applications

Hybrid Neural-Classical Correction for Frozen Time Series Foundation Models: A Comprehensive Ablation Study on High-Frequency Stock Prediction

arXiv:2608.08825v1 Announce Type: cross Abstract: Foundation models for time series forecasting demonstrate impressive zero-shot generalization but often underperform on specialized domains such as hi

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Latent World Models with Monotone Planning Costs for Image-Goal Navigation

DGX agent

arXiv:2608.09073v1 Announce Type: new Abstract: Image-goal navigation with latent world models requires not only accurate future prediction, but also a planning cost that reliably ranks candidate acti

applicationsarxiv-cs-ro

11 Aug 2026

Length-MAX Tokenizer for Language Models

arXiv:2511.20849v2 Announce Type: replace-cross Abstract: We introduce a new tokenizer for language models that minimizes the average tokens per character, thereby reducing the number of tokens needed

Leveraging the frontier ecosystem We work with neolabs like @trajectorylabs and @EngramLab and inference + post-training infra providers lik…

applicationsfireworks-ai--x

Leveraging the frontier ecosystem We work with neolabs like @trajectorylabs and @EngramLab and inference + post-training infra providers like @baseten, @FireworksAI_HQ, and @appliedcompute to post-tra

LineGraph2Road: Structural Graph Reasoning on Line Graphs for Road Network Extraction

arXiv:2602.23290v2 Announce Type: replace Abstract: Extracting routable road networks from satellite imagery requires accurate topology recovery beyond pixel-level segmentation. Recent methods decompo

Mask-aware inference with State-Space Models

arXiv:2603.04568v2 Announce Type: replace Abstract: Many real-world computer vision tasks, such as depth completion, must handle inputs with arbitrarily shaped regions of missing or invalid data. For

MeanSR: Restoration Trajectory Learning for One-Step Perceptual Super-Resolution

arXiv:2608.09405v1 Announce Type: new Abstract: Diffusion-based super-resolution (SR) achieves strong perceptual quality but requires costly iterative denoising. Existing one-step distillation methods

Metadata Reconstruction from Values Alone: Recovering Column Semantics in Undocumented Warehouses

arXiv:2608.07946v1 Announce Type: cross Abstract: Text-to-SQL benchmarks ship schemas whose column names already say what the columns mean. Production warehouses are the inverse: cryptic identifiers,

Motion-Aware Animatable Gaussian Avatars Deblurring

arXiv:2411.16758v4 Announce Type: replace Abstract: The creation of 3D human avatars from multi-view videos is a significant yet challenging task in computer vision. However, existing techniques rely

NTIRE 2026 Low-light Enhancement: Twilight Cowboy Challenge

arXiv:2608.09782v1 Announce Type: new Abstract: This paper presents a review of the NTIRE 2026 Low-light Enhancement: Twilight Cowboy Challenge. The objective of the competition was to merge a set of

PreGress: Ranking-Native Pre-training and Prompting for Graph Node Ranking

arXiv:2608.09016v1 Announce Type: cross Abstract: Node ranking is a fundamental problem in graph information retrieval, measuring the relative importance of nodes and supporting a wide range of applic

Preserve More Details: Mitigating Content Drift in Real-World Image Super-Resolution

arXiv:2608.09373v1 Announce Type: new Abstract: Real-world image super-resolution (Real-ISR) aims to reconstruct high-quality (HQ) images from low-quality (LQ) inputs subject to diverse real-world deg

Progressive Learned Image Compression for Machine Perception

arXiv:2512.20070v2 Announce Type: replace Abstract: Recent advances in learned image codecs have extended from human perception toward machine perception However, progressive image compression with fi

Protecting patient privacy in clinical foundation models: Technical and legal perspectives

arXiv:2608.07705v1 Announce Type: new Abstract: Clinical foundation models trained on large-scale patient data are increasingly used for decision support, screening, and public health. As deployment e

Quantifying Membership Disclosure Risk for Tabular Synthetic Data Using Kernel Density Estimators

arXiv:2603.10937v2 Announce Type: replace Abstract: The use of synthetic data has become increasingly popular as a privacy-preserving alternative to sharing real datasets, especially in sensitive doma

RAG-3DSG: Enhancing 3D Scene Graphs with Re-Shot Guided Retrieval-Augmented Generation

arXiv:2601.10168v3 Announce Type: replace-cross Abstract: Open-vocabulary 3D Scene Graph (3DSG) can enhance various downstream tasks in robotics by leveraging structured semantic representations, yet

