Search: “papers”

Minibatch persistency, eight years later: what batch reuse costs in steps and joules, and what it saves in data

arXiv:2609.13922v1 Announce Type: new Abstract: Minibatch persistency reuses data instead of reading it: rather than drawing a fresh minibatch at every optimizer step, it takes K consecutive steps on

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Mizan: A National Benchmark for Evaluating Large Language Models on Iraqi Arabic and the Iraqi Civic Context

DGX agent

arXiv:2609.13980v1 Announce Type: cross Abstract: Arabic large-language-model (LLM) evaluation has matured around Modern Standard Arabic (MSA): aggregated leaderboards such as the Open Arabic LLM Lead

model-releasesarxiv-cs-ai

15 Sept 2026

Modeling Social Dynamics with an LLM-Enabled Agent Based Network-Dynamic (LAND) Model

arXiv:2608.00929v2 Announce Type: replace Abstract: Social dynamics encode the process in which individual network and discourse interactions aggregate into collective influence, narrative dominance a

agentsarxiv-cs-ai

Moral Rebel Agents: Decision-Making Under Conflicting Obligations

arXiv:2609.14716v1 Announce Type: new Abstract: Autonomous agents are typically obliged to follow user-assigned tasks. However, strict obedience may conflict with moral obligations that arise during e

agentsarxiv-cs-ai

Multi-source Transfer Learning of Time Series with a Shapelet-based Distance Measure

arXiv:2609.15148v1 Announce Type: new Abstract: Transfer learning is an effective technique for addressing data scarcity in deep learning for time series classification, but its success depends on the

Multi-View Structure-from-Motion Enables Oriented Projective Shape Analysis in Three Dimensions

arXiv:2609.13263v1 Announce Type: new Abstract: Projective shape analysis provides a geometric framework for studying landmark configurations in digital images acquired by pinhole cameras. In the clas

researcharxiv-cs-cv

N^2: A Unified Python Package and Test Bench for Nearest Neighbor-Based Matrix Completion

arXiv:2506.04166v3 Announce Type: replace Abstract: Nearest neighbor (NN) methods have re-emerged as competitive tools for matrix completion, offering strong empirical performance and recent theoretic

Neuron Activation-based Computation of Logical Explanations for Deep Neural Networks

arXiv:2609.14099v1 Announce Type: cross Abstract: Formal explainability of classifying neural networks (NNs) is an active area of research, providing explanations with provable guarantees of the class

Non-Asymptotic Global Convergence of PPO-Clip

arXiv:2512.16565v2 Announce Type: replace-cross Abstract: Reinforcement learning has gained attention for modern Large Language Model post-training. The actor-only variants of Proximal Policy Optimiza

One Size Does Not Fit All: Setting Inference Depth from the Questions a Deployment Actually Asks

arXiv:2609.14144v1 Announce Type: new Abstract: A transformer language model is trained to respond to any prompt, but each deployment asks only a narrow range of questions: a support assistant sees de

PACE: Progressive Angular-to-Norm Contrastive Embedding

arXiv:2609.15152v1 Announce Type: cross Abstract: Multimodal embedding models encode heterogeneous inputs into a shared embedding space, enabling efficient similarity computation across modalities and

Parameter isolation with domain-specific experts for incremental audio classification

arXiv:2609.14730v1 Announce Type: cross Abstract: To successfully deploy a model in time-varying environments such as streaming data prediction and sensing control, domain-incremental learning (DIL) h

PARSE: Provenance-Aware Retrieval Sanitization for Professional Domain LLM Agents

arXiv:2606.17467v3 Announce Type: replace-cross Abstract: Prompt injection defenses evaluated on synthetic benchmarks do not generalize to real enterprise documents, which are longer, denser, and inte

Pathwise Individual Rationality in Federated Learning: A Mechanism-Architecture Co-Design

arXiv:2609.14591v1 Announce Type: new Abstract: Participation in federated learning (FL) comes at a cost. Clients trade off privacy, communication, and compute costs for potentially greater gains in m

Patient-Level, Leakage-Aware Deep Learning for Cross-Center Periapical Radiograph Classification

model-releasesarxiv-cs-cv

arXiv:2609.14703v1 Announce Type: new Abstract: Dental caries and endodontic disease are among the most common health conditions worldwide, and intraoral periapical radiographs are central to their de

