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Precision in Rice Variety Classification using Stacking-Based Ensemble Learning

arXiv:2609.10524v1 Announce Type: new Abstract: Rice, a staple food for a significant portion of the global population, exhibits remarkable diversity in its varieties, presenting substantial challenge

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Research

Predicting Estimated Times of Restoration for Electrical Outages Using Longitudinal Tabular Transformers

DGX agent

arXiv:2505.00225v2 Announce Type: replace Abstract: Utilities publish Estimated Times of Restoration (ETRs) for customer-facing storm outages, and their accuracy governs whether customers can make sou

researcharxiv-cs-lg

10 Sept 2026

Predicting upcoming visual features during eye movements yields scene representations aligned with human visual cortex

arXiv:2511.12715v2 Announce Type: replace-cross Abstract: Natural scenes are complex arrangements of objects, surfaces, and backgrounds. For the brain's visual system to effectively operate, it needs

Pretraining and Distillation Matter More Than Architecture Family for Label-Free Single-Cell Classification

model-releasesarxiv-cs-cv

arXiv:2609.09863v1 Announce Type: new Abstract: Choosing a deep learning architecture for label-free single-cell classification remains an open question, with microscopy benchmarks reporting conflicti

Safety

PRIMUS: Identity, Governance, and Verification for Multi-Agent Federations

arXiv:2609.07910v1 Announce Type: new Abstract: Multi-agent federations need governance that answers three questions under adversarial conditions: who participated (identity), did they conform (enforc

safetyarxiv-cs-ai

Local Ai

Privacy-Preserving Split Learning for Federated LLM Fine-Tuning

arXiv:2609.09794v1 Announce Type: new Abstract: Fine-tuning large language models (LLMs) on domain-specific data is essential for downstream adaptation. In many deployments, a participant cannot hold

local-aiarxiv-cs-lg

ProbPlug: A Plugin Uncertainty Network for Reliable Confidence in LLM Binary Classification

arXiv:2609.10122v1 Announce Type: new Abstract: Large language models (LLMs) have achieved strong performance across a broad range of classification settings, yet the reliability of their predictions

researcharxiv-cs-cl

ProcArena: A Multi-Scenario Benchmark for LLMs on Direct and Interactive PL/SQL Development from Natural Language

arXiv:2609.06527v1 Announce Type: cross Abstract: Large language models (LLMs) have shown strong potential for translating natural-language (NL) requirements into PL/SQL programs, attracting increasin

Local Ai

Procedural Graphs: Self-Evolving Execution Structures for LLM Agents

arXiv:2609.09153v1 Announce Type: new Abstract: Large language models are increasingly deployed as agents that plan over long horizons and act through external tools. Most agents select actions throug

local-aiarxiv-cs-ai

Programmable World Model

model-releasesarxiv-cs-cv

arXiv:2609.10540v1 Announce Type: new Abstract: Recent video world models generate increasingly realistic and interactive visual experiences, yet lack reliable mechanisms for maintaining persistent wo

ProMeta: Few-shot PROTAC-targeted degradation prediction across E3 ligases

model-releasesarxiv-cs-lg

arXiv:2609.09891v1 Announce Type: new Abstract: Proteolysis-targeting chimeras (PROTACs) have emerged as a transformative therapeutic strategy that selectively degrades historically ''undruggable'' ta

Proof-Carrying Cognition: Closing the Verification Gap with Reality-Settled Reward

model-releasesarxiv-cs-lg

arXiv:2609.09776v1 Announce Type: cross Abstract: Frontier gains in language-model reasoning come from reinforcement learning on reasoning traces and are concentrated in domains with a cheap, sound ve

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

model-releasesarxiv-cs-cv

arXiv:2609.09973v1 Announce Type: new Abstract: Evaluating video captioning remains a critical challenge for Visual Large Language Models (VLLMs). Existing metrics primarily rely on matching generated

Qiushi Engine on AstaBench E2E-Bench-Hard

arXiv:2609.08196v1 Announce Type: new Abstract: This report analyzes Qiushi Engine v0.8 across all 40 test tasks in AstaBench E2E-Bench-Hard, a benchmark that requires autonomous agents to carry a res

Quality Metrics for LLM-Generated Asset Administration Shells: A Perturbation-Based Evaluation Approach

arXiv:2609.07290v1 Announce Type: cross Abstract: The rapid digital transformation of manufacturing, often referred to as Industry 4.0, relies on seamless interoperability between physical and softwar

Quantifying the Engagement Trap: Impact of Short-form Video Recommender Systems on Users with ADHD

arXiv:2609.07795v1 Announce Type: cross Abstract: Short-form video platforms use recommender systems to maximize engagement through highly efficient personalized recommendations. However, the impact o

