Search: “models”

GeoFlow: Enforcing Implicit Geometric Consistency in Video Generation

arXiv:2605.18365v1 Announce Type: new Abstract: Generating geometrically consistent videos remains an open challenge: text-to-video diffusion models trained on web-scale data treat geometry only impli

researcharxiv-cs-cv

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Geometric Scaling of Bayesian Inference in LLMs

DGX agent

arXiv:2512.23752v5 Announce Type: replace-cross Abstract: Recent work has shown that small transformers trained in controlled 'wind-tunnel'' settings can implement exact Bayesian inference, and that t

model-releasesarxiv-cs-ai

19 May 2026

Geometry-Aware Surrogate for Real-Time Hydrodynamics Estimation of Autonomous Ground Vehicles in Amphibious Environments

arXiv:2605.18543v1 Announce Type: new Abstract: Autonomous ground vehicles operating in shallow water or flood-prone terrains require dynamic models that account for hydrodynamic forces. However, the

agentsarxiv-cs-ro

Safety

Goal-Conditioned Supervised Learning for LLM Fine-Tuning

arXiv:2605.16345v1 Announce Type: cross Abstract: Large language models often require fine-tuning to better align their behavior with user intent at deployment. Existing approaches are commonly divide

safetyarxiv-cs-ai

GUIDE-VAE: Advancing Data Generation with User Information and Pattern Dictionaries

arXiv:2411.03936v2 Announce Type: replace Abstract: Generative modelling of multi-user datasets has become prominent in science and engineering. Generating a data point for a given user requires emplo

tutorialsarxiv-cs-lg

Local Ai

Incentive-Aware Federated Averaging with Performance Guarantees under Strategic Participation

arXiv:2603.20873v2 Announce Type: replace Abstract: Federated learning (FL) is a communication-efficient collaborative learning framework that enables model training across multiple agents with privat

local-aiarxiv-cs-lg

Leveraging Unsupervised Learning for Cost-Effective Visual Anomaly Detection

arXiv:2409.15980v2 Announce Type: replace-cross Abstract: Traditional machine learning-based visual inspection systems require extensive data collection and repetitive model training to improve accura

Meta-Learning Guided Pruning for Few-Shot Plant Pathology on Edge Devices

arXiv:2601.02353v3 Announce Type: replace Abstract: Farmers in remote areas need quick and reliable methods for identifying plant diseases, yet they often lack access to laboratories or high-performan

tutorialsarxiv-cs-cv

Modality vs. Morphology: A Framework for Time Series Classification for Biological Signals

arXiv:2605.18483v1 Announce Type: cross Abstract: Time series classification (TSC) of biological signals has progressed from handcrafted, modality-specific approaches to deep architectures capable of

Needles in the Landscape: Semi-Supervised Pseudolabeling for Archaeological Site Discovery under Label Scarcity

arXiv:2510.16814v2 Announce Type: replace-cross Abstract: Archaeological predictive modelling estimates where undiscovered sites are likely to occur by combining known locations with environmental, cu

Applications

Network Knowledge Prior Guided Learning for Data-Efficient Surface Defect Detection

arXiv:2605.17780v1 Announce Type: new Abstract: Deep learning-based methods have become the de facto standard for industrial defect detection. However, their data-hungry nature and inherent 'black-box

applicationsarxiv-cs-cv

OmniVL-Guard Pro: A Tool-Augmented Agent for Omnibus Vision-Language Forensics

arXiv:2605.16962v1 Announce Type: cross Abstract: Existing vision-language forgery detection and grounding methods operate under a closed-world paradigm, assuming verification can be completed by the

On Improving Multimodal Pedestrian Trajectory Prediction with CVAE: A Study on Benchmark and Robot Data

model-releasesarxiv-cs-ro

arXiv:2605.18262v1 Announce Type: new Abstract: Accurate pedestrian trajectory prediction is crucial for autonomous systems operating in complex environments, such as modular buses and delivery robots

ORACLE: Anticipating Scams from Partial Trajectories in Streaming App Usage

arXiv:2605.16363v1 Announce Type: new Abstract: Smartphone scams are increasingly prevalent and typically manifest as multi-stage, cross-application processes with gradually emerging intent. Effective

PAREDA: A Multi-Accent Speech Dataset of Natural Language Processing Research Discussions

arXiv:2605.17860v1 Announce Type: cross Abstract: While modern Automatic Speech Recognition (ASR) systems achieve high accuracy on benchmark corpora, their performance often degrades when there is rea

