{"total":62,"rows":[{"id":"2102.10274","title":"Concealed Object Detection","created":"2021-02-20","cited_by_count":212,"area":null},{"id":"2103.12828","title":"Learning to Optimize: A Primer and A Benchmark","created":"2021-03-23","cited_by_count":208,"area":null},{"id":"2301.08727","title":"Neural Architecture Search: Insights from 1000 Papers","created":"2023-01-20","cited_by_count":139,"area":null},{"id":"2505.13259","title":"From Automation to Autonomy: A Survey on Large Language Models in Scientific Discovery","created":"2025-05-19","cited_by_count":93,"area":null},{"id":"2204.06504","title":"DL4SciVis: A State-of-the-Art Survey on Deep Learning for Scientific Visualization","created":"2022-04-13","cited_by_count":32,"area":null},{"id":"2204.09078","title":"AutoField: Automating Feature Selection in Deep Recommender Systems","created":"2022-04-19","cited_by_count":30,"area":null},{"id":"2103.16349","title":"Historical Inertia: A Neglected but Powerful Baseline for Long Sequence Time-series Forecasting","created":"2021-03-30","cited_by_count":26,"area":null},{"id":"2107.08861","title":"VolcanoML: Speeding up End-to-End AutoML via Scalable Search Space Decomposition","created":"2021-07-19","cited_by_count":25,"area":null},{"id":"2101.04296","title":"Fits and Starts: Enterprise Use of AutoML and the Role of Humans in the Loop","created":"2021-01-12","cited_by_count":21,"area":null},{"id":"2104.04987","title":"AutoGL: A Library for Automated Graph Learning","created":"2021-04-11","cited_by_count":15,"area":null},{"id":"2104.10625","title":"Searching to Sparsify Tensor Decomposition for N-ary Relational Data","created":"2021-04-21","cited_by_count":13,"area":null},{"id":"2111.00180","title":"Hierarchical Heterogeneous Graph Representation Learning for Short Text Classification","created":"2021-10-30","cited_by_count":13,"area":null},{"id":"2201.06834","title":"Hyper-Tune: Towards Efficient Hyper-parameter Tuning at Scale","created":"2022-01-18","cited_by_count":13,"area":null},{"id":"2107.00184","title":"Bilinear Scoring Function Search for Knowledge Graph Learning","created":"2021-07-01","cited_by_count":11,"area":null},{"id":"2204.13160","title":"AutoLossGen: Automatic Loss Function Generation for Recommender Systems","created":"2022-04-27","cited_by_count":10,"area":null},{"id":"2107.02378","title":"Learning an Explicit Hyperparameter Prediction Function Conditioned on Tasks","created":"2021-07-06","cited_by_count":9,"area":null},{"id":"2109.09587","title":"Recommender systems based on graph embedding techniques: A comprehensive review","created":"2021-09-20","cited_by_count":8,"area":null},{"id":"2601.11340","title":"Neural Chain-of-Thought Search: Searching the Optimal Reasoning Path to Enhance Large Language Models","created":"2026-01-16","cited_by_count":8,"area":"lr"},{"id":"2311.00447","title":"On the Opportunities of Green Computing: A Survey","created":"2023-11-01","cited_by_count":7,"area":null},{"id":"2503.23314","title":"SPIO: Ensemble and Selective Strategies via LLM-Based Multi-Agent Planning in Automated Data Science","created":"2025-03-30","cited_by_count":7,"area":"lr"},{"id":"2302.03255","title":"DivBO: Diversity-aware CASH for Ensemble Learning","created":"2023-02-07","cited_by_count":6,"area":null},{"id":"2110.06830","title":"CONetV2: Efficient Auto-Channel Size Optimization for CNNs","created":"2021-10-13","cited_by_count":4,"area":"distill"},{"id":"2205.04139","title":"The Roles and Modes of Human Interactions with Automated Machine Learning Systems","created":"2022-05-09","cited_by_count":4,"area":null},{"id":"2208.13116","title":"An Empirical Study on the Usage of Automated Machine Learning Tools","created":"2022-08-28","cited_by_count":4,"area":null},{"id":"2405.17309","title":"Survey of Graph Neural Network for Internet of Things and NextG Networks","created":"2024-05-27","cited_by_count":4,"area":null},{"id":"2411.01535","title":"Customized Subgraph Selection and Encoding for Drug-drug Interaction Prediction","created":"2024-11-03","cited_by_count":4,"area":null},{"id":"2106.07453","title":"Efficient Data-specific Model Search for Collaborative Filtering","created":"2021-06-14","cited_by_count":3,"area":null},{"id":"2201.01289","title":"Self-directed Machine Learning","created":"2022-01-04","cited_by_count":3,"area":null},{"id":"2306.07995","title":"Semantic-Based Neural Network Repair","created":"2023-06-12","cited_by_count":3,"area":null},{"id":"2307.11004","title":"Efficient and Joint Hyperparameter and Architecture Search for Collaborative Filtering","created":"2023-07-12","cited_by_count":3,"area":null},{"id":"2506.20494","title":"Multimodal Representation Learning and Fusion","created":"2025-06-25","cited_by_count":3,"area":null},{"id":"2510.04116","title":"Searching Meta Reasoning Skeleton to Guide LLM Reasoning","created":"2025-10-05","cited_by_count":3,"area":"lr"},{"id":"2104.00513","title":"Auto-KWS 