Search: “models”

X-RACE: XAI-assisted Recurrent neural network Attribution for Channel Estimation

arXiv:2609.11211v1 Announce Type: cross Abstract: Deep learning models, notably Long Short-Term Memory (LSTM), have demonstrated promising performance in channel estimation for high-mobility vehicular

researcharxiv-cs-ai

12 Sept 2026

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Local Ai

A Dynamic Toolkit for Transmission Characteristics of Precision Reducers with Explicit Contact Geometry

DGX agent

arXiv:2604.02387v3 Announce Type: replace Abstract: Precision reducers couple contact geometry, bearing support, structural deformation, and loading history. This paper presents a dynamic toolkit conn

local-aiarxiv-cs-ro

11 Sept 2026

Applications

A Hilbert-Valued Functional Decomposition Framework for Explaining Time-Dependent Outputs

arXiv:2609.11295v1 Announce Type: cross Abstract: Feature-based explanations quantify features' influence on model predictions, but are primarily designed for scalar outputs. In many applications, how

applicationsarxiv-cs-lg

A Multi-Stage Rule-Chaining Framework for Compositional and Interpretable Cognitive Reasoning

arXiv:2609.10654v1 Announce Type: cross Abstract: The Abstraction and Reasoning Corpus (ARC) benchmarks cognitive generalization, the ability to infer and apply abstract rules from limited examples. T

Local Ai

AgentHijack: Visual Patch Attacks on Multimodal Computer-Use Agents

arXiv:2609.09212v1 Announce Type: cross Abstract: This paper presents an end-to-end evaluation framework for image-triggered command injection against computer-use agents (CUAs). The goal is to test w

local-aiarxiv-cs-ai

Agents API is a bigger deal than it seems. OpenAI's bet on making the Codex harness open-source could pay off big time here. This harness-as…

Agents API is a bigger deal than it seems. OpenAI's bet on making the Codex harness open-source could pay off big time here. This harness-as-a-service idea hasn't hit mainstream yet, but some of the m

agentsdair-ai--x

Are We Really Doing Few-Shot Learning? A Critical Examination of Pre-Training Assumptions

arXiv:2609.10851v1 Announce Type: new Abstract: Few-shot learning is commonly evaluated under protocols that pre-train a model on a large auxiliary set whose classes are disjoint from the target episo

safetyarxiv-cs-cv

Artificial Intelligence Algorithms for the Detection of Pathologies Related to Lung Cancer through Image Analysis using Convolutional Neural Networks and Data Augmentation: a systematic mapping of the literature

arXiv:2609.10652v1 Announce Type: cross Abstract: Lung cancer is one of the leading causes of death worldwide, and its early diagnosis is crucial to improving patients prognosis and quality of life. H

Local Ai

BruNet: A Cross-Domain Transfer Framework for Bruise Segmentation

arXiv:2609.11463v1 Announce Type: new Abstract: Segmenting bruises is a challenging task in medical imaging due to limited data and annotations, diffuse boundaries, and highly variable appearance. In

local-aiarxiv-cs-cv

CAP: Continuously Adaptive Perception-Blind Humanoid Locomotion via Learned Denoising

arXiv:2609.11553v1 Announce Type: new Abstract: Humanoid locomotion across complex terrain demands forward-looking exteroception to anticipate obstacles, yet this signal is unreliable in real-world de

safetyarxiv-cs-ro

Characterizing Narrative Content in Web-scale LLM Pretraining Data

arXiv:2606.19468v2 Announce Type: replace Abstract: The narrative composition of web-scale LLM pretraining corpora remains largely unexplored, even though narrative is a fundamental mode of human comm

Applications

Combining Synthetic and Real Data for Low-Resource Historical OCR: A Manchu Case Study

arXiv:2609.11495v1 Announce Type: new Abstract: Manchu, now critically endangered, was one of the principal languages of the Qing empire (1636-1912), and its extensive archival record is increasingly

applicationsarxiv-cs-lg

DNA: Differentially private Neural Augmentation for contact tracing

arXiv:2404.13381v2 Announce Type: replace Abstract: The COVID19 pandemic had enormous economic and societal consequences. Contact tracing is an effective way to reduce infection rates by detecting pot

