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Workshop

DMLR Workshop: Data-centric Machine Learning Research

Ce Zhang ⋅ Praveen Paritosh ⋅ Newsha Ardalani ⋅ Nezihe Merve Gürel ⋅ William Gaviria Rojas ⋅ Yang Liu ⋅ Rotem Dror ⋅ Manil Maskey ⋅ Lilith Bat-Leah ⋅ Tzu-Sheng Kuo ⋅ Luis Oala ⋅ Max Bartolo ⋅ Ludwig Schmidt ⋅ Alicia Parrish ⋅ Daniel Kondermann ⋅ Najoung Kim
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Abstract

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Schedule

Timezone: Asia/Seoul
4:00 AM
Introduction and Opening
Praveen Paritosh
6:00 AM
Invited Talk 2: Olga Russakovsky (Princeton University)
Olga Russakovsky ⋅ Vikram V Ramaswamy
9:20 AM
Panel Discussion
Megan Ansdell ⋅ Nathan Lambert ⋅ Ludwig Schmidt ⋅ Praveen Paritosh ⋅ Sang Michael Xie
10:30 AM
Poster Session 1
DMOps: Data Management Operations and Recipes
Eujeong Choi ⋅ Chanjun Park
To Aggregate or Not? Learning with Separate Noisy Labels
Jiaheng Wei ⋅ Zhaowei Zhu ⋅ Tianyi Luo ⋅ Ehsan Amid ⋅ Abhishek Kumar ⋅ Yang Liu
On the Trade-off of Intra-/Inter-class Diversity for Supervised Pre-training
Jieyu Zhang ⋅ Bohan Wang ⋅ zhengyu hu ⋅ Pang We Koh ⋅ Alex Ratner
Algorithm Selection for Deep Active Learning with Imbalanced Datasets
Jifan Zhang ⋅ Shuai Shao ⋅ Saurabh Verma ⋅ Robert Nowak
How to Improve Imitation Learning Performance with Sub-optimal Supplementary Data?
Ziniu Li ⋅ Tian Xu ⋅ Zeyu Qin ⋅ Yang Yu ⋅ Zhiquan Luo
DoReMi: Optimizing Data Mixtures Speeds Up Language Model Pretraining
Sang Michael Xie ⋅ Hieu Pham ⋅ Xuanyi Dong ⋅ Nan Du ⋅ Hanxiao Liu ⋅ Yifeng Lu ⋅ Percy Liang ⋅ Quoc Le ⋅ Tengyu Ma ⋅ Adams Wei Yu
How to Cope with Gradual Data Drift?
Rasool Fakoor ⋅ Jonas Mueller ⋅ Zachary Lipton ⋅ Pratik Chaudhari ⋅ Alex Smola
Synthetic Alone: Exploring the Dark Side of Synthetic Data for Grammatical Error Correction
Chanjun Park ⋅ Seonmin Koo ⋅ Seolhwa Lee ⋅ Jaehyung Seo ⋅ Sugyeong Eo ⋅ Hyeonseok Moon ⋅ HEUISEOK LIM
Programmable Synthetic Tabular Data Generation
Mark Vero ⋅ Mislav Balunovic ⋅ Martin Vechev
Unitail: A Benchmark for Detecting, Reading, and Matching in Retail Scene
Fangyi Chen ⋅ Han Zhang ⋅ Hao Chen ⋅ Kai Hu ⋅ Jiachen Dou ⋅ zaiwang li ⋅ Chenchen Zhu ⋅ Marios Savvides
Promises and Pitfalls of Threshold-based Auto-labeling
Harit Vishwakarma ⋅ Heguang Lin ⋅ Frederic Sala ⋅ Ramya Korlakai Vinayak
Detecting Dataset Drift and Non-IID Sampling via k-Nearest Neighbors
Jesse Cummings ⋅ Jonas Mueller ⋅ Elías Snorrason
Prioritized Trajectory Replay: A Replay Memory for Data-driven Reinforcement Learning
Jinyi Liu ⋅ Yi Ma ⋅ Jianye Hao ⋅ Yujing Hu ⋅ Yan Zheng ⋅ Tangjie Lv ⋅ Changjie Fan
CD-GraB: Coordinating Distributed Example Orders for Provably Accelerated Training
A. Feder Cooper ⋅ Wentao Guo ⋅ Duc Khiem Pham ⋅ Tiancheng Yuan ⋅ Charlie Ruan ⋅ Yucheng Lu ⋅ Chris De Sa
Data-Centric Defense: Shaping Loss Landscape with Augmentations to Counter Model Inversion
