NeurIPS 2024 Past Tabular & structured data
NeurIPS 2024 Third Table Representation Learning Workshop
TRL @ NeurIPS 2024
- Submission deadline
- Sep 23, 2024, 18:00 UTC imported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).
Accepted papers (59)
Fetched from OpenReview (v2) on 2026-06-10.
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AdapTable: Test-Time Adaptation for Tabular Data via Shift-Aware Uncertainty Calibrator and Label Distribution Handler
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Adapting TabPFN for Zero-Inflated Metagenomic Data
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AGATa: Attention-Guided Augmentation for Tabular Data in Contrastive Learning
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Augmenting Small-size Tabular Data with Class-Specific Energy-Based Models
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Automating Enterprise Data Engineering with LLMs
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Benchmarking table comprehension in the wild
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Data-Centric Text-to-SQL with Large Language Models
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Distributionally robust self-supervised learning for tabular data
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Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data
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DynoClass: A Dynamic Table-Class Detection System Without the Need for Predefined Ontologies
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Enhancing Biomedical Schema Matching with LLM-based Training Data Generation
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Enhancing Table Representations with LLM-powered Synthetic Data Generation
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Expertise-Centric Prompting Framework for Financial Tabular Data Generation using Pre-trained Large Language Models
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Exploration of autoregressive models for in-context learning on tabular data
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From One to Zero: RAG-IM Adapts Language Models for Interpretable Zero-Shot Predictions on Clinical Tabular Data
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GAMformer: Exploring In-Context Learning for Generalized Additive Models
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HySem: A context length optimized LLM pipeline for unstructured tabular extraction
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ICE-T: Interactions-aware Cross-column Contrastive Embedding for Heterogeneous Tabular Datasets
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Improving LLM Group Fairness on Tabular Data via In-Context Learning
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Large Language Models Engineer Too Many Simple Features for Tabular Data
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Learnable Numerical Input Normalization for Tabular Representation Learning based on B-splines
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Learning Metadata-Agnostic Representations for Text-to-SQL In-Context Example Selection
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Lightweight Correlation-Aware Table Compression
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LLM Embeddings Improve Test-time Adaptation to Tabular $Y|X$-Shifts
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Matchmaker: Self-Improving Compositional LLM Programs for Table Schema Matching
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MotherNet: Fast Training and Inference via Hyper-Network Transformers
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MSc-SQL: Multi-Sample Critiquing Small Language Models For Text-To-SQL Translation
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Multi-Stage QLoRA with Augmented Structured Dialogue Corpora: Efficient and Improved Conversational Healthcare AI
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On Short Textual Value Column Representation Using Symbol Level Language Models
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PORTAL: Scalable Tabular Foundation Models via Content-Specific Tokenization
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PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning
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RACOON: An LLM-based Framework for Retrieval-Augmented Column Type Annotation with a Knowledge Graph
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Recurrent Interpolants for Probabilistic Time Series Prediction
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Relational Data Generation with Graph Neural Networks and Latent Diffusion Models
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Relational Deep Learning: Graph Representation Learning on Relational Databases
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SALT: Sales Autocompletion Linked Business Tables Dataset
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Scalable Representation Learning for Multimodal Tabular Transactions
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Scaling Generative Tabular Learning for Large Language Models
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Sparsely Connected Layers for Financial Tabular Data
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SynQL: Synthetic Data Generation for In-Domain, Low-Resource Text-to-SQL Parsing
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Synthetic SQL Column Descriptions and Their Impact on Text-to-SQL Performance
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Tabby: Tabular Adaptation for Language Models
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TabDeco: A Comprehensive Contrastive Framework for Decoupled Representations in Tabular Data
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TabDiff: a Unified Diffusion Model for Multi-Modal Tabular Data Generation
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TabFlex: Scaling Tabular Learning to Millions with Linear Attention
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TABGEN-RAG: Iterative Retrieval for Tabular Data Generation with Large Language Models
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TabGraphs: A Benchmark and Strong Baselines for Learning on Graphs with Tabular Node Features
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TabSketchFM: Sketch-based Tabular Representation Learning for Data Discovery over Data Lakes
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Tabular Data Generation using Binary Diffusion
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TARGET: Benchmarking Table Retrieval for Generative Tasks
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TART: An Open-Source Tool-Augmented Framework for Explainable Table-based Reasoning
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The Death of Schema Linking? Text-to-SQL in the Age of Well-Reasoned Language Models
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The Tabular Foundation Model TabPFN Outperforms Specialized Time Series Forecasting Models Based on Simple Features
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Towards Agentic Schema Refinement
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Towards Localization via Data Embedding for TabPFN
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Towards Optimizing SQL Generation via LLM Routing
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UniTable: Towards a Unified Framework for Table Recognition via Self-Supervised Pretraining
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Unlearning Tabular Data Without a "Forget Set''
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Unmasking Trees for Tabular Data