Emergent Risks in Generative Multi-Agent Systems

arXiv:2603.27771v3 Announce Type: replace-cross Abstract: Multi-agent systems composed of large generative models are rapidly moving from laboratory prototypes to real-world deployments, where they jo

agentsarxiv-cs-cl

Local Ai

Exponential Pixelating Integral transform with dual fractal features for enhanced chest X-ray abnormality detection

arXiv:2609.10988v1 Announce Type: cross Abstract: The heightened prevalence of respiratory disorders, particularly exacerbated by a significant upswing in fatalities due to the novel coronavirus, unde

local-aiarxiv-cs-cv

From Connectivity to Rewards: Dense Reward Learning with Directed State Graphs

arXiv:2609.10781v1 Announce Type: new Abstract: The integration of graphs with Goal-Conditioned Hierarchical Reinforcement Learning (GCHRL) has received increasing attention, as graphs naturally encod

safetyarxiv-cs-lg

Fugu Max pushes the Pareto Frontier for price-performance: • 2 input / 6 output per 1M tokens. • Performance within striking distance of e…

Fugu Max pushes the Pareto Frontier for price-performance: • 2 input / 6 output per 1M tokens. • Performance within striking distance of elite models at 2x to 6x lower cost. • Best overall score on 6

researchdavid-ha--x

Incentives to Offer Algorithmic Recourse

arXiv:2301.12884v2 Announce Type: replace-cross Abstract: Algorithmic recourse promises to help applicants rejected by automated systems by explaining the changes needed to secure acceptance. What inc

safetyarxiv-cs-ai

InstantHDR: Single-forward Gaussian Splatting Initialization for HDR 3D Reconstruction

arXiv:2603.11298v3 Announce Type: replace Abstract: High dynamic range (HDR) novel view synthesis (NVS) aims to reconstruct HDR scenes from multi-exposure low dynamic range (LDR) images. Existing HDR

Meta-Learning for Classifier Selection in Image Datasets: A Feature-Driven Framework for Accuracy Prediction

arXiv:2609.11041v1 Announce Type: new Abstract: No Free Lunch theorem implies that any performance gains achieved by a classifier on a particular image distribution are necessarily offset by a loss of

Modular Kinematic Reduction of Closed-Chain Mechanisms Using Path Assembly and Defect Homotopy

arXiv:2609.11338v1 Announce Type: new Abstract: Closed kinematic chains complicate modular modeling by coupling active and passive coordinates through nonlinear closure constraints. This paper present

researcharxiv-cs-ro

Hardware

Nvidia’s Backstop Universe – Heads I Win, Tails Who Loses?

The article examines Nvidia’s role in the 11 trillion AI infrastructure boom, exploring how the company finances this growth through AI Compute, Capital and Markets models that reveal funding sources,

hardwaresemianalysis

One of the main issues with AI document parsing is that because no solution is 100% accuracy, it's hard to tell if a given page is parsed in…

One of the main issues with AI document parsing is that because no solution is 100% accuracy, it's hard to tell if a given page is parsed incorrectly: for instance a misaligned table, missing/hallucin

agentsjerry-liu--x

Output Embedding Centering for Stable LLM Pretraining

arXiv:2601.02031v3 Announce Type: replace-cross Abstract: Pretraining of large language models is not only expensive but also prone to certain training instabilities. A specific instability that often

Overpainting: Localized Context-aware Diffusion Image Editing

arXiv:2609.10811v1 Announce Type: new Abstract: We present 'overpainting', an image editing operation which offers both control over the location of the edit and awareness of the previous content in t

PathoHR: Breast Cancer Survival Prediction on High-Resolution Pathological Images

arXiv:2503.17970v2 Announce Type: replace-cross Abstract: Breast cancer survival prediction in computational pathology presents a remarkable challenge due to tumor heterogeneity. For instance, differe

Polyhedral Geometry of Time-to-First-Spike Neural Networks

arXiv:2609.11227v1 Announce Type: new Abstract: We study the expressivity of spiking neural networks, which provide a natural framework for asynchronous, event-driven computation complementary to conv

Prevalence Determines Precision:Silent Contamination in Detector-Defined Datasets

arXiv:2609.11449v1 Announce Type: new Abstract: Many ML datasets are constructed by running a detector, heuristic, or model over candidate pools; accepted items become labels. Dataset precision is the

Tutorials

Project Qualia: Recovering Experiential Music Structure from Session Co-occurrence Data

arXiv:2609.10862v1 Announce Type: cross Abstract: This report presents results from Project Qualia, an ongoing effort to determine whether experiential similarity between songs, a structure not captur

tutorialsarxiv-cs-lg

Putting Captions to the Test: Evaluating Video Caption Quality through Multiple-Choice Question Answering

researchapple-ml-research

Evaluating video captioning remains a critical challenge for Visual Large Language Models (VLLMs). Existing metrics primarily rely on matching generated text against ground-truth references. This para

Quantum State Preparation with the QNN-based SRBB Algorithm

arXiv:2503.13647v2 Announce Type: replace-cross Abstract: In this work, a novel algorithm structured on Lie algebras for the approximate quantum state preparation problem is proposed, addressing a cha