Reading Cognition as Decisions Unfold in Words: A Factorized Inverse Decision Model

arXiv:2608.09222v1 Announce Type: new Abstract: Inverse decision modeling infers latent properties of decision processes from observed behavior, but existing formulations rely primarily on action traj

applicationsarxiv-cs-cl

Real-Time Climate Risk Assessment for Supply Chain Resilience: A Data-Driven Nowcasting Framework for Colombian Agriculture

arXiv:2608.09846v1 Announce Type: new Abstract: This paper presents a methodological framework for real-time climate risk assessment using data-driven nowcasting techniques to enhance supply chain res

Rethink Before You Execute: Adaptive Execution for World Action Models

arXiv:2608.09492v1 Announce Type: new Abstract: World Action Models (WAMs) jointly predict future actions and the evolution of the environment. At each inference, a WAM generates a chunk of actions an

applicationsarxiv-cs-ro

Search over the Visual World: Persistent Visual Memory, Layered Indexes, and Source-Grounded Evidence

arXiv:2608.08075v1 Announce Type: cross Abstract: Most video-retrieval systems assume a bounded corpus and return ranked files or timestamps. Agents operating over cameras, screens, streams, and archi

SG-WAM: Text-Grounded and Spatial-aware Semantic Guidance for World-Action Models

arXiv:2608.08839v1 Announce Type: cross Abstract: World-Action Models (WAMs) have emerged as a promising paradigm for robotic manipulation. However, most existing WAMs generate future videos and actio

SHRIMP: Iterative Refinement of Robot Task Plans

arXiv:2608.08884v1 Announce Type: new Abstract: As collaborative robots have entered domains such as manufacturing, agriculture, and healthcare, programming or adapting robot behavior typically requir

applicationsarxiv-cs-ro

Singapore raises its 2026 GDP growth forecast to 4.5%-5.5% from 2%-4%, citing stronger-than-expected global AI investment and improved external demand (Bloomberg)

Bloomberg: Singapore raises its 2026 GDP growth forecast to 4.5%-5.5% from 2%-4%, citing stronger-than-expected global AI investment and improved external demand — Singapore upgraded its 2026 economic

applicationstechmeme

Snowflake moves enterprise AI beyond fragmented data pipelines

Data interoperability is quickly becoming a practical requirement for companies trying to move artificial intelligence into production. Picking the right model or adding computing capacity is only par

applicationssiliconangle

Sparse Attention to Emotion: Efficient Facial Emotion Recognition via Token Reduction

arXiv:2608.08873v1 Announce Type: new Abstract: Facial Emotion Recognition (FER) is an important task that has significant implications across various fields such as biometrics, health, and human-comp

TDMA Based Communications Control Co-Design for Cooperative Carrying: Delay Calibration and Sampling-Rate Optimization

arXiv:2608.09556v1 Announce Type: new Abstract: Multi robot teams performing cooperative transportation face a fundamental challenge: maintaining stable control while keeping communications efficient.

applicationsarxiv-cs-ro

Three Generations of Healthcare IT: From the Digital Record to the Computable Care Process

arXiv:2608.08806v1 Announce Type: new Abstract: Objective. Healthcare IT is usually organized by the technologies it adopts. We instead organize it by the unit of information a system makes computable

Towards Adaptive Super-Resolution and Quality Assessment via Test-Time Adaptation

arXiv:2608.08508v1 Announce Type: new Abstract: This paper presents doctoral research on adaptive video super-resolution and perceptual quality modeling under real-world conditions. Existing video sup

Tracing sources of epistemic uncertainty in deep learning predictions: homo- and hetero-scedastic linearized estimators

arXiv:2608.07630v1 Announce Type: new Abstract: We adapt two classical statistical estimators for quantifying uncertainty to modern deep learning, in order to provide clearer insights into uncertainty

Ultraconstructive Model Theory via Bounded Adversarial Finite Structures

arXiv:2608.07534v1 Announce Type: cross Abstract: Ultraconstructive Model Theory (UCMT) replaces idealized satisfaction, at finite compu- tational scale, by bounded adversarial survival. A finite part

Universal or Language-Family-Specific Script Unification for Cross-Lingual Transfer? A Case Study on Turkic Languages

arXiv:2608.09356v1 Announce Type: new Abstract: Closely related languages written in different scripts expose little surface overlap to multilingual models, limiting cross-lingual transfer. We compare

applicationsarxiv-cs-cl

V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control

arXiv:2608.07870v1 Announce Type: new Abstract: Improving sample efficiency remains a core challenge in reinforcement learning (RL), especially in real-world settings like robotics, where data collect