Prior Knowledge Makes It Possible: From Sublinear Graph Algorithms to LLM Test-Time Methods

arXiv:2510.16609v3 Announce Type: replace-cross Abstract: Test-time augmentation, such as Retrieval-Augmented Generation (RAG) or tool use, critically depends on an interplay between a model's paramet

agentsarxiv-cs-ai

Probing for Representation Manifolds in Superposition

arXiv:2605.18537v1 Announce Type: cross Abstract: This paper introduces the Manifold Probe, a supervised method for discovering representation manifolds in superposition. The method generalizes linear

Proof-Carrying Certificates for LLM Pipelines: A Trust-Boundary Architecture

arXiv:2605.16407v1 Announce Type: cross Abstract: We present a framework for verifying the deterministic structured computations surrounding a large language model rather than the model itself, extend

agentsarxiv-cs-cl

Protein Fold Classification at Scale: Benchmarking and Pretraining

arXiv:2605.18552v1 Announce Type: new Abstract: Classifying protein topology is essential for deciphering biological function, but progress is held back by the lack of large-scale benchmarks that avoi

QLIF-CAST: Quantum Leaky-Integrate-and-Fire for Time-Series Weather Forecasting

arXiv:2605.18333v1 Announce Type: cross Abstract: Accurate and efficient time-series forecasting remains a challenging problem for both classical and quantum neural architectures, particularly in mult

Local Ai

Rethinking Point Clouds as Sequences: A Causal Next-Token Predictive Learning Framework

arXiv:2605.17566v1 Announce Type: new Abstract: With the rapid progress of multimodal foundation models and predictive pre-training, an important open question is how to equip 3D point clouds with a p

local-aiarxiv-cs-cv

Revisiting the Adam-SGD Gap in LLM Pre-Training: The Role of Large Effective Learning Rates

arXiv:2605.17787v1 Announce Type: new Abstract: It is widely believed that stochastic gradient descent (SGD) performs significantly worse than adaptive optimizers such as Adam in pre-training Large La

RoboMME: Benchmarking and Understanding Memory for Robotic Generalist Policies

arXiv:2603.04639v2 Announce Type: replace-cross Abstract: Memory is critical for long-horizon and history-dependent robotic manipulation. Such tasks often involve counting repeated actions or manipula

Safety

SafeDiffusion-R1: Online Reward Steering for Safe Diffusion Post-Training

arXiv:2605.18719v1 Announce Type: new Abstract: Diffusion models have been widely studied for removing unsafe content learned during pre-training. Existing methods require expensive supervised data, e

safetyarxiv-cs-cv

Local Ai

SAMRI: Segment Any MRI

arXiv:2510.26635v3 Announce Type: replace-cross Abstract: Summary: SAMRI is an MRI-specialized adaptation of the Segment Anything Model achieving superior whole-body MRI segmentation, particularly for

local-aiarxiv-cs-cv

SENSE: Satellite-based ENergy Synthesis for Sustainable Environment

arXiv:2605.18101v1 Announce Type: cross Abstract: Urban Building Energy Modeling plays a critical role in achieving the United Nations' Sustainable Development Goals 7 and 11. Although existing studie

SocialMemBench: Are AI Memory Systems Ready for Social Group Settings?

arXiv:2605.17789v1 Announce Type: cross Abstract: Memory systems for AI assistants were built for single-user dialogue and fail characteristically when applied to multi-party social group settings. Th

Sparse-to-Dense: A Free Lunch for Lossless Acceleration of Video Understanding in LLMs

arXiv:2505.19155v2 Announce Type: replace-cross Abstract: Due to the auto-regressive nature of current video large language models (Video-LLMs), the inference latency increases as the input sequence l

researcharxiv-cs-cl

Spectral Progressive Diffusion for Efficient Image and Video Generation

arXiv:2605.18736v1 Announce Type: new Abstract: Diffusion models have been shown to implicitly generate visual content autoregressively in the frequency domain, where low-frequency components are gene

researcharxiv-cs-cv

SRC-Flow: Compact Semantic Representations Enable Normalizing Flows for Image Generation

arXiv:2605.18267v1 Announce Type: new Abstract: Normalizing flows (NFs) provide exact likelihoods and deterministic invertible sampling, but have historically lagged behind diffusion models for large-

tutorialsarxiv-cs-cv

SteadyDancer: Harmonized and Coherent Human Image Animation with First-Frame Preservation

arXiv:2511.19320v2 Announce Type: replace Abstract: Preserving first-frame identity while ensuring precise motion control is a fundamental challenge in human image animation. The Image-to-Motion Bindi

