struggle to synthesize rare concepts involving unusual attribute-object p

Rank-Order N-of-M Codes for Sparse Distributed Memory: Disentangling Representation and Learning Effects in Noise Robustness Against Contemporary Neuromorphic Architectures

arXiv:2607.02967v1 Announce Type: new Abstract: Large language models remain limited as continual learning systems, motivating renewed interest in Sparse Distributed Memory (SDM) as an explicit online

Agents

Real-World Perturbation Testing of Autonomous Driving Systems

arXiv:2607.04953v1 Announce Type: cross Abstract: Autonomous Driving Systems (ADS) must operate reliably under diverse conditions, yet representative data for rare or adverse scenarios is difficult to

agentsarxiv-cs-ro