View-Adaptive Renderer for View-Consistent 2D-to-3D Generation

arXiv:2608.09110v1 Announce Type: new Abstract: Reconstructing 3D shapes from a single image remains a fundamental yet challenging problem in computer vision. Traditional monocular 3D generation pipel

Visual Distortion Detection in UGC Images Using Large Multimodal Models

arXiv:2608.09122v1 Announce Type: cross Abstract: The localized depiction of perceptual quality has long been a crucial, yet underexplored, challenge in image quality assessment (IQA). Existing approa

AdvTiles: Physical Adversarial Camouflage Clothing against Person Detectors via Learnable Tiles

arXiv:2608.06801v1 Announce Type: new Abstract: Physical adversarial attacks against person detectors have evolved from localized patches to full-body textures. However, achieving both visual naturaln

Assessing AI-generated music detection in real-world broadcast monitoring

arXiv:2608.07359v1 Announce Type: cross Abstract: The proliferation of AI-generated music in broadcast media raises concerns about transparency and fair compensation, but reliable detection under real

AtlasVLA: Persistent World-Ego State Modeling for Vision-Language-Action Models

arXiv:2608.06729v1 Announce Type: cross Abstract: While Vision-Language-Action (VLA) models have advanced embodied AI, their fundamentally reactive paradigm severely limits performance in partially ob

Autonomy-of-Heads: Data-Free Sparse Attention from Frozen Query-Key Geometry

arXiv:2608.06849v1 Announce Type: cross Abstract: Long-context LLM inference is bottlenecked by quadratic attention computation and growing KV-cache costs. Existing sparse attention and KV-compression

Can MLLMs Decode the Creative Leap? Introducing C4 for Cross-Concept Understanding

arXiv:2608.06501v1 Announce Type: new Abstract: Creative capabilities of MLLMs matter in design, communication, education, and human--AI collaboration, yet remain difficult to evaluate because explici

CANIS: Generation-Assisted 3D Canonicalization via an Image-Semantic Bridge

arXiv:2608.07256v1 Announce Type: new Abstract: Canonicalizing 3D object orientation is fundamental to 3D understanding and analysis. Existing approaches often rely on geometric cues, although 3D cano

Casting the Net! Revisiting MasterFace Impersonation Attacks

arXiv:2608.06952v1 Announce Type: cross Abstract: Impersonation is a fundamental security threat in face recognition systems (FRSs). While the security of FRSs has been challenged by various attack ve

CertBind from Multimodal Connectivity to Certifiable Retrieval Decisions

arXiv:2608.06516v1 Announce Type: cross Abstract: Lightweight connectors make frozen multimodal encoders composable at the representation level. Deployment exposes a second problem at the level of tas

Characterizing the Quality Profile of AI-Generated C++ in Production

arXiv:2608.06640v1 Announce Type: cross Abstract: The widespread integration of AI coding assistants offers undeniable boosts to engineering velocity. Yet, recent studies point to a growing trade-off,

Curriculum as Code: An AI-Assisted Architecture for Instructional Design in STEM Education

arXiv:2608.07364v1 Announce Type: new Abstract: Contribution: This paper presents a six-phase AI-assisted instructional design architecture based on the Curriculum as Code paradigm, integrating Genera

Cybersecurity is the ultimate venue for real-world RL: 2p0s game, sim-able, clean reward signals Cybersecurity in a year will be fought betw…

applicationssonya-huang--x

Cybersecurity is the ultimate venue for real-world RL: 2p0s game, sim-able, clean reward signals Cybersecurity in a year will be fought between swarms of good and bad playing an exceptionally fast, co

Direct Visual Grounding by Directing Attention of Visual Tokens

arXiv:2511.12738v2 Announce Type: replace Abstract: Vision Language Models (VLMs) mix visual tokens and text tokens. A puzzling issue is the fact that visual tokens most related to the query receive l

Equivariant Sparse Autoencoders: Mechanistic Interpretability of Neural Networks on Symmetric Data

arXiv:2511.09432v2 Announce Type: replace Abstract: Machine learning (ML) models achieve remarkable performance but remain hard to interpret due to their scale and complexity. In particular, their act

How Much AI Is in This Track? Quantifying the Proportion of AI-Generated Stems in Hybrid Music Mixtures

arXiv:2608.07285v1 Announce Type: cross Abstract: AI-generated music is increasingly used at the stem level, with producers integrating synthetic drums, basslines, or vocals alongside human-performed