Search: “models”

arXiv:2608.20532v1 Announce Type: new Abstract: NVIDIA provides a SASS disassembler but no public SASS assembler for recent data-center GPUs, limiting controlled machine-code rewriting. We present F2A

hardwarearxiv-cs-lg

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On the Transferability of Agricultural Weed Detection Under Cross-Field Distribution Shift

DGX agent

arXiv:2608.21254v1 Announce Type: new Abstract: Accurate agricultural weed detection in real-world field conditions is essential for precision agriculture, enabling targeted intervention and reducing

applicationsarxiv-cs-cv

24 Aug 2026

Ontology-Driven Structural Regularization for Document-Level Relation Extraction

arXiv:2608.20856v1 Announce Type: new Abstract: Document-Level Relation Extraction (DocRE) relies heavily on costly manually annotated datasets, while large distant supervision resources such as DocRE

researcharxiv-cs-cl

Query Efficient Structured Matrix Learning

arXiv:2507.19290v2 Announce Type: replace-cross Abstract: We study the problem of learning a structured approximation (low-rank, sparse, banded, etc.) to an unknown matrix A given access to matrix-vec

Recognition-Conditioned Reasoning: A Training-Free Multimodal-LLM Pipeline for Fine-Grained Micro-Action Understanding

arXiv:2608.21022v1 Announce Type: new Abstract: Micro-actions are subtle, short, low-amplitude body movements, such as a fidgeting hand or a slight head tilt, that humans perform with little conscious

Rethinking Expressivity and Efficiency in Test-Time Training

arXiv:2608.21308v1 Announce Type: new Abstract: Test-Time Training (TTT) enables long-context processing via continuous weight updates during inference, but current methods struggle to balance the exp

Robust Discovery of Coarse-Grained Continuum Equations from Microscopic Dynamics

arXiv:2608.20404v1 Announce Type: cross Abstract: The discovery of governing partial differential equations (PDEs) directly from spatiotemporal data has emerged as a powerful tool for understanding th

Root cause analysis via difference graph discovery from linear time-series data

arXiv:2608.21117v1 Announce Type: new Abstract: Root cause analysis aims to identify the mechanisms responsible for anomalies in complex dynamical systems. In this paper, we study root cause analysis

applicationsarxiv-cs-ai

Routing Before Looking: Query-Adaptive Evidence Acquisition for Long-form Video Understanding

arXiv:2608.20805v1 Announce Type: new Abstract: Long-form video understanding remains challenging for video agents due to the mismatch between query demands and evidence acquisition strategies. Althou

Shared Physics Responses Recover Hidden Rankings in Neural Operator Libraries

arXiv:2608.20441v1 Announce Type: new Abstract: Selecting the optimal neural-operator prediction during deployment is challenging when high-fidelity reference solutions are unavailable. We demonstrate

SPARCL: Spectral Partitioned Analytic Continual Learning

arXiv:2608.21307v1 Announce Type: new Abstract: Analytic continual learning has emerged as a strong exemplar-free alternative to gradient-based class-incremental learning because it replaces iterative

STAR-OPD: Structured Aspect-Cascade-Aware On-Policy Reward Distillation for ABSA Quadruple Extraction

arXiv:2608.20831v1 Announce Type: cross Abstract: Aspect-based sentiment analysis (ABSA) quadruple extraction requires jointly predicting target, aspect, opinion, and sentiment over reviews that often

StruProKGR: A Structural and Probabilistic Framework for Sparse Knowledge Graph Reasoning

arXiv:2512.12613v2 Announce Type: replace Abstract: Sparse Knowledge Graphs (KGs) are commonly encountered in real-world applications, where knowledge is often incomplete or limited. Sparse KG reasoni

applicationsarxiv-cs-cl

TRACE-C: Rank-Calibrated Relational Anomaly Detection for Multi-Stream Operational Telemetry

arXiv:2608.21251v1 Announce Type: new Abstract: Operational telemetry can be jointly anomalous while every individual stream stays inside its familiar range. TRACE-C is an auditable strictly-prior ran