PolicyMem: Geometric Policy Memory for LLM Governance

arXiv:2609.13734v1 Announce Type: cross Abstract: As large language models (LLMs) are increasingly deployed in real-world high-stakes applications, effective governance has become essential. Existing

safetyarxiv-cs-ai

Positive Topology and Feasible Refinement: Forcing Matrices, Positivity, and Information

arXiv:2609.13523v1 Announce Type: cross Abstract: We develop a conceptual and operational account of Positive Topology starting from a basic relation between points or models and observable properties

applicationsarxiv-cs-ai

Preserving Guidance in Cost-Volume Retrieval under Extreme LiDAR Sparsity in Iterative Stereo

arXiv:2507.19738v2 Announce Type: replace Abstract: While accurate LiDAR depth has been shown to improve stereo matching, high-end LiDAR remains costly and difficult to deploy at scale, motivating gui

tutorialsarxiv-cs-cv

Privacy-Aligned Personalized Federated Learning with Compact Adaptation and Variable-Length Gaussian Communication

arXiv:2609.15950v1 Announce Type: new Abstract: Record-level differential privacy exposes a structural misalignment in personalized federated learning when client-specific variation is low-dimensional

ProIQA: A Process-Based Framework for Fine-Grained Math Item Quality Assessment

arXiv:2609.15292v1 Announce Type: new Abstract: Automatic Item Generation (AIG) is pivotal for personalized education, yet guaranteeing the pedagogical value of generated items remains a bottleneck. E

applicationsarxiv-cs-ai

ProtoCAM: Interpretable Few-Shot Mask-Guided Prototypical Learning for Breast Lesion Classification in Ultrasound Imaging

arXiv:2609.13340v1 Announce Type: cross Abstract: Breast ultrasound imaging plays an important role in the early detection and diagnosis of breast cancer, particularly for patients with dense breast t

tutorialsarxiv-cs-ai

PuzzleMate: Benchmarking MLLMs for Egocentric Puzzle Assistance

model-releasesarxiv-cs-cv

arXiv:2609.14473v1 Announce Type: new Abstract: Personal AI assistants hold the potential to evolve from digital interfaces into embodied companions capable of guiding users through complex physical a

Q-SiT: Teaching LMMs for Image Quality Scoring and Interpreting

arXiv:2503.09197v2 Announce Type: replace Abstract: Image quality scoring and interpreting are two fundamental components of Image Quality Assessment (IQA). The former quantifies image quality, while

tutorialsarxiv-cs-cv

Real-World Deployment and Performance Characterisation of Fog-Based Deep Learning for Cold-Chain Temperature Prediction over LoRaWAN

arXiv:2609.14036v1 Announce Type: cross Abstract: Fresh fruits and vegetables (FFVs) are highly perishable, and cold-chain breaks contribute significantly to global food waste. While Machine Learning

agentsarxiv-cs-lg

Representing Clinical Conditions on Vital Signs from Healthy Individuals using Latent Modeling

arXiv:2609.15379v1 Announce Type: new Abstract: Machine learning can be crucial to help scale complex signal processing applications in scenarios such as healthcare. However, these machine learning mo

tutorialsarxiv-cs-lg

RFCLLM: Evaluating LLMs' Reasoning Ability of Network Protocol State Machines

arXiv:2609.13389v1 Announce Type: new Abstract: Mapping textual specifications into formal representations is essential for ensuring the correctness of protocol designs and implementations. LLM-genera

researcharxiv-cs-cl

Robotic Servo Tracking of Moving Targets with Dynamic Imitation Constraints

arXiv:2609.14589v1 Announce Type: new Abstract: Imposing explicit trajectory constraints in robot visual servoing remains challenging. Existing tracking methods achieve fast responses by mapping visua

applicationsarxiv-cs-ro

Robust and Efficient Communication for Multi-Agent Learning

arXiv:2609.15361v1 Announce Type: cross Abstract: Effective communication is a cornerstone of distributed intelligence in Multi-Agent Reinforcement Learning (MARL), yet ensuring that generated message

agentsarxiv-cs-ai

Rotation-Based Subspace Tracking for Robust Kernel PCA on Streaming Data

arXiv:2609.15488v1 Announce Type: new Abstract: Machine learning models process large amounts of data, and Principal Component Analysis (PCA) is a widely used technique to reduce the dimensionality of

Runtime-Incremental Transformer for Reinforcement-Learning-Based Adaptive Control

arXiv:2609.13545v1 Announce Type: cross Abstract: Learning-based adaptive control of robotic manipulators with non-observable friction memory has been addressed by attention- based meta-controllers wh

Safe Meta-Reinforcement Learning via Information Space Reachability

arXiv:2609.15915v1 Announce Type: new Abstract: Meta-reinforcement learning (meta-RL) enables agents to adapt to unseen tasks with limited experience. Despite its promise, the application of meta-RL i

Safety as a Constraint: Fine-Tuning a LLM Recommender to Explain Itself

arXiv:2609.13657v1 Announce Type: new Abstract: Traditional recommender systems are typically trained to predict what item users will interact with next, but not why. However, offering personalized ev

safetyarxiv-cs-ai

SALUTE: Benchmarking and Adapting LLMs for the Defense Domain

arXiv:2609.15022v1 Announce Type: new Abstract: Defense is a knowledge-intensive domain that requires precise understanding of specialized terminology, doctrinal concepts, operational procedures, and

