{"total":25,"rows":[{"id":"2308.06374","title":"Large Language Models and Knowledge Graphs: Opportunities and Challenges","created":"2023-08-11","cited_by_count":71,"area":null},{"id":"2305.09696","title":"Generative Table Pre-training Empowers Models for Tabular Prediction","created":"2023-05-16","cited_by_count":55,"area":null},{"id":"2201.09745","title":"Table Pre-training: A Survey on Model Architectures, Pre-training Objectives, and Downstream Tasks","created":"2022-01-24","cited_by_count":42,"area":null},{"id":"2104.01785","title":"Annotating Columns with Pre-trained Language Models","created":"2021-04-05","cited_by_count":37,"area":null},{"id":"2310.07875","title":"TabLib: A Dataset of 627M Tables with Context","created":"2023-10-11","cited_by_count":23,"area":null},{"id":"2109.07323","title":"FORTAP: Using Formulas for Numerical-Reasoning-Aware Table Pretraining","created":"2021-09-15","cited_by_count":19,"area":null},{"id":"2307.02796","title":"VerifAI: Verified Generative AI","created":"2023-07-06","cited_by_count":16,"area":null},{"id":"2212.07588","title":"DeepJoin: Joinable Table Discovery with Pre-trained Language Models","created":"2022-12-15","cited_by_count":15,"area":null},{"id":"2310.07736","title":"Observatory: Characterizing Embeddings of Relational Tables","created":"2023-10-05","cited_by_count":12,"area":null},{"id":"2404.11581","title":"E2ETune: End-to-End Knob Tuning via Fine-tuned Generative Language Model","created":"2024-04-17","cited_by_count":9,"area":null},{"id":"2410.21717","title":"Generating Realistic Tabular Data with Large Language Models","created":"2024-10-29","cited_by_count":9,"area":null},{"id":"2305.15321","title":"Towards Foundation Models for Relational Databases [Vision Paper]","created":"2023-05-24","cited_by_count":7,"area":null},{"id":"2402.02643","title":"LLM-Enhanced Data Management","created":"2024-02-04","cited_by_count":7,"area":null},{"id":"2412.18111","title":"AIGT: AI Generative Table Based on Prompt","created":"2024-12-24","cited_by_count":7,"area":null},{"id":"2204.08941","title":"CodexDB: Generating Code for Processing SQL Queries using GPT-3 Codex","created":"2022-04-19","cited_by_count":5,"area":null},{"id":"2510.09783","title":"Large Language Models for Imbalanced Classification: Diversity makes the difference","created":"2025-10-10","cited_by_count":4,"area":null},{"id":"2305.00366","title":"S2abEL: A Dataset for Entity Linking from Scientific Tables","created":"2023-04-30","cited_by_count":3,"area":null},{"id":"2411.17110","title":"TabulaX: Leveraging Large Language Models for Multi-Class Table Transformations","created":"2024-11-26","cited_by_count":3,"area":null},{"id":"2107.04553","title":"Can Deep Neural Networks Predict Data Correlations from Column Names?","created":"2021-07-09","cited_by_count":2,"area":null},{"id":"2109.05173","title":"Making Table Understanding Work in Practice","created":"2021-09-11","cited_by_count":1,"area":null},{"id":"2406.17574","title":"Beyond Text-to-SQL for IoT Defense: A Comprehensive Framework for Querying and Classifying IoT Threats","created":"2024-06-25","cited_by_count":1,"area":null},{"id":"2408.02128","title":"Table Transformers for Imputing Textual Attributes","created":"2024-08-04","cited_by_count":1,"area":null},{"id":"2306.11696","title":"RoTaR: Efficient Row-Based Table Representation Learning via Teacher-Student Training","created":"2023-06-20","cited_by_count":0,"area":null},{"id":"2405.05618","title":"An Automatic Prompt Generation System for Tabular Data Tasks","created":"2024-05-09","cited_by_count":0,"area":null},{"id":"2605.16085","title":"Towards Foundation Models for Relational Databases with Language Models and Graph Neural Networks","created":"2026-05-15","cited_by_count":0,"area":null}],"next_cursor":null}