Using Human-LLM Disagreement to Improve Checklist-Based Quality Appraisal

arXiv:2608.20385v1 Announce Type: new Abstract: Systematic reviews rely on quality appraisal of included studies, a process that is time-consuming and sensitive to ambiguity in checklist criteria. Alt

researcharxiv-cs-cl

Hardware

Valid Inference with Synthetic Data via Task Exchangeability

arXiv:2606.13629v2 Announce Type: replace-cross Abstract: There is a proliferation of work arguing for the use of synthetic data in scientific research. For example, social scientists are arguing for

hardwarearxiv-cs-ai

When Looks Do Not Lie: Discourse Structure Guided In-Context Learning for Faithful Diagram Generation

arXiv:2601.20476v2 Announce Type: replace Abstract: GenAI is widespread in educational applications; however, it is known to generate content with intrinsic and extrinsic hallucination. We introduce a

researcharxiv-cs-cl

Agents

A three-dimensional typology of agency for advanced AI systems

arXiv:2608.20041v1 Announce Type: new Abstract: Research on the agency of advanced artificial intelligence (AI) systems focuses on agency as a normative concept and on the agency of particularly agent

agentsarxiv-cs-ai

Composition-Driven Phase Evolution in Sm-Doped BiFeO3 via Latent-Field Reconstruction of Atomically Resolved STEM Data

arXiv:2608.19544v1 Announce Type: cross Abstract: Functionalities of ferroelectric materials are governed by the spatial organization and coupling of polarization, strain, lattice rotation, and struct

Electronic Navigational Chart Change Classification

arXiv:2608.20218v1 Announce Type: new Abstract: Electronic Navigational Charts (ENCs) are geospatial vector datasets used in maritime navigation systems that represent hydrographic and navigational in

Agents

From Agent Behaviour to Agent-Friendly Documentation: An Empirical Study of How Coding Agents Discover, Read, and Write Technical Documentation

arXiv:2608.20195v1 Announce Type: cross Abstract: Technical documentation is written for human developers, but an increasing share of software changes is now authored by autonomous coding agents. Whic

agentsarxiv-cs-ai

GOAG: Generative and Object-Agnostic Grasp Planner for Dexterous Robotic Manipulation

arXiv:2608.19759v1 Announce Type: cross Abstract: Multifingered grasping is a crucial robotic skill, but current deep-learning grasp planners often struggle to generalize to new objects because they a

applicationsarxiv-cs-ai

GridCodex: A RAG-Driven AI Framework for Power Grid Code Reasoning and Compliance

arXiv:2508.12682v2 Announce Type: replace Abstract: The global shift towards renewable energy presents unprecedented challenges for the electricity industry, making regulatory reasoning and compliance

ID-VTG: Image-Disambiguated Video Temporal Grounding

arXiv:2608.20127v1 Announce Type: new Abstract: Video Temporal Grounding (VTG) faces significant challenges when natural language queries must distinguish between multiple events involving visually si

Information on trajectories: martingales and random times

arXiv:2608.20337v1 Announce Type: cross Abstract: Accounting for information flow on the path space of trajectories of a nonnegative martingale yields exact variational identities for it, even at arbi

MambaX-Net: Dual-Input Mamba-Enhanced Cross-Attention Network for Longitudinal Prostate MRI Segmentation

arXiv:2510.17529v3 Announce Type: replace-cross Abstract: Active Surveillance (AS) is a treatment option for managing low and intermediate-risk prostate cancer (PCa), aiming to avoid overtreatment whi

ReynoldsFlow: Physics-Inspired Spatiotemporal Flow Representation for Video Understanding

arXiv:2503.04500v3 Announce Type: replace-cross Abstract: Video understanding has largely relied on deep spatiotemporal architectures, including 3D convolutional networks and optical flow (OF) based m

SceneGTMM: A Conformal Mapping-based Scene-Aware Transferable GNN-Transformer Dual-Graph Interaction Framework for Map Matching

arXiv:2608.19298v1 Announce Type: new Abstract: Map matching is a key technology connecting positioning data with high precision road networks, but it faces challenges in noise robustness, cross regio

Truncate Bad, Upweight Good: BoN-Style Distillation via Rank-Based Classification

arXiv:2608.19748v1 Announce Type: cross Abstract: Inference-time selection methods, such as Best-of-N, improve generation by sampling a pool of candidates and selecting the top-ranked completion accor

Unsupervised Anomaly Detection Using Flow Matching on Tabular Data

arXiv:2608.19801v1 Announce Type: new Abstract: Financial anomaly detection often relies on large unlabeled transaction logs, where anomalous samples may already be present during training. Such train

WaveVerif: Acoustic Side-Channel based Verification of Robotic Workflows

arXiv:2510.25960v2 Announce Type: replace-cross Abstract: In this paper, we present a framework that uses acoustic side-channel analysis (ASCA) to monitor and verify whether a robot correctly executes

Tutorials

Why Can't I See My Clusters? A Precision-Recall Approach to Dimensionality Reduction Validation

arXiv:2509.04222v2 Announce Type: replace Abstract: Dimensionality Reduction (DR) is widely used for visualizing high-dimensional data, often with the goal of revealing expected cluster structure. How

tutorialsarxiv-cs-lg

A Metamorphic Artificial Age Score Decision-Support Prototype for Flight-Log-Based Drone Propeller Health Monitoring

arXiv:2608.18088v1 Announce Type: new Abstract: Drone propeller faults can create safety and reliability risks when their effects are distributed across multiple flight-log channels rather than appear