2021 Challenge: Task, Datasets, and Baselines","created":"2021-03-31","cited_by_count":2,"area":null},{"id":"2107.13186","title":"AutoML Meets Time Series Regression Design and Analysis of the AutoSeries Challenge","created":"2021-07-28","cited_by_count":2,"area":null},{"id":"2108.13009","title":"Communication-Computation Efficient Device-Edge Co-Inference via AutoML","created":"2021-08-30","cited_by_count":2,"area":null},{"id":"2109.05319","title":"HyP-ABC: A Novel Automated Hyper-Parameter Tuning Algorithm Using Evolutionary Optimization","created":"2021-09-11","cited_by_count":2,"area":null},{"id":"2110.09770","title":"AEFE: Automatic Embedded Feature Engineering for Categorical Features","created":"2021-10-19","cited_by_count":2,"area":null},{"id":"2303.04068","title":"VOCALExplore: Pay-as-You-Go Video Data Exploration and Model Building [Technical Report]","created":"2023-03-07","cited_by_count":2,"area":null},{"id":"2107.10495","title":"Benchmarking AutoML Frameworks for Disease Prediction Using Medical Claims","created":"2021-07-22","cited_by_count":1,"area":null},{"id":"2204.01715","title":"BigDL 2.0: Seamless Scaling of AI Pipelines from Laptops to Distributed Cluster","created":"2022-04-03","cited_by_count":1,"area":null},{"id":"2307.14283","title":"General Purpose Artificial Intelligence Systems (GPAIS): Properties, Definition, Taxonomy, Societal Implications and Responsible Governance","created":"2023-07-26","cited_by_count":1,"area":null},{"id":"2311.14214","title":"Extending Variability-Aware Model Selection with Bias Detection in Machine Learning Projects","created":"2023-11-23","cited_by_count":1,"area":null},{"id":"2402.11641","title":"Towards Versatile Graph Learning Approach: from the Perspective of Large Language Models","created":"2024-02-18","cited_by_count":1,"area":null},{"id":"2511.15315","title":"Robust Bayesian Optimisation with Unbounded Corruptions","created":"2025-11-19","cited_by_count":1,"area":null},{"id":"2102.12036","title":"DNN2LR: Automatic Feature Crossing for Credit Scoring","created":"2021-02-24","cited_by_count":0,"area":null},{"id":"2109.08028","title":"Neural Architecture Search in operational context: a remote sensing case-study","created":"2021-09-15","cited_by_count":0,"area":null},{"id":"2112.08511","title":"OptABC: an Optimal Hyperparameter Tuning Approach for Machine Learning Algorithms","created":"2021-12-15","cited_by_count":0,"area":null},{"id":"2203.12469","title":"3D Adapted Random Forest Vision (3DARFV) for Untangling Heterogeneous-Fabric Exceeding Deep Learning Semantic Segmentation Efficiency at the Utmost Accuracy","created":"2022-03-23","cited_by_count":0,"area":null},{"id":"2205.07860","title":"AdaCap: Adaptive Capacity control for Feed-Forward Neural Networks","created":"2022-05-09","cited_by_count":0,"area":null},{"id":"2206.09423","title":"Efficient End-to-End AutoML via Scalable Search Space Decomposition","created":"2022-06-19","cited_by_count":0,"area":null},{"id":"2207.11673","title":"AutoWeird: Weird Translational Scoring Function Identified by Random Search","created":"2022-07-24","cited_by_count":0,"area":null},{"id":"2210.17545","title":"Unclonability and Quantum Cryptanalysis: From Foundations to Applications","created":"2022-10-31","cited_by_count":0,"area":null},{"id":"2305.11390","title":"ALT: An Automatic System for Long Tail Scenario Modeling","created":"2023-05-19","cited_by_count":0,"area":null},{"id":"2307.00758","title":"Structured Network Pruning by Measuring Filter-wise Interactions","created":"2023-07-03","cited_by_count":0,"area":null},{"id":"2308.08504","title":"ResBuilder: Automated Learning of Depth with Residual Structures","created":"2023-08-16","cited_by_count":0,"area":null},{"id":"2310.19841","title":"An interpretable clustering approach to safety climate analysis: examining driver group distinction in safety climate perceptions","created":"2023-10-30","cited_by_count":0,"area":null},{"id":"2311.17124","title":"A knowledge-driven AutoML architecture","created":"2023-11-28","cited_by_count":0,"area":null},{"id":"2312.04918","title":"Pruning Convolutional Filters via Reinforcement Learning with Entropy Minimization","created":"2023-12-08","cited_by_count":0,"area":null},{"id":"2509.17734","title":"An AutoML Framework using AutoGluonTS for Forecasting Seasonal Extreme Temperatures","created":"2025-09-22","cited_by_count":0,"area":null},{"id":"2603.21698","title":"A Blueprint for Self-Evolving Coding Agents in Vehicle Aerodynamic Drag Prediction","created":"2026-03-23","cited_by_count":0,"area":"agents"},{"id":"2606.07342","title":"LLM-Guided Evolution for Medical Decision Pipelines","created":"2026-06-05","cited_by_count":0,"area":null},{"id":"2606.09004","title":"LATTEArena: An Evaluation Framework for LLM-powered Tabular Feature Engineering (Extended Version)","created":"2026-06-08","cited_by_count":0,"area":null}],"next_cursor":null}