Search: “pretraining”

Sat2RealCity: Geometry-Aware and Appearance-Controllable 3D Urban Generation from Satellite Imagery

arXiv:2511.11470v3 Announce Type: replace Abstract: 3D urban generation from satellite imagery is an important task for scalable digital twins and real-world simulation environments. Existing approach

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Local Ai

SeamGen: Artist-Aligned UV Seam Generation via Graph Flow Matching

DGX agent

arXiv:2607.12379v1 Announce Type: new Abstract: UV seam placement is a critical yet labor-intensive step in 3D content creation, requiring artists to balance chart shape, seam concealment, and alignme

local-aiarxiv-cs-cv

15 Jul 2026

Structure-Semantic Co-optimized Latent Diffusion Model for Fast Visual Anagram Synthesis

arXiv:2606.16241v3 Announce Type: replace Abstract: Visual anagram is an intriguing form of art creation wherein a single image presents different conceptual interpretations under transformations such

Agents

The Emerging Paradigm of Geospatial Foundation Models: From Pre-Training to Agentic Reasoning

arXiv:2607.12177v1 Announce Type: new Abstract: The analysis of satellite and aerial imagery has entered a new era with the advent of foundation models. This paper describes the concept of Geospatial

agentsarxiv-cs-ai

The Spectrum Is Not Enough: When Context Helps Time-Series Forecasting

arXiv:2607.13006v1 Announce Type: new Abstract: A growing family of indices scores how predictable a series is from its spectrum. Practitioners increasingly read these scores as answering a different

Agents

ViCo3D: Empowering LiDAR-based Collaborative 3D Object Detection with Vision Foundation Models

arXiv:2607.12959v1 Announce Type: new Abstract: LiDAR-based collaborative 3D perception in Vehicle-to-Everything (V2X) systems typically relies on fusing bird's-eye-view (BEV) features across agents.

agentsarxiv-cs-cv

Attribute Retrieving for Open-Vocabulary Endoscopic Compositional Referring Segmentation

arXiv:2607.08397v1 Announce Type: new Abstract: Referring Image Segmentation (RIS) aims to segment image regions specified by natural language, enabling fine-grained and controllable visual understand

Continual Test-Time Adaptation in Computer Vision: Methods, Benchmarks, and Future Directions

arXiv:2607.08164v1 Announce Type: new Abstract: Deep neural nets achieve remarkable performance when training and test data share the same distribution, but this assumption frequently breaks in real-w

DeepSWE: Measuring Frontier Coding Agents on Original, Long-Horizon Engineering Tasks

model-releasesarxiv-cs-lg

arXiv:2607.07946v1 Announce Type: cross Abstract: DeepSWE is a benchmark of 113 original, long-horizon software engineering tasks for evaluating coding agents. Most public agentic coding benchmarks fo

Hardware

EVIS: A Physics-Grounded Event Camera Plugin for NVIDIA Isaac Sim

arXiv:2607.08098v1 Announce Type: new Abstract: Event cameras offer microsecond temporal resolution, low latency, and high dynamic range, making them attractive for robotics. However, labeled event-ca

hardwarearxiv-cs-cv

FabriVLA: A Lightweight Vision-Language-Action Model for Precise Multi-Task Manipulation

model-releasesarxiv-cs-ro

arXiv:2607.08575v1 Announce Type: new Abstract: We present FabriVLA, a lightweight Vision-Language-Action model for Precise Multi-Task Manipulation. FabriVLA combines an InternVL3.5 vision-language ba

Local Ai

Harness VLA: Steering Frozen VLAs into Reliable Manipulation Primitives via Memory-Guided Agents

arXiv:2607.08448v1 Announce Type: new Abstract: Language-conditioned manipulation requires both precise contact-rich control and robust reasoning over language, scenes, and long horizons. End-to-end V

local-aiarxiv-cs-ro

Jet-Long: Efficient Long-Context Extension with Dynamic Bifocal RoPE

arXiv:2607.07740v1 Announce Type: cross Abstract: Modern LLMs are increasingly deployed in long-context applications such as retrieval-augmented generation, repository-level coding, and agentic workfl

ReCoLoRA: Spectrum-Aware Recursive Consolidation for Continual LLM Fine-Tuning

arXiv:2607.07719v1 Announce Type: cross Abstract: Parameter-efficient fine-tuning adapts a large language model to one task cheaply, but across a task sequence LoRA-style methods keep stacking low-ran

Selective Left-Shift: Turning Test-Time Compute and Difficulty-based Curation into Training Data for Low-Resource Code Generation

arXiv:2607.07748v1 Announce Type: new Abstract: Large Language Models achieve strong code generation for high resource languages like Python and Java but suffer sharp performance drops on Low-Resource

TypeProbe: Recovering Type Representations from Hidden States of Pre-trained Code Models

arXiv:2607.08339v1 Announce Type: cross Abstract: State-of-the-art code models achieve impressive performance, yet the extent to which they internally encode type information remains poorly understood