Agents

A Multi-Agent Platform for Automated Enterprise Analytics and Insight Generation

arXiv:2608.18740v1 Announce Type: new Abstract: This paper proposes a multi-agent framework built on CrewAI [1] for conversational business intelligence. Five specialized AI agents operate in a sequen

agentsarxiv-cs-ai

Algorithms for adaptive and heteroskedastic linear regression at the computational threshold

arXiv:2608.18402v1 Announce Type: cross Abstract: We study finite-sample linear regression in the presence of varied and unknown label noise, focusing on the heteroskedastic and adaptive linear regres

Continuous-Time Reinforcement Learning for Controlled Hawkes Jump-Diffusions

arXiv:2608.19151v1 Announce Type: new Abstract: We study stochastic control of multivariate Hawkes-driven stochastic differential equations with machine learning algorithms in a non-Markovian setting.

safetyarxiv-cs-lg

Debiased Inference for AI-Generated Data without Gold-Standard Labels: Identification via Multiple Imperfect Measurements

arXiv:2608.18294v1 Announce Type: cross Abstract: An increasing number of scholars use AI to measure variables they subsequently include in downstream analyses. Although AI-measured variables are ofte

Europe's Climate Ambition Under Scrutiny: Evidence from Deep Learning Emission Projections

arXiv:2608.18690v1 Announce Type: cross Abstract: The European Union has committed to reducing greenhouse gas emissions 55% below 1990 levels by 2030, but whether current trends are compatible with th

FD-CanKD: Frequency-Decoupled Cross-Attention Distillation as a Refinement Prior for Compact Object Detectors

arXiv:2608.18590v1 Announce Type: new Abstract: Compact object detectors are suitable for resource-constrained visual perception, but their limited representation capacity creates an accuracy gap rela

FRAGMENT: Factorized Graph Representations for Document Generation and Editing via Entity-Aware Transformations

arXiv:2608.18679v1 Announce Type: new Abstract: Structured documents such as invoices, forms, reports, and scientific articles derive meaning from the interplay between spatial layout, textual content

From Threat Intelligence to Detection: Knowledge-driven Enrichment and Template-based Rule Grounding for Automated Sigma Rule Generation

arXiv:2608.19011v1 Announce Type: cross Abstract: Mechanisms for dynamically converting cyber threat intelligence (CTI) into actionable detection capabilities are necessary due to the rapid evolution

applicationsarxiv-cs-ai

Generalizable AI-Generated Image Detection Based on Fractal Self-Similarity in the Spectrum

arXiv:2503.08484v2 Announce Type: replace Abstract: With the rapid development of image synthesis techniques, AI-generated images have become increasingly realistic, which heightens the potential risk

Geometric Data Perturbation with Noisy-Anchor Alignment for Privacy-Preserving Collaborative Learning

arXiv:2608.18749v1 Announce Type: new Abstract: Geometric Data Perturbation (GDP) enables one-shot, privacy-preserving collaborative learning: each participant applies a distance-preserving transforma

safetyarxiv-cs-lg

Institutional Books - Visual Elements: An open-source pipeline for extracting, classifying, deduplicating, and captioning visual elements from digital book collections

arXiv:2608.18957v1 Announce Type: new Abstract: Historical book collections contain rich visual elements - such as illustrations, photographs, engravings, and decorative art - that are frequently unde

Learning What to Fail On: Failure-Mode Contextual Bandits for Adversarial Data Curation

arXiv:2608.18681v1 Announce Type: new Abstract: We introduce a failure-aware adversarial retrieval-augmented framework for improving robustness in natural language understanding. Rather than selecting

safetyarxiv-cs-cl

MIFR: A Modality-Invariant and Fair Representation Framework for Skin Disease Classification

arXiv:2608.18774v1 Announce Type: new Abstract: Skin diseases represent a major global public health burden, yet machine learning tools developed to assist in their diagnosis suffer from two critical

Local Ai

Mitigating Spectral Bias in Neural Operators for Underwater Transmission Loss Prediction

arXiv:2608.18141v1 Announce Type: cross Abstract: Predicting underwater acoustic transmission loss rapidly and accurately is crucial for real-time ocean acoustic applications. While Fourier Neural Ope

local-aiarxiv-cs-lg

On the Power of Source Screening for Learning Shared Feature Extractors

arXiv:2602.16125v3 Announce Type: replace Abstract: Learning with shared representation is widely recognized as an effective way to separate commonalities from heterogeneity across various heterogeneo

applicationsarxiv-cs-lg