Salesforce introduces Enterprise AI Harness, AI Control Plane

Salesforce Inc. today previewed two offerings that will help customers build and manage artificial intelligence agents. Developers turn a large language model into an agent by extending it with variou

agentssiliconangle

Semi-Tensor Product-Based Multi-Term Randomized T-SVD and Its Visual Applications

arXiv:2609.11168v1 Announce Type: new Abstract: Tensor singular value decomposition (T-SVD), which is built upon the tensor-tensor product (t-product), has emerged as a powerful tool for processing hi

Semidefinite Programming for Quantum Channel Learning

arXiv:2601.12502v2 Announce Type: replace Abstract: The problem of reconstructing a quantum channel from a sample of classical data is considered. When the total fidelity can be represented as a ratio

Smart Adaptive Computing Across the Continuum: LLMs in IoT-Edge-Cloud Resource Management

arXiv:2609.09348v1 Announce Type: cross Abstract: Managing resources across IoT, edge, and cloud layers calls for continuous, context-aware decisions under constraints that rarely stay fixed. Deep rei

agentsarxiv-cs-ai

Applications

TART: A Modular Tool for Technique-Aware Audio-to-Tablature Guitar Transcription

arXiv:2609.11904v1 Announce Type: new Abstract: Automatic Music Transcription (AMT) for guitar remains limited by three challenges: existing systems often fail to capture expressive techniques such as

applicationsarxiv-cs-lg

Temporal and Multimodal Deep Learning for Cyberattack Detection in LEO Satellite Systems

arXiv:2609.10746v1 Announce Type: cross Abstract: The growing reliance on Low-Earth Orbit (LEO) satellite communication systems has increased the need for intelligent methods capable of detecting cybe

TrajFusionNet+: Transformer-Based Prediction of Pedestrian Crossing Intention via Fusion of Trajectory Representations and Scene Graphs

arXiv:2609.10806v1 Announce Type: new Abstract: The pedestrian crossing intention task involves predicting whether pedestrians are likely to cross the road from the point of view of an autonomous vehi

agentsarxiv-cs-cv

What is happening in maths right now will happen to any hard industry with verifiable problems and high value rewards. Take microchip design…

What is happening in maths right now will happen to any hard industry with verifiable problems and high value rewards. Take microchip design, nuclear or 100s of other industrial processes that are val

agentssonya-huang--x

What Language is This? Ask Your Tokenizer

arXiv:2602.17655v3 Announce Type: replace Abstract: Language Identification (LID) is an important component of many multilingual natural language processing pipelines, where it facilitates corpus cura

When Noise Fabricates Bias: The Fragility of LLM-as-a-Judge Bias Measurement under Noisy Text

arXiv:2609.11067v1 Announce Type: new Abstract: Large language models are increasingly used as judges to measure social bias in text, yet the passages they judge are often noisy, containing typos, inf

safetyarxiv-cs-cl

A Jump-Diffusion Framework for Irregular Time Series Generation

arXiv:2505.23215v2 Announce Type: replace-cross Abstract: We propose a framework for generative modeling of continuous-time processes from irregularly and asynchronously recorded data. It is based on

A Trustworthy Watermarking Framework for LLM-Generated Food Safety Content

arXiv:2609.06708v1 Announce Type: cross Abstract: Large language models are transforming many industries with their text generation abilities. However, their outputs can be easily tampered with, creat

safetyarxiv-cs-ai

A TTP by TTP Approach: Precise Malware Detection via Malicious TTP Recognition

arXiv:2609.06579v1 Announce Type: cross Abstract: Machine learning methods, and especially neural networks, are now routinely used for malware detection in network traffic. Though very effective, syst

researcharxiv-cs-ai

Accountable and uncertainty-aware evaluation of sensor-based AI under distribution shift: devices, subjects, and nearly three years underground

arXiv:2609.09257v1 Announce Type: new Abstract: Sensor-based AI systems are rarely operated under the conditions under which they were trained: devices, personnel and recording epochs change, and each

AgentBrew: Offline Tool-Use Agent Learning from Raw Real-World Trajectories

arXiv:2609.05837v1 Announce Type: new Abstract: LLM-based agents are increasingly deployed in real-world applications through tool-use APIs, yet training them for specific environments remains fundame

safetyarxiv-cs-ai

AgentGrad: Intervention-guided Prompt Optimization for Multi Agent Systems

arXiv:2609.08572v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent systems (MAS) achieve strong performance by employing specialized multiple agents, yet their performance de

agentsarxiv-cs-ai

AgenticGen: Reward-Guided Agentic Video Generation for Advertising

arXiv:2609.09187v1 Announce Type: cross Abstract: Advertising video generation is not only a video synthesis task, but also a product-conditioned reasoning problem whose success is measured by online

safetyarxiv-cs-cl