Fri 6:30 a.m. - 6:45 a.m.
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Opening notes
(
Talk
)
>
SlidesLive Video
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🔗
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Fri 6:45 a.m. - 7:15 a.m.
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Invited talk: Co-Designing LLMs and LLM-Powered Data Management Tools
(
Talk
)
>
SlidesLive Video
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Simran Arora
🔗
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Fri 7:15 a.m. - 7:22 a.m.
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High-Performance Transformers for Table Structure Recognition Need Early Convolutions
(
Spotlight
)
>
link
SlidesLive Video
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ShengYun Peng · Seongmin Lee · Xiaojing Wang · Rajarajeswari Balasubramaniyan · Duen Horng Chau
🔗
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Fri 7:23 a.m. - 7:30 a.m.
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Pool-Search-Demonstrate: Improving Data-wrangling LLMs via better in-context examples
(
Spotlight
)
>
link
SlidesLive Video
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Joon Suk Huh · Changho Shin · Elina Choi
🔗
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Fri 7:31 a.m. - 7:38 a.m.
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TabPFGen – Tabular Data Generation with TabPFN
(
Spotlight
)
>
link
SlidesLive Video
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Jeremy (Junwei) Ma · Apoorv Dankar · George Stein · Guangwei Yu · Anthony Caterini
🔗
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Fri 7:38 a.m. - 7:45 a.m.
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Data Ambiguity Strikes Back: How Documentation Improves GPT's Text-to-SQL
(
Spotlight
)
>
link
SlidesLive Video
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Zachary Huang · Pavan Kalyan Damalapati · Eugene Wu
🔗
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Fri 7:46 a.m. - 7:53 a.m.
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MultiTabQA: Generating Tabular Answers for Multi-Table Question Answering
(
Spotlight
)
>
link
SlidesLive Video
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Vaishali Pal · Andrew Yates · Evangelos Kanoulas · Maarten Rijke
🔗
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Fri 8:00 a.m. - 8:20 a.m.
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Coffee break + poster setup
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🔗
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Fri 8:20 a.m. - 9:00 a.m.
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Poster Session 1
(
Poster session
)
>
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🔗
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Fri 9:00 a.m. - 9:30 a.m.
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Invited talk: Advances in In-Context Learning for Tabular Datasets
(
Talk
)
>
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Frank Hutter
🔗
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Fri 9:30 a.m. - 9:37 a.m.
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Self-supervised Representation Learning from Random Data Projectors
(
Spotlight
)
>
link
SlidesLive Video
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Yi Sui · Tongzi Wu · Jesse Cresswell · Ga Wu · George Stein · Xiao Shi Huang · Xiaochen Zhang · Maksims Volkovs
🔗
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Fri 9:38 a.m. - 9:45 a.m.
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GCondNet: A Novel Method for Improving Neural Networks on Small High-Dimensional Tabular Data
(
Spotlight
)
>
link
SlidesLive Video
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Andrei Margeloiu · Nikola Simidjievski · Pietro Lió · Mateja Jamnik
🔗
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Fri 9:46 a.m. - 9:53 a.m.
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HyperFast: Instant Classification for Tabular Data
(
Spotlight
)
>
link
SlidesLive Video
|
David Bonet · Daniel Mas Montserrat · Xavier Giró-i-Nieto · Alexander Ioannidis
🔗
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Fri 9:54 a.m. - 10:01 a.m.
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Training-Free Generalization on Heterogeneous Tabular Data via Meta-Representation
(
Spotlight
)
>
link
SlidesLive Video
|
Han-Jia Ye · Qile Zhou · De-Chuan Zhan
🔗
|
Fri 10:00 a.m. - 11:30 a.m.
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Lunch Break
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🔗
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Fri 11:30 a.m. - 12:00 p.m.
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Invited talk: Next-Generation Data Management with Large Language Models
(
Talk
)
>
SlidesLive Video
|
Immanuel Trummer
🔗
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Fri 12:00 p.m. - 12:07 p.m.
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Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs
(
Spotlight
)
>
link
SlidesLive Video
|
Ananya Singha · José Cambronero · Sumit Gulwani · Vu Le · Chris Parnin
🔗
|
Fri 12:08 p.m. - 12:15 p.m.
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How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings
(
Spotlight
)
>
link
SlidesLive Video
|
Shuaichen Chang · Eric Fosler-Lussier
🔗
|
Fri 12:16 p.m. - 12:23 p.m.
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IngesTables: Scalable and Efficient Training of LLM-Enabled Tabular Foundation Models
(
Spotlight
)
>
link
SlidesLive Video
|
Scott Yak · Yihe Dong · Javier Gonzalvo · Sercan Arik
🔗
|
Fri 12:30 p.m. - 1:00 p.m.
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Invited talk: Advancing Natural Language Interfaces to Data with Language Models as Agents
(
Talk
)
>
SlidesLive Video
|
Tao Yu
🔗
|
Fri 1:00 p.m. - 1:20 p.m.
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Coffee Break + poster setup
|
🔗
|
Fri 1:20 p.m. - 2:00 p.m.