Si Chen ⋅ Feiyang Kang ⋅ Nikhil Abhyankar ⋅ Ming Jin ⋅ Ruoxi Jia
Probing Heterogeneous Pretraining Datasets with Small Curated Datasets
Gregory Yauney ⋅ Emily Reif ⋅ David Mimno
Dataset Interfaces: Diagnosing Model Failures Using Controllable Counterfactual Generation
Joshua Vendrow ⋅ Saachi Jain ⋅ Logan Engstrom ⋅ Aleksander Madry
EPIC: Graph Augmentation with Edit Path Interpolation via Learnable Cost
Jaeseung Heo ⋅ Seungbeom Lee ⋅ Sungsoo Ahn ⋅ Dongwoo Kim
Toward Practical Automatic Speech Recognition and Post-Processing: a Call for Explainable Error Benchmark Guideline
Seonmin Koo ⋅ Chanjun Park ⋅ Jinsung Kim ⋅ Jaehyung Seo ⋅ Sugyeong Eo ⋅ Hyeonseok Moon ⋅ HEUISEOK LIM
Contrastive clustering of tabular data
Piotr Przemielewski ⋅ Witold Wydmański ⋅ Marek Śmieja
Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning
Patrik Okanovic ⋅ Roger Waleffe ⋅ Vasileios Mageirakos ⋅ Konstantinos Nikolakakis ⋅ Amin Karbasi ⋅ Dionysios Kalogerias ⋅ Nezihe Merve Gürel ⋅ Theodoros Rekatsinas
Addressing Discrepancies in Semantic and Visual Alignment in Neural Networks
Natalie Abreu ⋅ Nathan Vaska ⋅ Victoria Helus
Fair Machine Unlearning: Data Removal while Mitigating Disparities
Alex Oesterling ⋅ Jiaqi Ma ⋅ Flavio Calmon ⋅ Hima Lakkaraju
TMARS: Improving Visual Representations by Circumventing Text Feature Learning
Pratyush Maini ⋅ Sachin Goyal ⋅ Zachary Lipton ⋅ Zico Kolter ⋅ Aditi Raghunathan
Do Machine Learning Models Learn Statistical Rules Inferred from Data?
Aaditya Naik ⋅ Yinjun Wu ⋅ Mayur Naik ⋅ Eric Wong
Knowledge Graph-Augmented Korean Generative Commonsense Reasoning
Dahyun Jung ⋅ Jaehyung Seo ⋅ Jaewook Lee ⋅ Chanjun Park ⋅ HEUISEOK LIM
Accelerating Batch Active Learning Using Continual Learning Techniques
Gantavya Bhatt ⋅ Arnav M Das ⋅ ⋅ Rui Yang ⋅ Vianne Gao ⋅ Jeff Bilmes
RewriteLM: An Instruction-Tuned Large Language Model for Text Rewriting
Liangchen Luo ⋅ Lei Shu ⋅ Jayakumar Hoskere ⋅ Yun Zhu ⋅ Canoee Liu ⋅ Simon Tong ⋅ Jindong Chen ⋅ Lei Meng
Data Similarity is Not Enough to Explain Language Model Performance
Gregory Yauney ⋅ Emily Reif ⋅ David Mimno
Enhancing Time Series Forecasting Models under Concept Drift by Data-centric Online Ensembling
Yi-Fan Zhang ⋅ Qingsong Wen ⋅ Xue Wang ⋅ Weiqi Chen ⋅ Liang Sun ⋅ Zhang Zhang ⋅ Liang Wang ⋅ Rong Jin ⋅ Tieniu Tan
A Privacy-Friendly Approach to Data Valuation
Jiachen Wang ⋅ Yuqing Zhu ⋅ Yu-Xiang Wang ⋅ Ruoxi Jia ⋅ Prateek Mittal
Performance Scaling via Optimal Transport: Enabling Data Selection from Partially Revealed Sources
Feiyang Kang ⋅ Hoang Anh Just ⋅ Anit Kumar Sahu ⋅ Ruoxi Jia
Improve Model Inference Cost with Image Gridding
Shreyas Krishnaswamy ⋅ Lisa Dunlap ⋅ Lingjiao Chen ⋅ Matei Zaharia ⋅ James Zou ⋅ Joseph Gonzalez
THOS: A Benchmark Dataset for Targeted Hate and Offensive Speech
Saad Almohaimeed ⋅ Saleh Almohaimeed ⋅ Saleh Almohaimeed ⋅ Ashfaq Ali Shafin ⋅ Bogdan Carbunar ⋅ Ladislau Boloni
