Skip to yearly menu bar Skip to main content


Workshop

1st Workshop on Foundation Models for Structured Data (FMSD)

Nick Erickson ⋅ Xiyuan Zhang ⋅ Abdul Fatir Ansari ⋅ Boran Han ⋅ Mononito Goswami ⋅ Samuel Gabriel Müller ⋅ Lennart Purucker ⋅ Yuyang Wang ⋅ Christos Faloutsos ⋅ Michael Mahoney
Project Page [ OpenReview] 

Abstract

Video

Chat is not available.

Schedule

Timezone: Asia/Seoul
1:00 AM
Opening Remarks
2:15 AM
Coffee Break
7:00 AM
Coffee Break
7:45 AM
Poster Session
8:45 AM
Closing Remarks
CLEAR: Contextual Logic-based Explanations for Anomaly Reasoning
Vikash Sharma ⋅ Vipul Joshi ⋅ Anurag Tripathi ⋅ Mayank Jauhari ⋅ Amir Raza
Towards Benchmarking Foundation Models for Tabular Data With Text
Martin Mráz ⋅ Breenda Das ⋅ Anshul Gupta ⋅ Lennart Purucker ⋅ Frank Hutter
Calibration Properties of Time Series Foundation Models
Coen Adler ⋅ Yuxin Chang ⋅ Samar Abdi ⋅ Padhraic Smyth
Query, Don’t Train: Privacy-Preserving Tabular Prediction from EHR Data via SQL Queries
Josefa Stoisser ⋅ Marc Martell ⋅ Kaspar Märtens ⋅ Lawrence Phillips ⋅ Stephen Town ⋅ Rory Donovan-Maiye ⋅ Julien Fauqueur
GATS: A Time-Series Dataset for Addressing General Aviation Flight Safety
Charles Duong ⋅ Aidan LaBella ⋅ Pak Iong Long ⋅ Nathan DePiero ⋅ Aditya Iyer ⋅ Elise Carman ⋅ Randall Balestriero ⋅ Travis Desell
Foundation models for time series forecasting and policy evaluation in infectious disease epidemics: a modelling study
Suprabhath Kalahasti ⋅ Benjamin Faucher ⋅ boxuan wang ⋅ Claudio Ascione ⋅ Federico Baldo ⋅ Eugenio Valdano
State-Space Models for Tabular Prior-Data Fitted Networks
Felix Koch ⋅ Marcel Wever ⋅ Fabian Raisch ⋅ Benjamin Tischler
Two-Stage Contrastive Language Electrocardiogram Pre-training for Fine-Grained Waveform Features
Haitao Li ⋅ che liu ⋅ Zhengyao Ding ⋅ Ziyi Liu ⋅ Zhengxing Huang
G1: Teaching LLMs to Reason on Graphs with Reinforcement Learning
Xiaojun Guo ⋅ Ang Li ⋅ Yifei Wang ⋅ Stefanie Jegelka ⋅ Yisen Wang
Are Time Series Foundation Models Ready for Zero-Shot Forecasting?
Yunkai Zhang ⋅ Qi Zeng ⋅ Yawen Zhang ⋅ Zhijie Xu ⋅ Ming Zheng ⋅ Chongyang Gao ⋅ Muyan Jiang ⋅ Zeyu Zheng
Instruction Tuning of Large Language Models for Tabular Data Generation—in One Day
Milad Abdollahzadeh ⋅ Abdul Raheem ⋅ Zilong Zhao ⋅ Uzair Javaid ⋅ Kevin Yee ⋅ Venkata Abhishek Nalam ⋅ Tram Truong-Huu ⋅ Biplab Sikdar
Multivariate Calibration is Performative: A Perspective on Pitfalls and Progress
Sofian Zalouk ⋅ Charles Marx ⋅ Syrine Belakaria ⋅ Chris De Sa ⋅ Stefano Ermon
Eliciting Numerical Predictive Distributions of LLMs Without Auto-Regression
Julianna Piskorz ⋅ Katarzyna Kobalczyk ⋅ Mihaela van der Schaar
Toward Scientific Foundation Models for Aquatic Ecosystems
Abhilash Neog ⋅ Medha Sawhney ⋅ Kazi Sajeed Mehrab ⋅ Sepideh Fatemi ⋅ Mary Lofton ⋅ Amartya Dutta ⋅ Aanish Pradhan ⋅ Bennett McAfee ⋅ Emma Marchisin ⋅ Robert Ladwig ⋅ Arka Daw ⋅ Cayelan C. Carey ⋅ Paul Hanson ⋅ Anuj Karpatne
Towards Synthetic Data for Fine-tuning Tabular Foundation Models
Magnus Bühler ⋅ Lennart Purucker ⋅ Frank Hutter
Self-Imputation and Cross-Variable Learning Improve Water Quality Prediction with Sparse Data
Xiaofeng Liu ⋅ Xiaobo Xia ⋅ Xuechen Zhang ⋅ Mohna Chakraborty ⋅ Xiyuan Chang ⋅ Kuai Fang ⋅ William Currie ⋅ Samet Oymak