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Poster Session 2
(
Poster Session
)
>
|
🔗
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Fri 2:00 p.m. - 2:30 p.m.
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Invited talk: Enabling Large Language Models to Reason with Tables
(
Talk
)
>
SlidesLive Video
|
Wenhu Chen
🔗
|
Fri 2:30 p.m. - 3:15 p.m.
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Panel - TBA
(
Panel
)
>
SlidesLive Video
|
🔗
|
Fri 3:15 p.m. - 3:30 p.m.
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Closing notes
(
Talk
)
>
SlidesLive Video
|
🔗
|
-
|
MultiTabQA: Generating Tabular Answers for Multi-Table Question Answering
(
Poster
)
>
link
|
Vaishali Pal · Andrew Yates · Evangelos Kanoulas · Maarten Rijke
🔗
|
-
|
Generating Data Augmentation Queries Using Large Language Models
(
Poster
)
>
link
|
Christopher Buss · Jasmin Mousavi · Mikhail Tokarev · Arash Termehchy · David Maier · Stefan Lee
🔗
|
-
|
ReConTab: Regularized Contrastive Representation Learning for Tabular Data
(
Poster
)
>
link
|
Suiyao Chen · Jing Wu · NAIRA HOVAKIMYAN · Handong Yao
🔗
|
-
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Unlocking the Transferability of Tokens in Deep Models for Tabular Data
(
Poster
)
>
link
|
Qile Zhou · Han-Jia Ye · Leye Wang · De-Chuan Zhan
🔗
|
-
|
Augmentation for Context in Financial Numerical Reasoning over Textual and Tabular Data with Large-Scale Language Model
(
Poster
)
>
link
|
Yechan Hwang · Jinsu Lim · Young-Jun Lee · Ho-Jin Choi
🔗
|
-
|
TabContrast: A Local-Global Level Method for Tabular Contrastive Learning
(
Poster
)
>
link
|
Hao Liu · Yixin Chen · Bradley A Fritz · Christopher King
🔗
|
-
|
Explaining Explainers: Necessity and Sufficiency in Tabular Data
(
Poster
)
>
link
|
Prithwijit Chowdhury · Mohit Prabhushankar · Ghassan AlRegib
🔗
|
-
|
Beyond Individual Input for Deep Anomaly Detection on Tabular Data
(
Poster
)
>
link
|
Hugo Thimonier · Fabrice Popineau · Arpad Rimmel · Bich-Liên DOAN
🔗
|
-
|
GradTree: Learning Axis-Aligned Decision Trees with Gradient Descent
(
Poster
)
>
link
|
Sascha Marton · Stefan Lüdtke · Christian Bartelt · Heiner Stuckenschmidt
🔗
|
-
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Elephants Never Forget: Testing Language Models for Memorization of Tabular Data
(
Poster
)
>
link
|
Sebastian Bordt · Harsha Nori · Rich Caruana
🔗
|
-
|
InterpreTabNet: Enhancing Interpretability of Tabular Data Using Deep Generative Models and Large Language Models
(
Poster
)
>
link
|
Jacob Yoke Hong Si · Rahul Krishnan · Michael Cooper · Wendy Yusi Cheng
🔗
|
-
|
On Incorporating new Variables during Evaluation
(
Poster
)
>
link
|
Harsimran Bhasin · Soumyadeep Ghosh
🔗
|
-
|
GCondNet: A Novel Method for Improving Neural Networks on Small High-Dimensional Tabular Data
(
Poster
)
>
link
|
Andrei Margeloiu · Nikola Simidjievski · Pietro Lió · Mateja Jamnik
🔗
|
-
|
High-Performance Transformers for Table Structure Recognition Need Early Convolutions
(
Poster
)
>
link
|
ShengYun Peng · Seongmin Lee · Xiaojing Wang · Rajarajeswari Balasubramaniyan · Duen Horng Chau
🔗
|
-
|
Unnormalized Density Estimation with Root Sobolev Norm Regularization
(
Poster
)
>
link
|
Mark Kozdoba · Binyamin Perets · Shie Mannor
🔗
|
-
|
Self-supervised Representation Learning from Random Data Projectors
(
Poster
)
>
link
|
Yi Sui · Tongzi Wu · Jesse Cresswell · Ga Wu · George Stein · Xiao Shi Huang · Xiaochen Zhang · Maksims Volkovs
🔗
|
-
|
Tree-Regularized Tabular Embeddings
(
Poster
)
>
link
|
Xuan Li · Yun Wang · Bo Li
🔗
|
-
|
Binning as a Pretext Task: Improving Self-Supervised Learning in Tabular Domains
(
Poster
)
>
link
|
Kyungeun Lee · Ye Seul Sim · Hyeseung Cho · Suhee Yoon · Sanghyu Yoon · Woohyung Lim
🔗
|
-
|
A Deep Learning Blueprint for Relational Databases
(
Poster
)
>
link
|
Lukáš Zahradník · Jan Neumann · Gustav Šír
🔗
|
-
|
Scaling TabPFN: Sketching and Feature Selection for Tabular Prior-Data Fitted Networks
(
Poster
)
>
link
|
Benjamin Feuer · Niv Cohen · Chinmay Hegde
🔗
|
-
|
Modeling string entries for tabular data prediction: do we need big large language models?