On Robustness-Accuracy Characterization of Large Language Models using Synthetic Datasets
Ching-Yun (Irene) Ko ⋅ Pin-Yu Chen ⋅ Payel Das ⋅ Yung-Sung Chuang ⋅ Luca Daniel
Partial Label Learning meets Active Learning: Enhancing Annotation Efficiency through Binary Questioning
Shivangana Rawat ⋅ Chaitanya Devaguptapu ⋅ Vineeth Balasubramanian
Towards an Efficient Algorithm for Time Series Forecasting with Anomalies
Hao Cheng ⋅ Qingsong Wen ⋅ Yang Liu ⋅ Liang Sun
Towards Declarative Systems for Data-Centric Machine Learning
Stefan Grafberger ⋅ Bojan Karlaš ⋅ Paul Groth ⋅ Sebastian Schelter
No Imputation without Representation
Oliver Lenz ⋅ Daniel Peralta ⋅
L3Cube-MahaSent-MD: A Multi-domain Marathi Sentiment Analysis Dataset and Transformer Models
Aabha Pingle ⋅ Aditya Vyawahare ⋅ Isha Joshi ⋅ Rahul Tangsali ⋅ Raviraj Joshi
Point Cloud Classification with ModelNet40: What is left?
Jarne Van den Herrewegen ⋅ Tom Tourwé ⋅ Francis Wyffels
Does Progress On Object Recognition Benchmarks Improve Real-World Generalization?
Megan Richards ⋅ Diane Bouchacourt ⋅ Mark Ibrahim ⋅ Polina Kirichenko
In or Out? Fixing ImageNet Out-of-Distribution Detection Evaluation
Julian Bitterwolf ⋅ Maximilian Müller ⋅ Matthias Hein
Localized Data Work as a Precondition for Data-Centric ML: A Case Study of Full Lifecycle Crop Disease Identification in Ghana
Darlington Akogo ⋅ Issah Samori ⋅ Cyril Akafia ⋅ Harriet Fiagbor ⋅ Andrews Kangah ⋅ Donald Donald ⋅ Kwabena Fuachie ⋅ Luis Oala
On the Reproducibility of Data Valuation under Learning Stochasticity
Jiachen Wang ⋅ Feiyang Kang ⋅ Chiyuan Zhang ⋅ Ruoxi Jia ⋅ Prateek Mittal
On the Usefulness of Synthetic Tabular Data Generation
Dionysis Manousakas ⋅ Sergul Aydore
Bayesian Optimisation Against Climate Change: Applications and Benchmarks
Sigrid Passano Hellan ⋅ Chris Lucas ⋅ Nigel Goddard
Suboptimal Data Can Bottleneck Scaling
Jacob Buckman ⋅ Kshitij Gupta ⋅ Ethan Caballero ⋅ Rishabh Agarwal ⋅ Marc Bellemare
Speech Wikimedia: A 77 Language Multilingual Speech Dataset
Rafael Mosquera Gómez ⋅ Julian Eusse ⋅ Juan Ciro ⋅ Daniel Galvez ⋅ Ryan Hileman ⋅ Kurt Bollacker ⋅ David Kanter
Active learning for time instant classification
Nauman Ahad ⋅ Namrata Nadagouda ⋅ Eva Dyer ⋅ Mark Davenport
Prediction without Preclusion Recourse Verification with Reachable Sets
Avni Kothari ⋅ Berk Ustun ⋅ Lily Weng ⋅ Bogdan Kulynych
Skill-it! A Data-Driven Skills Framework for Understanding and Training Language Models
Mayee Chen ⋅ Nicholas Roberts ⋅ Kush Bhatia ⋅ Jue Wang ⋅ Ce Zhang ⋅ Frederic Sala ⋅ Christopher Ré
Mobile Internet Quality Estimation using Self-Tuning Kernel Regression
Hanyang Jiang ⋅ Yao Xie ⋅ Ellen Zegura ⋅ Elizabeth Belding ⋅ Shaowu Yuchi
STG-MTL: Scalable Task Grouping for Multi-Task Learning Using Data Maps
Ammar Sherif ⋅ Abubakar Abid ⋅ Mustafa Elattar ⋅ Mohamed ElHelw
Detecting Errors in Numerical Data via any Regression Model