In-context Pre-trained Time-Series Foundation Models adapt to Unseen Tasks
Shangqing Xu ⋅ Harshavardhan Kamarthi ⋅ Haoxin Liu ⋅ B. Aditya Prakash
Theoretical Insights into In-context Learning with Unlabeled Data
Yingcong Li ⋅ Xiangyu Chang ⋅ Muti Kara ⋅ Xiaofeng Liu ⋅ Amit Roy-Chowdhury ⋅ Samet Oymak
Toto: An Open Time Series Foundation Model Optimized for Observability
Ben Cohen ⋅ Emaad Khwaja ⋅ Youssef Doubli ⋅ Salahidine Lemaachi ⋅ Chris Lettieri ⋅ Charles Masson ⋅ Hugo Miccinilli ⋅ Elise Ramé ⋅ Qiqi Ren ⋅ Afshin Rostamizadeh ⋅ Jean du Terrail ⋅ Anna-Monica Toon ⋅ Kan Wang ⋅ Stephan Xie ⋅ Zongzhe Xu ⋅ Viktoriya Zhukova ⋅ David Asker ⋅ Ameet Talwalkar ⋅ Othmane Abou-Amal
TiRex: Zero-Shot Forecasting Across Long and Short Horizons
Andreas Auer ⋅ Patrick Podest ⋅ Daniel Klotz ⋅ Sebastian Böck ⋅ Günter Klambauer ⋅ Sepp Hochreiter
Foundation Models for Clinical Records at Health System Scale
Haresh Rengaraj Rajamohan ⋅ Xiang Gao ⋅ Weicheng Zhu ⋅ Shih-Lun Huang ⋅ Long Chen ⋅ Kyunghyun Cho ⋅ Cem Deniz ⋅ Narges Razavian
Towards Generalizable Multimodal ECG Representation Learning with LLM-extracted Clinical Entities
Mingsheng Cai ⋅ Jiuming Jiang ⋅ Wenhao Huang ⋅ che liu ⋅ Rossella Arcucci
W-LSTMix: A Hybrid Modular Forecasting Framework for Trend and Pattern Learning in Short-Term Load Forecasting
SHIVAM DWIVEDI ⋅ Anuj Kumar ⋅ Harish Kumar Saravanan ⋅ Pandarasamy Arjunan
GeoGrid-Bench: Can Foundation Models Understand Multimodal Gridded Geo-Spatial Data?
Bowen Jiang ⋅ Yangxinyu Xie ⋅ Xiaomeng Wang ⋅ Jiashu HE ⋅ John Hutchison ⋅ Jordan Branham ⋅ Camillo Taylor ⋅ Tanwi Mallick
Filter, Augment, Forecast: Online Data Selection for Robust Time Series Forecasting
Ege Onur Taga ⋅ Halil Alperen Gozeten ⋅ Kutay Tire ⋅ Rahul Dalvi ⋅ Reinhard Heckel ⋅ Samet Oymak
Multivariate de Bruijn Graphs: A Symbolic Graph Framework for Time Series Forecasting
Mert Cakiroglu ⋅ Idil Altun ⋅ HASAN KURBAN ⋅ Elham buxton ⋅ Mehmet Dalkilic
From Structured Data to Clinical Notes: Robust Clinical Decision Support with Fine-Tuned LLMs
Frederike Lübeck ⋅ Jonas Wildberger ⋅ Frederik Träuble ⋅ Maximilian Mordig ⋅ Sergios Gatidis ⋅ Andreas Krause ⋅ Bernhard Schölkopf
Random Initialization Can’t Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting
Roland Riachi ⋅ Kashif Rasul ⋅ Arjun Ashok ⋅ Prateek Humane ⋅ Alexis Roger ⋅ Andrew Williams ⋅ Yuriy Nevmyvaka ⋅ Irina Rish
LUNA: Efficient and Topology-Agnostic Foundation Model for EEG Signal Analysis
Berkay Döner ⋅ Thorir Ingolfsson ⋅ Luca Benini ⋅ Yawei Li
RECoRD: A Multi-Agent LLM Framework for Reverse Engineering Codebase to Relational Diagram
Yuan Xue ⋅ Xiaoyu Lu ⋅ Yunfei Bai ⋅ Hoiyi Ng ⋅ Yunan Liu
TabRep: Training Tabular Diffusion Models with a Simple and Effective Continuous Representation
Jacob Si ⋅ Zijing Ou ⋅ Mike Qu ⋅ Zhengrui Xiang ⋅ Yingzhen Li
CauKer: Classification Time Series Foundation Models Can Be Pretrained on Synthetic Data only
Shifeng Xie ⋅ Vasilii Feofanov ⋅ Marius Alonso ⋅ Ambroise Odonnat ⋅ Jianfeng Zhang ⋅ Ievgen Redko
Towards Interpretable Time Series Foundation Models
Matthieu Boileau ⋅ Philippe Helluy ⋅ Jérémy Pawlus ⋅ Svitlana Vyetrenko
DriMM: Drilling Multimodal Model for Time-Series and Text in the Era of Large Models