AI for Cultural Heritage Textiles: Fine-Tuned Latent Diffusion for Novel Ulos Motif Synthesis

arXiv:2607.06590v1 Announce Type: new Abstract: Preserving and revitalising traditional textiles such as Ulos, a cultural heritage of the Batak ethnic group in North Sumatra, Indonesia, requires balan

`Attention-Guided Cross-Temporal Clustering for Self-Supervised Video Object Segmentation

arXiv:2607.07230v1 Announce Type: new Abstract: Video object segmentation (VOS) is a fundamental task in video understanding, requiring accurate delineation and consistent tracking of objects across f

CarbonCLIP: Enhance Carbon Prediction from Satellite Imagery via Integrated Street-View Semantics and Temporal Context Training

arXiv:2607.07292v1 Announce Type: cross Abstract: Accurately estimating urban carbon emissions is critical for sustainable urban planning, yet many existing approaches remain difficult to apply consis

Collaborative Synthetic Data Generation for Knowledge Transfer in Federated Learning

arXiv:2607.07565v1 Announce Type: cross Abstract: One-shot federated learning (OSFL) addresses the communication overhead of federated learning by limiting training to a single round, but doing so wit

D2PO: Optimizing Diffusion Samplers via Dynamic Preference

arXiv:2607.06609v1 Announce Type: cross Abstract: We propose D2PO (Dynamic Direct Preference Optimization), a principled framework for optimizing diffusion sampling policies with respect to timestep s

safetyarxiv-cs-ai

Ego-Human Motion Prediction with 3D-Aware LLM

arXiv:2607.07001v1 Announce Type: new Abstract: Anticipating human motion from an egocentric perspective is fundamental for proactive assistance in AR/VR, human-robot collaboration, and embodied AI. W

Fingerprint, Not Blueprint: How Positional Schemes Set the Default Spectral Algebra of Attention

arXiv:2607.06621v1 Announce Type: new Abstract: The pre-softmax score of an attention head is a bilinear form score(i,j) = x_i^T M x_j in a learned operator M = W_q^T W_k. Because M is generally non-s

Applications

G-ZAP: A Generalizable Zero-Shot Framework for Arbitrary-Scale Pansharpening

arXiv:2603.14412v2 Announce Type: replace Abstract: Pansharpening aims to fuse a high-resolution panchromatic (PAN) image and a low-resolution multispectral (LRMS) image to produce a high-resolution m

applicationsarxiv-cs-cv

Generalist Vision-Language Models for Fast Radio Burst detection: a zero-shot benchmark against a specialized detector

model-releasesarxiv-cs-lg

arXiv:2607.07382v1 Announce Type: new Abstract: Fast Radio Bursts (FRBs) are millisecond-duration radio transients whose automated detection increasingly relies on highly specialized deep learning mod

HunyuanVideo-HOMA: Generic Human-Object Interaction in Multimodal Driven Human Animation

arXiv:2506.08797v2 Announce Type: replace Abstract: To address key limitations in human-object interaction (HOI) video generation -- specifically the reliance on curated motion data, limited generaliz

Hardware

Infinite Worlds with Versatile Interactions

arXiv:2607.07534v1 Announce Type: new Abstract: We present LingBot-World 2.0 (also known as LingBot-World-Infinity), an advanced iteration of LingBot-World featuring four distinct upgrades. (1) Our mo

hardwarearxiv-cs-cv

MADB: A Large-Scale Music Aesthetics Dataset with Professional and Multi-Dimensional Annotations

arXiv:2607.06929v1 Announce Type: cross Abstract: Music aesthetic assessment is a challenging yet underexplored problem, requiring models to capture fine-grained, multi-dimensional human perceptual ju

MedPMC: A Systematic Framework for Scaling High-Fidelity Medical Multimodal Data for Foundation Models

arXiv:2607.07673v1 Announce Type: new Abstract: Medicine is inherently multimodal, requiring clinicians to synthesize information across diverse data streams. Yet the development of multimodal foundat

Physically Grounded Monocular Depth via Nanophotonic Wavefront Encoding

arXiv:2503.15770v3 Announce Type: replace-cross Abstract: Depth foundation models (DFMs) offer strong learned priors for 3D perception from single RGB images but lack physical depth cues, leading to a

researcharxiv-cs-cv

Applications

PriGo: Test-Time Primitive Guidance to Diffusion and Flow Policies for Adaptive Robotic Manipulation

arXiv:2607.07076v1 Announce Type: new Abstract: Imitation learning has enabled remarkable progress in robotic manipulation, especially with diffusion and flow-based policies that generate complex visu

applicationsarxiv-cs-ro

Refine Thought: A Test-Time Inference Method for Embedding Model Reasoning

arXiv:2511.13726v2 Announce Type: replace-cross Abstract: We propose RT (Refine Thought), a method that can enhance the semantic reasoning ability of text embedding models. The method obtains the fina

