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