Supervise Less, See More: Training-free Nuclear Instance Segmentation with Prototype-Guided Prompting

arXiv:2511.19953v2 Announce Type: replace Abstract: Accurate nuclear instance segmentation is a pivotal task in computational pathology, supporting data-driven clinical insights and facilitating downs

TailedTS: Benchmark Dataset for Heavy-Tailed Time Series Prediction and Periodicity Quantification

arXiv:2605.16361v1 Announce Type: cross Abstract: We present TailedTS, a large-scale benchmark dataset derived from Wikipedia hourly page view observations throughout 2024, specifically designed to te

The Diffusion Duality, Chapter II: Psi-Samplers

arXiv:2602.21185v2 Announce Type: replace Abstract: Uniform-state discrete diffusion models excel at few-step generation and guidance due to their ability to self-correct, making them preferred over a

tutorialsarxiv-cs-lg

The Expressive Power of Low Precision Softmax Transformers with (Summarized) Chain-of-Thought

model-releasesarxiv-cs-cl

arXiv:2605.18079v1 Announce Type: cross Abstract: Existing expressivity results for transformers typically rely on hardmax attention, high precision, and other architectural modifications that disconn

The Neural Tangent Kernel for Classification

arXiv:2605.17606v1 Announce Type: new Abstract: In wide neural networks, the Neural Tangent Kernel (NTK) remains approximately constant during training, providing a powerful theoretical tool for study

The Silent Brush: Evaluating Artistic Style Leakage in AI Art Generation

arXiv:2605.17500v1 Announce Type: cross Abstract: Generative text-to-image models are typically trained on large-scale web-scraped datasets that include diverse visual content such as copyrighted and

tutorialsarxiv-cs-cv

TOBench: A Task-Oriented Omni-Modal Benchmark for Real-World Tool-Using Agents

arXiv:2605.16909v1 Announce Type: new Abstract: Tool-using agents are increasingly expected to operate across realistic professional workflows, where they must interpret multimodal inputs, coordinate

Towards Human-Level Book-Writing Capability

arXiv:2605.17064v1 Announce Type: new Abstract: Large language models optimized for instruction following and agentic tasks remain poorly aligned with the requirements of high-quality creative writing

agentsarxiv-cs-ai

TTE-Flash: Accelerating Reasoning-based Multimodal Representations via Think-Then-Embed Tokens

arXiv:2605.16638v1 Announce Type: new Abstract: Recent research has demonstrated that Universal Multimodal Embedding (UME) benefits significantly from Chain-of-Thought (CoT) reasoning. In this paradig

UAVFF3D: A Geometry-Aware Benchmark for Feed-Forward UAV 3D Reconstruction

arXiv:2605.17942v1 Announce Type: new Abstract: Feed-forward 3D reconstruction has recently demonstrated strong generalization across diverse scenes, yet its performance in UAV imagery remains underex

Applications

Unveiling Memorization-Generalization Coexistence: A Case Study on Arithmetic Tasks with Label Noise

arXiv:2605.18022v1 Announce Type: cross Abstract: Highly over-parameterized models can simultaneously memorize noisy labels and generalize well, yet how these behaviors coexist remains poorly understo

applicationsarxiv-cs-ai

WavFlow: Audio Generation in Waveform Space

arXiv:2605.18749v1 Announce Type: cross Abstract: Modern audio generation predominantly relies on latent-space compression, introducing additional complexity and potential information loss. In this wo

WEBSERV: A Full-Stack and RL-Ready Web Environment for Training Web Agents at Scale

model-releasesarxiv-cs-cl

arXiv:2510.16252v2 Announce Type: replace-cross Abstract: Reinforcement learning (RL) for web agents demands environments that are both effective for evaluation and efficient enough for large-scale on

Safety

White-Box Sensitivity Auditing with Steering Vectors

arXiv:2601.16398v2 Announce Type: replace-cross Abstract: Algorithmic audits are essential tools for examining systems for properties required by regulators or desired by operators. Current audits of

safetyarxiv-cs-cl

Zero-Shot Faithful Textual Explanations via Directional-Derivative Influence on Predictions

arXiv:2605.16877v1 Announce Type: new Abstract: Zero-shot textual explanations aim to make image classifiers more transparent by probing their internal representations, without relying on task-specifi

AirNav: A Large-Scale UAV Vision-and-Language Navigation Dataset with Natural and Diverse Instructions

model-releasesarxiv-cs-cl

arXiv:2601.03707v2 Announce Type: replace Abstract: Existing UAV vision-and-language navigation (VLN) benchmarks rarely provide realistic aerial scenes, natural process-level instructions, and suffici

18 May 2026

AOT-POT: Adaptive Operator Transformation for Large-Scale PDE Pre-training