Hang Zhou ⋅ Jonas Mueller ⋅ Mayank Kumar ⋅ Jane-Ling Wang ⋅ Jing Lei
ObjectLab: Automated Diagnosis of Mislabeled Images in Object Detection Data
Ulyana Tkachenko ⋅ Aditya Thyagarajan ⋅ Jonas Mueller
Characterizing Risk Regimes for Safe Deployment of Deep Regression Models
Jayaraman J. Thiagarajan ⋅ Vivek Narayanaswamy ⋅ Puja Trivedi ⋅ Rushil Anirudh
Offline Reinforcement Learning with Imbalanced Datasets
Li Jiang ⋅ Sijie Cheng ⋅ Jielin Qiu ⋅ Victor Chan ⋅ Ding Zhao
Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias
Yue Yu ⋅ Yuchen Zhuang ⋅ Jieyu Zhang ⋅ Yu Meng ⋅ Alex Ratner ⋅ Ranjay Krishna ⋅ Jiaming Shen ⋅ Chao Zhang
Is Pre-training Truly Better Than Meta-Learning?
Brando Miranda ⋅ Patrick Yu ⋅ Saumya Goyal ⋅ Yu-Xiong Wang ⋅ Sanmi Koyejo
Characterizing the Impacts of Semi-supervised Learning for Weak Supervision
Jeffrey Li ⋅ Jieyu Zhang ⋅ Ludwig Schmidt ⋅ Alex Ratner
A Skew-Sensitive Evaluation Framework for Imbalanced Data Classification
Min Du ⋅ Nesime Tatbul ⋅ Brian Rivers ⋅ Akhilesh Kumar Gupta ⋅ Lucas Hu ⋅ Wei Wang ⋅ Ryan Marcus ⋅ Shengtian Zhou ⋅ Insup Lee ⋅ Justin Gottschlich
Learning pipeline-invariant representation for robust brain phenotype prediction
Xinhui Li ⋅ Alex Fedorov ⋅ Mrinal Mathur ⋅ Anees Abrol ⋅ Gregory Kiar ⋅ Sergey Plis ⋅ Vince Calhoun
Improving multimodal datasets with image captioning
Thao Nguyen ⋅ ⋅ Gabriel Ilharco ⋅ Sewoong Oh ⋅ Ludwig Schmidt
Adaptive Aggregated Drift Detector
Beverly Quon ⋅ Jean-Luc Gaudiot
On Estimating the Epistemic Uncertainty of Graph Neural Networks using Stochastic Centering
Puja Trivedi ⋅ Mark Heimann ⋅ Rushil Anirudh ⋅ Danai Koutra ⋅ Jayaraman J. Thiagarajan
Identifying Implicit Social Biases in Vision-Language Models
Kimia Hamidieh ⋅ Haoran Zhang ⋅ Thomas Hartvigsen ⋅ Marzyeh Ghassemi
SemDeDup: Data-efficient learning at web-scale through semantic deduplication
Amro Abbas ⋅ Daniel Simig ⋅ Surya Ganguli ⋅ Ari Morcos ⋅ Kushal Tirumala
LabelBench: A Comprehensive Framework for Benchmarking Label-Efficient Learning
Jifan Zhang ⋅ Yifang Chen ⋅ Gregory Canal ⋅ Stephen Mussmann ⋅ Yinglun Zhu ⋅ Simon Du ⋅ Kevin Jamieson ⋅ Robert Nowak
Internet Explorer: Targeted Representation Learning on the Open Web
Alexander Li ⋅ Ellis Brown ⋅ Alexei Efros ⋅ Deepak Pathak
Graphtester: Exploring Theoretical Boundaries of GNNs on Graph Datasets
M. Eren Akbiyik ⋅ Florian Grötschla ⋅ Beni Egressy ⋅ Roger Wattenhofer
Uncovering Neural Scaling Law in Molecular Representation Learning
Dingshuo Chen ⋅ Yanqiao Zhu ⋅ Jieyu Zhang ⋅ Yuanqi Du ⋅ Zhixun Li ⋅ Qiang Liu ⋅ Shu Wu ⋅ Liang Wang
MultiLegalPile: A 689GB Multilingual Legal Corpus
Joel Niklaus ⋅ Veton Matoshi ⋅ Matthias Stürmer ⋅ Ilias Chalkidis ⋅ Daniel Ho
On Memorization and Privacy risks of Sharpness Aware Minimization
Young In Kim ⋅ Pratiksha Agrawal ⋅ Johannes Royset ⋅ RAJIV KHANNA
Evaluating the Evaluators: Are Current Few-Shot Learning Benchmarks Fit for Purpose?
