{"list":"other","total":65,"rows":[{"id":"2005.14165","title":"Language Models are Few-Shot Learners","created":"2020-05-28","cited_by_count":32419},{"id":"2303.08774","title":"GPT-4 Technical Report","created":"2023-03-15","cited_by_count":18396},{"id":"1907.11692","title":"RoBERTa: A Robustly Optimized BERT Pretraining Approach","created":"2019-07-26","cited_by_count":13372},{"id":"2201.11903","title":"Chain-of-Thought Prompting Elicits Reasoning in Large Language Models","created":"2022-01-28","cited_by_count":12459},{"id":"2005.11401","title":"Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks","created":"2020-05-22","cited_by_count":9297},{"id":"1802.03268","title":"Efficient Neural Architecture Search via Parameter Sharing","created":"2018-02-09","cited_by_count":837},{"id":"1807.02811","title":"A Tutorial on Bayesian Optimization","created":"2018-07-08","cited_by_count":744},{"id":"2106.11959","title":"Revisiting Deep Learning Models for Tabular Data","created":"2021-06-22","cited_by_count":740},{"id":"2207.01848","title":"TabPFN: A Transformer That Solves Small Tabular Classification Problems in a Second","created":"2022-07-05","cited_by_count":674},{"id":"1908.07442","title":"TabNet: Attentive Interpretable Tabular Learning","created":"2019-08-20","cited_by_count":648},{"id":"1706.02515","title":"Self-Normalizing Neural Networks","created":"2017-06-08","cited_by_count":598},{"id":"2110.01889","title":"Deep Neural Networks and Tabular Data: A Survey","created":"2021-10-05","cited_by_count":491},{"id":"2410.07095","title":"MLE-bench: Evaluating Machine Learning Agents on Machine Learning Engineering","created":"2024-10-09","cited_by_count":469},{"id":"2012.06678","title":"TabTransformer: Tabular Data Modeling Using Contextual Embeddings","created":"2020-12-11","cited_by_count":409},{"id":"1708.05123","title":"Deep & Cross Network for Ad Click Predictions","created":"2017-08-17","cited_by_count":393},{"id":"2002.06715","title":"BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning","created":"2020-02-17","cited_by_count":371},{"id":"2310.03302","title":"MLAgentBench: Evaluating Language Agents on Machine Learning Experimentation","created":"2023-10-05","cited_by_count":366},{"id":"2008.13535","title":"DCN V2: Improved Deep & Cross Network and Practical Lessons for Web-scale Learning to Rank Systems","created":"2020-08-19","cited_by_count":327},{"id":"1810.11921","title":"AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks","created":"2018-10-29","cited_by_count":320},{"id":"2502.05564","title":"TabICL: A Tabular Foundation Model for In-Context Learning on Large Data","created":"2025-02-08","cited_by_count":289},{"id":"2210.10723","title":"TabLLM: Few-shot Classification of Tabular Data with Large Language Models","created":"2022-10-19","cited_by_count":277},{"id":"2402.14658","title":"OpenCodeInterpreter: Integrating Code Generation with Execution and Refinement","created":"2024-02-22","cited_by_count":247},{"id":"2502.13138","title":"AIDE: AI-Driven Exploration in the Space of Code","created":"2025-02-18","cited_by_count":226},{"id":"2305.02997","title":"When Do Neural Nets Outperform Boosted Trees on Tabular Data?","created":"2023-05-04","cited_by_count":223},{"id":"1909.06312","title":"Neural Oblivious Decision Ensembles for Deep Learning on Tabular Data","created":"2019-09-13","cited_by_count":203},{"id":"2203.05556","title":"On Embeddings for Numerical Features in Tabular Deep Learning","created":"2022-03-10","cited_by_count":186},{"id":"2206.06565","title":"LIFT: Language-Interfaced Fine-Tuning for Non-Language Machine Learning Tasks","created":"2022-06-14","cited_by_count":148},{"id":"2401.05507","title":"InfiAgent-DABench: Evaluating Agents on Data Analysis Tasks","created":"2024-01-10","cited_by_count":140},{"id":"2205.09328","title":"TransTab: Learning Transferable Tabular Transformers Across Tables","created":"2022-05-19","cited_by_count":132},{"id":"2305.03403","title":"Large Language Models for Automated Data Science: Introducing CAAFE for Context-Aware Automated Feature Engineering","created":"2023-05-05","cited_by_count":127},{"id":"2410.18164","title":"TabDPT: Scaling Tabular Foundation Models on Real Data","created":"2024-10-23","cited_by_count":113},{"id":"2410.24210","title":"TabM: Advancing Tabular Deep Learning with Parameter-Efficient Ensembling","created":"2024-10-31","cited_by_count":113},{"id":"2407.04491","title":"Better by Default: Strong Pre-Tuned MLPs and Boosted Trees on Tabular