Quantile-Led Feature Extraction for Multi-Horizon Predictive Maintenance in Industrial Manufacturing Systems

arXiv:2609.07533v1 Announce Type: new Abstract: In data-driven predictive maintenance (PdM), feature extraction is usually treated as fixed preprocessing: a descriptor set is chosen once and reused wh

applicationsarxiv-cs-ai

Safety

Quantization Amplifies Determinism, Not Bias: Scale-Dependent Behavioral Effects of Serving-Time Weight Compression

arXiv:2609.07901v1 Announce Type: new Abstract: Weight quantization largely determines the economics of serving open-weight LLMs. Its costs are usually assessed with capability benchmarks, on which 4-

safetyarxiv-cs-ai

Quantum Feature Engineering for Credit Default Prediction: When and Why IQP Circuits Help Linear Classifiers

arXiv:2609.10505v1 Announce Type: new Abstract: Credit default prediction is a tabular classification problem in which modest gains in F1 translate directly into reduced financial exposure. We ask whe

researcharxiv-cs-lg

Query-Aware Token Budgeting for Efficient Late-Interaction Visual Document Retrieval

arXiv:2609.07262v1 Announce Type: cross Abstract: Late-interaction visual document retrievers preserve fine-grained page evidence by storing many token embeddings per page, but the resulting storage a

Query Brand Entity Linking in E-Commerce Search

arXiv:2502.01555v3 Announce Type: replace-cross Abstract: Associating user search queries with the correct brand entity is critical for e-commerce product retrieval, yet remains challenging due to the

researcharxiv-cs-lg

Qwen-Audio-3.0-ASR Technical Report

arXiv:2609.07549v2 Announce Type: replace Abstract: In recent years, automatic speech recognition (ASR) has witnessed transformative advancements driven by three complementary paradigms: data scaling,

Hardware

RAGMark: A Comprehensive Framework for Benchmarking Retrieval-Augmented Generation Systems

arXiv:2609.05760v1 Announce Type: cross Abstract: We present RAGMark, a modular benchmarking framework for advanced Retrieval-Augmented Generation (RAG) systems targeting small-scale multi-GPU environ

hardwarearxiv-cs-ai

RAP: Research Attention Prediction Reveals Target-Conditioned Evidence Acquisition Biases

arXiv:2609.10092v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly act as research agents, yet their ability to track shifts in research attention is difficult to evaluate bec

RAPID: Reliability-Aware Pair Importance Distillation

arXiv:2609.05481v1 Announce Type: new Abstract: Inter example relational distillation transfers a teacher's representation geometry by matching relations among examples within a mini batch. Computing

Tutorials

RAU: Reference-based Anatomical Understanding with Vision Language Models

arXiv:2509.22404v2 Announce Type: replace Abstract: Anatomical understanding, which is the ability to identify, localize, or segment anatomical structures, is critical in medical image analysis; howev

tutorialsarxiv-cs-cv

Reading a Legal Question Word by Word: Embedding Trajectories of 2,144 Vietnamese Legal Headlines

arXiv:2609.08372v2 Announce Type: replace Abstract: A dense retriever encodes a question as one vector, but the question arrives one word at a time. We read 2,144 held-out headlines from Thu Vien Phap

Real-time and adaptive anomaly detection algorithm for cyclostationary models

arXiv:2609.09326v1 Announce Type: cross Abstract: This article introduces PeriodicCALM, an effective real-time anomaly detection framework designed for cyclostationary data streams. While classical cy

applicationsarxiv-cs-lg

RealSimLoop: Online Real-to-Sim Adaptation via Differentiable Reduced-Order Simulation with Vision Feedback

arXiv:2609.09828v1 Announce Type: cross Abstract: Real-world observations of deformable objects are often sparse or surface-level, while downstream tasks require hidden physical quantities such as int

applicationsarxiv-cs-cv

Reasoning-Aware Compression: Identifying and Protecting Vulnerable Reasoning Circuits for Energy-Efficient LLM Deployment

arXiv:2609.05512v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) impose substantial energy costs during deployment, yet current compression methods apply uniform quantization across all c

Tutorials

Recompilation Is Not Enough: Test-Guided Decompiled-C Repair

arXiv:2609.07201v1 Announce Type: cross Abstract: Decompiled C often becomes recompilable only after repair, but recompilation alone does not establish test-observed behavior. A recompiled command-lin

tutorialsarxiv-cs-ai

Recovering Biomechanical Signals from Missing Keypoints Using Temporal Interpolation in Monocular Gait Analysis

arXiv:2609.09670v1 Announce Type: new Abstract: Monocular pose estimation enables low-cost gait analysis but is sensitive to missing keypoints caused by occlusion, detection errors, or efficiency-driv