Same path, different: a mechanistic comparison of looped and stacked transformer encoders on 12-lead ECG

arXiv:2609.15498v1 Announce Type: new Abstract: Recurrent Transformers reusing their weights rather than stacking L distinct layers are becoming widely adopted due to their parameter efficiency [1,2,3

Scaling Hindi Quantum Natural Language Processing through Automatic Pregroup Supertagging

arXiv:2609.13721v1 Announce Type: new Abstract: Quantum Natural Language Processing (QNLP) uses pregroup grammars to translate grammatical structure into diagrammatic representations and quantum circu

researcharxiv-cs-cl

Local Ai

SCOUT-SLAM: Structurally-Coupled Dual Uncertainty-Aware 3DGS SLAM in the Wild

arXiv:2609.14634v1 Announce Type: new Abstract: Recently, 3D Gaussian Splatting SLAM (3DGS-SLAM) has gained significant momentum in simultaneous localization and 3DGS scene reconstruction. In real-wor

local-aiarxiv-cs-cv

Seeing What the Vehicle Sees: Video-Augmented Virtual Reality for Physical Autonomous Vehicles

arXiv:2609.13224v1 Announce Type: new Abstract: Autonomous vehicles are expected to improve road safety and efficiency, but passengers often remain uncertain about what the vehicle perceives and why i

safetyarxiv-cs-ro

Semantic Privacy Protection with Utility Preservation for 3D Point Clouds

model-releasesarxiv-cs-cv

arXiv:2609.13823v1 Announce Type: new Abstract: Point cloud data face serious semantic privacy risks during acquisition, transmission, and cross-institutional sharing. Existing methods mostly rely on

ShopEase: A Generative AI-Based Multi-Agent Framework for Intelligent Enterprise Customer Support Using Hybrid Retrieval-Augmented Generation

arXiv:2609.13856v1 Announce Type: new Abstract: Enterprise customer support systems must answer customer questions correctly, retrieve the right policy information, use customer context, and pass diff

SJD-SV: Speculative Jacobi Decoding with Semantics Verification for Autoregressive Image Generation

arXiv:2609.13245v1 Announce Type: new Abstract: Speculative Jacobi Decoding (SJD) is an important approach for accelerating autoregressive image generation. Although SJD has shown superior performance

researcharxiv-cs-cv

SpermYOLO: A Coordinated YOLO-Based Detector for Accurate and Efficient Sperm and Impurity Detection in Microscopic Images

arXiv:2609.14278v1 Announce Type: cross Abstract: Accurate sperm detection is essential for computer-assisted semen analysis, yet it remains challenging in microscopic images due to dense distribution

Surprising Effectiveness of Self-Demonstrations in Enhancing Schema-Ontology Mapping with LLMs

arXiv:2609.13776v1 Announce Type: new Abstract: Integrating heterogeneous relational databases into a centralized ontology remains a persistent challenge in enterprise knowledge representation, primar

Syn2Logic: End-to-End Neuromorphic Design Automation

arXiv:2608.25536v2 Announce Type: replace-cross Abstract: In this work, we propose a view on electronic Neuromorphic Design Automation (eNDA), which we see as a design automation flow that bridges com

SynGhost: Invisible and Universal Task-agnostic Backdoor Attack via Syntactic Transfer

arXiv:2402.18945v5 Announce Type: replace-cross Abstract: Although pre-training achieves remarkable performance, it suffers from task-agnostic backdoor attacks due to vulnerabilities in data and train

researcharxiv-cs-ai

SyntheticDoc: A Large Synthetic Dataset for Document Unwarping and Illumination Correction

arXiv:2609.15503v1 Announce Type: new Abstract: Deep learning models have become the standard tool for document rectification and illumination correction, yet their performance is fundamentally bound

researcharxiv-cs-cv

Talking to Me or Someone Else? Rethinking Talk-to-Me Detection in Egocentric Videos

arXiv:2609.14118v1 Announce Type: cross Abstract: Online understanding of who is talking to the camera wearer is a key capability for egocentric social interaction. However, existing talk-to-me (TTM)

Task-Distribution-Aware Counterweight Synthesis and Constrained Co-Design for Serial Manipulators

arXiv:2609.15082v1 Announce Type: cross Abstract: Passive counterweights are simple gravity compensators, but a counterweight selected from a single pose is not generally optimal for the configuration

applicationsarxiv-cs-lg

TEAR: Table Extraction with Attribute Recommendation from Texts via Large Language Models

arXiv:2609.15205v1 Announce Type: cross Abstract: Table extraction from texts is an important task for information systems, and recent approaches that prompt large language models (LLMs) with instruct