Data","created":"2024-07-05","cited_by_count":92},{"id":"2305.02499","title":"AutoML-GPT: Automatic Machine Learning with GPT","created":"2023-05-04","cited_by_count":81},{"id":"2404.09491","title":"Large Language Models Can Automatically Engineer Features for Few-Shot Tabular Learning","created":"2024-04-15","cited_by_count":81},{"id":"2406.12031","title":"Large Scale Transfer Learning for Tabular Data via Language Modeling","created":"2024-06-17","cited_by_count":76},{"id":"2307.14338","title":"TabR: Tabular Deep Learning Meets Nearest Neighbors in 2023","created":"2023-07-26","cited_by_count":74},{"id":"2410.20424","title":"AutoKaggle: A Multi-Agent Framework for Autonomous Data Science Competitions","created":"2024-10-27","cited_by_count":70},{"id":"2304.14979","title":"MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks","created":"2023-04-28","cited_by_count":66},{"id":"2305.11097","title":"Statistical Foundations of Prior-Data Fitted Networks","created":"2023-05-18","cited_by_count":65},{"id":"2303.14725","title":"Natural Language Reasoning, A Survey","created":"2023-03-26","cited_by_count":61},{"id":"2406.05207","title":"Retrieval & Fine-Tuning for In-Context Tabular Models","created":"2024-06-07","cited_by_count":59},{"id":"2403.01841","title":"Making Pre-trained Language Models Great on Tabular Prediction","created":"2024-03-04","cited_by_count":57},{"id":"2407.04057","title":"TALENT: A Tabular Analytics and Learning Toolbox","created":"2024-07-04","cited_by_count":52},{"id":"2112.02962","title":"DANets: Deep Abstract Networks for Tabular Data Classification and Regression","created":"2021-12-06","cited_by_count":50},{"id":"1702.08835","title":"Deep Forest","created":"2017-02-28","cited_by_count":46},{"id":"2002.07971","title":"Gradient Boosting Neural Networks: GrowNet","created":"2020-02-19","cited_by_count":46},{"id":"2401.02013","title":"SwitchTab: Switched Autoencoders Are Effective Tabular Learners","created":"2024-01-04","cited_by_count":38},{"id":"2305.18446","title":"Trompt: Towards a Better Deep Neural Network for Tabular Data","created":"2023-05-29","cited_by_count":36},{"id":"2502.02527","title":"TabPFN Unleashed: A Scalable and Effective Solution to Tabular Classification Problems","created":"2025-02-04","cited_by_count":36},{"id":"2504.16109","title":"Representation Learning for Tabular Data: A Comprehensive Survey","created":"2025-04-17","cited_by_count":36},{"id":"2301.02819","title":"ExcelFormer: A neural network surpassing GBDTs on tabular data","created":"2023-01-07","cited_by_count":34},{"id":"2303.05506","title":"TANGOS: Regularizing Tabular Neural Networks through Gradient Orthogonalization and Specialization","created":"2023-03-09","cited_by_count":32},{"id":"2407.03257","title":"Revisiting Nearest Neighbor for Tabular Data: A Deep Tabular Baseline Two Decades Later","created":"2024-07-03","cited_by_count":30},{"id":"2407.05364","title":"PTaRL: Prototype-based Tabular Representation Learning via Space Calibration","created":"2024-07-07","cited_by_count":28},{"id":"2306.14101","title":"Language models are weak learners","created":"2023-06-25","cited_by_count":22},{"id":"2503.06664","title":"Exploring LLM Agents for Cleaning Tabular Machine Learning Datasets","created":"2025-03-09","cited_by_count":20},{"id":"2403.06644","title":"Elephants Never Forget: Testing Language Models for Memorization of Tabular Data","created":"2024-03-11","cited_by_count":19},{"id":"2410.17787","title":"Large Language Models Engineer Too Many Simple Features For Tabular Data","created":"2024-10-23","cited_by_count":10},{"id":"2504.10950","title":"Unveiling Challenges for LLMs in Enterprise Data Engineering","created":"2025-04-15","cited_by_count":9},{"id":"2310.15149","title":"Unlocking the Transferability of Tokens in Deep Models for Tabular Data","created":"2023-10-23","cited_by_count":8},{"id":"2311.00055","title":"Rethinking Pre-Training in Tabular Data: A Neighborhood Embedding Perspective","created":"2023-10-31","cited_by_count":7},{"id":"2502.03147","title":"Scalable In-Context Learning on Tabular Data via Retrieval-Augmented Large Language Models","created":"2025-02-05","cited_by_count":7},{"id":"2501.15627","title":"HardML: A Benchmark For Evaluating Data Science And Machine Learning knowledge and reasoning in AI","created":"2025-01-26","cited_by_count":5},{"id":"2502.20260","title":"Understanding the Limits of Deep Tabular Methods with Temporal Shift","created":"2025-02-27","cited_by_count":5}],"next_cursor":null}