Recovering Temporal and Geographic Signals from Language Model Embeddings

arXiv:2609.05721v1 Announce Type: new Abstract: Understanding whether language-model embeddings encode structured real-world information is important for both representation analysis and information r

applicationsarxiv-cs-ai

Recovering topological information of light by topological learning

arXiv:2609.06542v1 Announce Type: cross Abstract: The evolution of modern-day communication networks towards optical solutions with enhanced capacity and robustness is driving interest in topological

RedKnot-MLA: Multi-Head Offline-Online Reuse for DeepSeek-V4 Long-Context Serving

arXiv:2609.07008v1 Announce Type: new Abstract: Multi-head latent attention (MLA) exposes many logical query heads through one packed latent KV stream. This representation is memory efficient, but it

Reducing Hallucinations in LLM-based Scientific Literature Analysis Using Peer Context Outlier Detection

arXiv:2604.01461v2 Announce Type: replace Abstract: Reducing hallucinations in Large Language Models (LLMs) is essential for accurate data extraction from large text corpora. Current methods, like pro

Regularized Estimation and Feature Selection in Mixtures of Generalized Linear Experts

model-releasesarxiv-cs-lg

arXiv:1907.06994v2 Announce Type: replace-cross Abstract: Mixtures of experts (MoE) are conditional mixture models in which both the mixing proportions and the component densities depend on the predic

Reliability-Aware Hybrid-K Ensemble Selection for Cervical Cytology Classification: Integrating Discrimination, Calibration, and Selective Prediction

arXiv:2609.09189v1 Announce Type: cross Abstract: High classification accuracy alone is insufficient for clinical image analysis, where calibrated confidence and reliable uncertainty estimates are ess

Reproducing Omitted Temporal Expressions in Japanese News for Retrieval-Augmented Applications

arXiv:2609.09569v1 Announce Type: new Abstract: News articles often contain omitted temporal expressions, such as day-only or month-only mentions, which must be interpreted with reference to the publi

researcharxiv-cs-cl

Agents

ResidualAuth: What Authorization State Must Language Agents Preserve under Revocable Delegation?

arXiv:2609.08062v1 Announce Type: new Abstract: Tool-using language agents can delegate and revoke permissions while acting through external services. We show that two authorization histories can have

agentsarxiv-cs-ai

Rethinking Sign Language Translation: The Impact of Signer Dependence on Model Evaluation

arXiv:2609.07965v1 Announce Type: cross Abstract: Sign Language Translation has advanced with deep learning, yet evaluations remain largely signer-dependent, with overlapping signers across train/dev/

Retrofitting Code Using LLMs to Support Exceptional Behavior

arXiv:2609.10397v1 Announce Type: cross Abstract: Exception Related Code (ERC), which includes throw statements, conditions (if statements) that guard those throw statements, and try/catch blocks, is

Revisiting the Shape Convention of Transformer Language Models

arXiv:2602.06471v2 Announce Type: replace Abstract: The architectural shape of dense Transformers has remained remarkably stable: narrow-wide-narrow feed-forward networks (FFNs) consume most non-embed

Safety

Revoked but Still Authoritative: An Empirical Study of Revocation Enforcement in Agent-Memory Systems

arXiv:2609.08258v1 Announce Type: new Abstract: Long-running language-model agents depend on persistent memory. Many agent-memory systems preserve history through soft revocation: a contradicted fact

safetyarxiv-cs-ai

RiLM: Parameter-Efficient Language Modeling via Geodesic Decoding

arXiv:2609.10305v1 Announce Type: new Abstract: Language models under one million parameters matter for edge deployment, domain adaptation, and reproducible research, yet a two-layer LSTM or Transform

Risk-Constrained Belief-Space Optimization for Safe Control under Latent Uncertainty

model-releasesarxiv-cs-ro

arXiv:2604.03868v2 Announce Type: replace-cross Abstract: Many safety-critical control systems operate under latent uncertainty that sensors cannot resolve at decision time. Such uncertainty, arising

Risk Is Not Review Value: Wrong-Answer Exposure Under Bounded Review Budgets

arXiv:2609.07095v1 Announce Type: new Abstract: LLM assistants often produce more answers than humans can review before users see them. Most evaluations ask whether an answer is wrong, unsupported, or

ROAM: Robust Organization of Atomic Memories for Agents through Semantic Relations

arXiv:2609.09778v1 Announce Type: new Abstract: Long-term language-model agents rely on external memory across interactions. Atomic memories are particularly useful: their fine-grained semantic bounda

researcharxiv-cs-cl