Luísa Shimabucoro ⋅ Timothy Hospedales ⋅ Henry Gouk
The Matrix Reloaded: A Counterfactual Perspective on Bias in Machine Learning
Andre Carreiro ⋅ Mariana Pinto ⋅ Pedro Madeira ⋅ Alberto Lopez ⋅ Hugo Gamboa
D4: Document Deduplication and Diversification
Kushal Tirumala ⋅ Daniel Simig ⋅ Armen Aghajanyan ⋅ Ari Morcos
On Data Quality and Speed of Training: Bad Data Slows Training
Newsha Ardalani ⋅ Mostafa Elhoushi ⋅ Carole-Jean Wu
Put on your detective hat: What's wrong in this video?
Rohith Peddi ⋅ Shivvrat Arya ⋅ Bharath Challa ⋅ Likhitha Pallapothula ⋅ Akshay Vyas ⋅ Qifan Zhang ⋅ Jikai Wang ⋅ Vasundhara Komaragiri ⋅ Eric Ragan ⋅ Nicholas Ruozzi ⋅ Yu Xiang ⋅ Vibhav Gogate
Regularizing Neural Networks with Meta-Learning Generative Models
Shin'ya Yamaguchi ⋅ Daiki Chijiwa ⋅ Sekitoshi Kanai ⋅ Atsutoshi Kumagai ⋅ Hisashi Kashima
Taming Small-sample Bias in Low-budget Active Learning
Linxin Song ⋅ Jieyu Zhang ⋅ Xiaotian Lu ⋅ Tianyi Zhou
Training with Low-Label-Quality Data: Rank Pruning and Multi-Review
Yue Xing ⋅ Ashutosh Pandey ⋅ David Yan ⋅ Fei Wu ⋅ Michael Fronda ⋅ Pamela Bhattacharya
DataCI: A Platform for Data-Centric AI on Streaming Data
Huaizheng Zhang ⋅ Liao Chang ⋅ Yuanming Li
Participatory Personalization in Classification
Hailey Joren ⋅ Chirag Nagpal ⋅ Katherine Heller ⋅ Berk Ustun
Making Scalable Meta Learning Practical
Sang Keun Choe ⋅ Sanket Vaibhav Mehta ⋅ Hwijeen Ahn ⋅ Willie Neiswanger ⋅ Pengtao Xie ⋅ Emma Strubell ⋅ Eric Xing
Learning Better with Less: Effective Augmentation for Sample-Efficient Visual Reinforcement Learning
Guozheng Ma ⋅ ⋅ Haoyu Wang ⋅ Lu Li ⋅ Zilin Wang ⋅ Zhen Wang ⋅ Li Shen ⋅ Xueqian Wang ⋅ Dacheng Tao
Data Integration for Driver Telematics with Selection Biases
Hashan Peiris ⋅ Himchan Jeong ⋅ Jae-kwang Kim
Self-supervised Autoencoder for Correlation-Preserving in Tabular GANs
Siddarth Ramesh ⋅ Surgan Jandial ⋅ Gauri Gupta ⋅ Piyush Gupta ⋅ Balaji Krishnamurthy
Principlism Guided Responsible Data Curation
Jerone Andrews ⋅ Dora Zhao ⋅ William Thong ⋅ Apostolos Modas ⋅ Orestis Papakyriakopoulos ⋅ Alice Xiang