Seeing What Matters: Lesion-Aware High-Resolution Patch Discovery and Fusion for Chest X-ray Report Generation

arXiv:2607.06909v1 Announce Type: new Abstract: Despite rapid advances in chest X-ray (CXR) foundation models, most radiology report generation (RRG) systems still rely on heavily downsampled inputs (

researcharxiv-cs-cv

SonoRank: Towards Calibration-Free Real-Time Finger Flexion Detection from Forearm Ultrasound Sequences

arXiv:2607.07542v1 Announce Type: cross Abstract: Powered prosthetic hands are frequently abandoned, largely due to the limited functionality of current devices that rely on surface electromyography (

researcharxiv-cs-cv

TF-Engram: A Train-Free Engram with SSD-Backed Memory for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2607.07388v1 Announce Type: new Abstract: Large Language Models (LLMs) store factual knowledge and domain-specific patterns implicitly in dense Transformer parameters, making knowledge expansion

Video2Reaction: Mapping Video to Audience Reaction Distribution in the Wild

arXiv:2607.06875v1 Announce Type: new Abstract: Understanding and forecasting audience reactions to video content are crucial for improving content creation, recommendation systems, and media analysis

WAM-TTT: Steering World-Action Models by Watching Human Play at Test Time

arXiv:2607.06988v1 Announce Type: cross Abstract: Steering robot foundation models (RFMs) toward new task variants or user-preferred behaviors remains challenging, often requiring additional robot dem

A Constrained Optimization Perspective of Unrolled Transformers

arXiv:2601.17257v2 Announce Type: replace Abstract: We introduce a constrained optimization framework for training transformers that behave like optimization descent algorithms. Specifically, we enfor

AbICL: In-Context Learning for Antigen-Specific Antibody Affinity Ranking

arXiv:2607.05846v1 Announce Type: cross Abstract: Accurate ranking of antibody candidates according to their binding affinity is essential for therapeutic antibody discovery. However, existing methods

BlueMagpie-TTS: A Token-Efficient Tokenizer, Language Model, and TTS for Taiwanese-Accent Code-Switching Speech

model-releasesarxiv-cs-cl

arXiv:2607.06054v1 Announce Type: cross Abstract: Off-the-shelf TTS systems are poorly adapted to Taiwanese Mandarin. Their accent defaults to other Mandarin variants, their tokenizers over-segment co

Tutorials

Breaking Spurious Correlations via Generative Randomization and Cross-Variant Self-Supervised Learning

arXiv:2607.05850v1 Announce Type: new Abstract: Deep neural networks trained with Empirical Risk Minimization (ERM) often fail under distribution shifts because they exploit spurious correlations betw

tutorialsarxiv-cs-cv

Tutorials

Canopy: A Heterograph Foundation Model for Metabolic Engineering

arXiv:2607.06224v1 Announce Type: new Abstract: Designing microbial strains that produce high-value chemicals at commercially viable titers remains a central challenge in metabolic engineering. Existi

tutorialsarxiv-cs-lg

Hardware

Design-CP: Context Parallelism for Design of Protein Nanoparticles

arXiv:2607.05439v1 Announce Type: new Abstract: Many all-atom generative protein models can in principle design large multimeric complexes by jointly modelling all chains, but their quadratic token- a

hardwarearxiv-cs-lg

Harnessing Generative Image Models for Training-Free Primitive Shape Abstraction

arXiv:2607.05568v1 Announce Type: cross Abstract: Representing 3D shapes as compact sets of geometric primitives is fundamental to robotics, simulation, and scene understanding. Generative image model

Industry Classification of GitHub Repositories Using the North American Industry Classification System (NAICS)

arXiv:2607.06505v1 Announce Type: cross Abstract: GitHub hosts hundreds of millions of public repositories, but the platform exposes no native mapping from repositories to standardized industry sector

Integrating GNSS-Derived Zenith Wet Delay into a Weather Foundation Model Improves Precipitation Forecasting

arXiv:2607.05658v1 Announce Type: cross Abstract: Global Navigation Satellite Systems (GNSS), best known for positioning, also serve weather science, as atmospheric water vapour delays their signals.

LAMP: Latent Motion Prior-Guided Real-World Learning for Dexterous Hand Manipulation

arXiv:2607.06323v1 Announce Type: new Abstract: Real-world learning for dexterous hands remains brittle because high-dimensional hand actions amplify imitation errors and make reinforcement-learning e

safetyarxiv-cs-ro

Applications

Lift3D-VLA: Lifting VLA Models to 3D Geometry and Dynamics-Aware Manipulation

arXiv:2607.06564v1 Announce Type: cross Abstract: Recently, Vision-Language-Action (VLA) models have demonstrated strong generalization across diverse tasks. However, effective robotic manipulation in

applicationsarxiv-cs-cv