Sebastiaan Buiting ⋅ Soumyadipta Sengupta ⋅ Abdallah Benzine ⋅ Amine EL KHAIR ⋅ Imane Khaouja ⋅ Youssef Tamaazousti
ConTextTab: A Semantics-Aware Tabular In-Context Learner
Marco Spinaci ⋅ Marek Polewczyk ⋅ Maximilian Schambach ⋅ Sam Thelin
Do Large Foundation Models Improve Time Series Segmentation? An Industrial Case Study in Oil and Gas Drilling
Imane Khaouja ⋅ Amine EL KHAIR ⋅ Abdallah Benzine ⋅ Sebastiaan Buiting ⋅ Soumyadipta Sengupta ⋅ Youssef Tamaazousti
Do-PFN: In-Context Learning for Causal Effect Estimation
Jake Robertson ⋅ Arik Reuter ⋅ Siyuan Guo ⋅ Noah Hollmann ⋅ Frank Hutter ⋅ Bernhard Schölkopf
LEAD - Framework for efficient time-series anomaly detection on large scale data using LLMs
Akash Chandrayan ⋅ Amir ZIDI ⋅ Matthew Reimherr ⋅ Anis Mjirda ⋅ Abhinav Pradhan
Exploring Relational Database Foundation Models from a Graph Perspective
Yanbo Wang ⋅ Xiyuan Wang ⋅ Quan Gan ⋅ Minjie Wang ⋅ Qibin Yang ⋅ David Wipf ⋅ Muhan Zhang
One-Run Privacy Auditing for Structured Generative and Foundation Models
Rishav Chourasia ⋅ Zilong Zhao ⋅ Uzair Javaid
Lights Out, Tabs On: Advancing Row-Column Encoding for Tabular LLMs
Yi-Kai Zhang ⋅ Huai-Hong Yin ⋅ Xin Li ⋅ Haoyu Cao ⋅ Yinsong Liu ⋅ Deqiang Jiang ⋅ Xing Sun ⋅ De-Chuan Zhan ⋅ Han-Jia Ye
Early Stopping Tabular In-Context Learning
Jaris Küken ⋅ Lennart Purucker ⋅ Frank Hutter
Mantis: Lightweight Calibrated Foundation Model for User-Friendly Time Series Classification
Vasilii Feofanov ⋅ Marius Alonso ⋅ Songkang Wen ⋅ Romain Ilbert ⋅ Hongbo Guo ⋅ Malik TIOMOKO ⋅ Lujia Pan ⋅ Jianfeng Zhang ⋅ Ievgen Redko
FoMo-0D: A Foundation Model for Zero-shot Outlier Detection
Yuchen Shen ⋅ Haomin Wen ⋅ Leman Akoglu
Real-TabPFN: Improving Tabular Foundation Models via Continued Pre-training With Real-World Data
Anurag Garg ⋅ Muhammad Ali ⋅ Noah Hollmann ⋅ Lennart Purucker ⋅ Samuel Gabriel Müller ⋅ Frank Hutter
Soft Contrastive Learning for Irregular Multivariate Time Series
Junghoon Lim ⋅ Seunghan Lee ⋅ Taeyoung Park
Towards Fair In-Context Learning with Tabular Foundation Models
Patrik Kenfack ⋅ Samira Ebrahimi Kahou ⋅ Ulrich Aïvodji
Causal Foundation Models: Disentangling Physics from Instrument Properties
Jeroen Audenaert ⋅ Daniel Muthukrishna ⋅ Paul Gregory ⋅ David W. Hogg ⋅ V Villar
From Video Classification to Action Detection: Foundation vs. Task-Specific Models
Goncalo Mesquita ⋅ Ana Rita Cóias ⋅ Alexandre Bernardino ⋅ Artur Dubrawski
MORPHEUS : A Foundation Model for Multivariate Time Series Forecasting
Prathamesh Patil ⋅ Amit Varshney ⋅ Manoj Cherukumalli ⋅ Harsh Deshpande ⋅ Leonard Eun ⋅ Dushyant Sahoo ⋅ Naren Chittar
TabReason: A Reinforcement Learning-Enhanced Reasoning LLM for Explainable Tabular Data Prediction
Tommy M. Xu ⋅ Andy Zhang ⋅ Xiangyu Sun ⋅ Lauren Zung ⋅ Hossein Hajimirsadeghi ⋅ Greg Mori
Improving Treatment Effect Estimation with LLM-Based Data Augmentation
Nicolas Huynh ⋅ Julianna Piskorz ⋅ Jeroen Berrevoets ⋅ Max Ruiz Luyten ⋅ Mihaela van der Schaar
TimePoint: Accelerated Time Series Alignment via Self-Supervised Keypoint and Descriptor Learning
Ron Shapira Weber ⋅ shahar benishay ⋅ Andrey Lavrinenko ⋅ Shahaf E. Finder ⋅ Oren Freifeld
LLM Agents Struggle at Time Series Machine Learning Engineering
Yifu Cai ⋅ Xinyu Li ⋅ Mononito Goswami ⋅ Michal Wilinski ⋅ Gus Welter ⋅ Artur Dubrawski