(
Poster
)
>
link
|
Leo Grinsztajn · Myung Jun Kim · Edouard Oyallon · Gael Varoquaux
🔗
|
-
|
HyperFast: Instant Classification for Tabular Data
(
Poster
)
>
link
|
David Bonet · Daniel Mas Montserrat · Xavier Giró-i-Nieto · Alexander Ioannidis
🔗
|
-
|
Hopular: Modern Hopfield Networks for Tabular Data
(
Poster
)
>
link
|
Bernhard Schäfl · Lukas Gruber · Angela Bitto · Sepp Hochreiter
🔗
|
-
|
Training-Free Generalization on Heterogeneous Tabular Data via Meta-Representation
(
Poster
)
>
link
|
Han-Jia Ye · Qile Zhou · De-Chuan Zhan
🔗
|
-
|
NeuroDB: Efficient, Privacy-Preserving and Robust Query Answering with Neural Networks
(
Poster
)
>
link
|
Sepanta Zeighami · Cyrus Shahabi
🔗
|
-
|
A DB-First approach to query factual information in LLMs
(
Poster
)
>
link
|
Mohammed SAEED · Nicola De Cao · Paolo Papotti
🔗
|
-
|
A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning
(
Poster
)
>
link
|
Valeriia Cherepanova · Roman Levin · Gowthami Somepalli · Jonas Geiping · C. Bayan Bruss · Andrew Wilson · Tom Goldstein · Micah Goldblum
🔗
|
-
|
Incorporating LLM Priors into Tabular Learners
(
Poster
)
>
link
|
Max Zhu · Siniša Stanivuk · Andrija Petrovic · Mladen Nikolic · Pietro Lió
🔗
|
-
|
CHORUS: Foundation Models for Unified Data Discovery and Exploration
(
Poster
)
>
link
|
Moe Kayali · Anton Lykov · Ilias Fountalis · Nikolaos Vasiloglou · Dan Olteanu · Dan Suciu
🔗
|
-
|
Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs
(
Poster
)
>
link
|
Ananya Singha · José Cambronero · Sumit Gulwani · Vu Le · Chris Parnin
🔗
|
-
|
Introducing the Observatory Library for End-to-End Table Embedding Inference
(
Poster
)
>
link
|
Tianji Cong · Zhenjie Sun · Paul Groth · H. V. Jagadish · Madelon Hulsebos
🔗
|
-
|
Scaling Experiments in Self-Supervised Cross-Table Representation Learning
(
Poster
)
>
link
|
Maximilian Schambach · Dominique Paul · Johannes Otterbach
🔗
|
-
|
Benchmarking Tabular Representation Models in Transfer Learning Settings
(
Poster
)
>
link
|
Qixuan Jin · Talip Ucar
🔗
|
-
|
Exploring the Retrieval Mechanism for Tabular Deep Learning
(
Poster
)
>
link
|
Felix den Breejen · Sangmin Bae · Stephen Cha · Tae-Young Kim · Seoung Hyun Koh · Se-Young Yun
🔗
|
-
|
In Defense of Zero Imputation for Tabular Deep Learning
(
Poster
)
>
link
|
John Van Ness · Madeleine Udell
🔗
|
-
|
Data Ambiguity Strikes Back: How Documentation Improves GPT's Text-to-SQL
(
Poster
)
>
link
|
Zachary Huang · Pavan Kalyan Damalapati · Eugene Wu
🔗
|
-
|
IngesTables: Scalable and Efficient Training of LLM-Enabled Tabular Foundation Models
(
Poster
)
>
link
|
Scott Yak · Yihe Dong · Javier Gonzalvo · Sercan Arik
🔗
|
-
|
Pool-Search-Demonstrate: Improving Data-wrangling LLMs via better in-context examples
(
Poster
)
>
link
|
Joon Suk Huh · Changho Shin · Elina Choi
🔗
|
-
|
How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settings
(
Poster
)
>
link
|
Shuaichen Chang · Eric Fosler-Lussier
🔗
|
-
|
TabPFGen – Tabular Data Generation with TabPFN
(
Poster
)
>
link
|
Jeremy (Junwei) Ma · Apoorv Dankar · George Stein · Guangwei Yu · Anthony Caterini
🔗
|
-
|
Multitask-Guided Self-Supervised Tabular Learning for Patient-Specific Survival Prediction
(
Poster
)
>
link
|
You Wu · Omid Bazgir · Yongju Lee · Tommaso Biancalani · James Lu · Ehsan Hajiramezanali
🔗
|
-
|
Testing the Limits of Unified Sequence to Sequence LLM Pretraining on Diverse Table Data Tasks
(
Poster
)
>
link
|
Soumajyoti Sarkar · Leonard Lausen
🔗
|