Alexander Ratner

48 papers A* 7A 2Journal 32Unranked 6

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	Towards Acyclic Preference Evaluation of Language Models via Multiple Evaluators. AAAI Zhengyu Hu, Jieyu Zhang, Zhihan Xiong, Alexander Ratner, Kaize Ding, Ranjay Krishna
2025	A*	`conf`	MaskSearch: Querying Image Masks at Scale. ICDE Dong He, Jieyu Zhang, Maureen Daum, Alexander Ratner, Magdalena Balazinska
2024	J	`jnl`	Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization. CoRR Cheng-Yu Hsieh, Yung-Sung Chuang, Chun-Liang Li, Zifeng Wang, Long T. Le, Abhishek Kumar, James R. Glass, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister
2024	—	`conf`	Found in the middle: Calibrating Positional Attention Bias Improves Long Context Utilization. ACL (Findings) Cheng-Yu Hsieh, Yung-Sung Chuang, Chun-Liang Li, Zifeng Wang, Long T. Le, Abhishek Kumar, James R. Glass, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister
2024	J	`jnl`	Language Model Preference Evaluation with Multiple Weak Evaluators. CoRR Zhengyu Hu, Jieyu Zhang, Zhihan Xiong, Alexander Ratner, Hui Xiong, Ranjay Krishna
2023	J	`jnl`	DataComp: In search of the next generation of multimodal datasets. CoRR Samir Yitzhak Gadre, Gabriel Ilharco, Alex Fang, Jonathan Hayase, Georgios Smyrnis, Thao Nguyen, Ryan Marten, Mitchell Wortsman, Dhruba Ghosh, Jieyu Zhang, Eyal Orgad, Rahim Entezari, Giannis Daras, Sarah M. Pratt, Vivek Ramanujan, Yonatan Bitton, Kalyani Marathe, Stephen Mussmann, Richard Vencu, Mehdi Cherti, Ranjay Krishna, Pang Wei Koh, Olga Saukh, Alexander Ratner, Shuran Song, Hannaneh Hajishirzi, Ali Farhadi, Romain Beaumont, Sewoong Oh, Alex Dimakis, Jenia Jitsev, Yair Carmon, Vaishaal Shankar, Ludwig Schmidt
2023	J	`jnl`	Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes. CoRR Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alexander Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister
2023	J	`jnl`	Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias. CoRR Yue Yu, Yuchen Zhuang, Jieyu Zhang, Yu Meng, Alexander Ratner, Ranjay Krishna, Jiaming Shen, Chao Zhang
2023	J	`jnl`	MaskSearch: Querying Image Masks at Scale. CoRR Dong He, Jieyu Zhang, Maureen Daum, Alexander Ratner, Magdalena Balazinska
2023	J	`jnl`	On the Trade-off of Intra-/Inter-class Diversity for Supervised Pre-training. CoRR Jieyu Zhang, Bohan Wang, Zhengyu Hu, Pang Wei Koh, Alexander Ratner
2023	J	`jnl`	Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models. CoRR Cheng-Yu Hsieh, Si-An Chen, Chun-Liang Li, Yasuhisa Fujii, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister
2022	J	`jnl`	A Survey on Programmatic Weak Supervision. CoRR Jieyu Zhang, Cheng-Yu Hsieh, Yue Yu, Chao Zhang, Alexander Ratner
2022	A	`conf`	Binary Classification with Positive Labeling Sources. CIKM Jieyu Zhang, Yujing Wang, Yaming Yang, Yang Luo, Alexander Ratner
2022	J	`jnl`	Binary Classification with Positive Labeling Sources. CoRR Jieyu Zhang, Yujing Wang, Yaming Yang, Yang Luo, Alexander Ratner
2022	A*	`conf`	Creating Training Sets via Weak Indirect Supervision. ICLR Jieyu Zhang, Bohan Wang, Xiangchen Song, Yujing Wang, Yaming Yang, Jing Bai, Alexander Ratner
2022	J	`jnl`	Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervision. CoRR Jieyu Zhang, Linxin Song, Alexander Ratner
2022	J	`jnl`	Nemo: Guiding and Contextualizing Weak Supervision for Interactive Data Programming. CoRR Cheng-Yu Hsieh, Jieyu Zhang, Alexander Ratner
2022	J	`jnl`	Understanding Programmatic Weak Supervision via Source-aware Influence Function. CoRR Jieyu Zhang, Haonan Wang, Cheng-Yu Hsieh, Alexander Ratner
2021	J	`jnl`	Creating Training Sets via Weak Indirect Supervision. CoRR Jieyu Zhang, Bohan Wang, Xiangchen Song, Yujing Wang, Yaming Yang, Jing Bai, Alexander Ratner
2021	—	`conf`	WRENCH: A Comprehensive Benchmark for Weak Supervision. NeurIPS Datasets and Benchmarks Jieyu Zhang, Yue Yu, Yinghao Li, Yujing Wang, Yaming Yang, Mao Yang, Alexander Ratner
2021	J	`jnl`	WRENCH: A Comprehensive Benchmark for Weak Supervision. CoRR Jieyu Zhang, Yue Yu, Yinghao Li, Yujing Wang, Yaming Yang, Mao Yang, Alexander Ratner
2020	J	`jnl`	Extracting chemical reactions from text using Snorkel. BMC Bioinform. Emily K. Mallory, Matthieu de Rochemonteix, Alexander Ratner, Ambika Acharya, Christopher Ré, Roselie A. Bright, Russ B. Altman
2020	J	`jnl`	Snorkel: rapid training data creation with weak supervision. VLDB J. Alexander Ratner, Stephen H. Bach, Henry R. Ehrenberg, Jason A. Fries, Sen Wu, Christopher Ré
2019	A*	`conf`	A Kernel Theory of Modern Data Augmentation. ICML Tri Dao, Albert Gu, Alexander Ratner, Virginia Smith, Chris De Sa, Christopher Ré
2019	—	`—`	Accelerating machine learning with training data management. Alexander Ratner
2019	J	`jnl`	Cross-Modal Data Programming Enables Rapid Medical Machine Learning. CoRR Jared Dunnmon, Alexander Ratner, Nishith Khandwala, Khaled Saab, Matthew Markert, Hersh Sagreiya, Roger E. Goldman, Christopher Lee-Messer, Matthew P. Lungren, Daniel L. Rubin, Christopher Ré
2019	—	`conf`	Doubly Weak Supervision of Deep Learning Models for Head CT. MICCAI (3) Khaled Saab, Jared Dunnmon, Roger E. Goldman, Alexander Ratner, Hersh Sagreiya, Christopher Ré, Daniel L. Rubin
2019	A*	`conf`	Learning Dependency Structures for Weak Supervision Models. ICML Paroma Varma, Frederic Sala, Ann He, Alexander Ratner, Christopher Ré
2019	J	`jnl`	Learning Dependency Structures for Weak Supervision Models. CoRR Paroma Varma, Frederic Sala, Ann He, Alexander Ratner, Christopher Ré
2019	—	`conf`	Osprey: Weak Supervision of Imbalanced Extraction Problems without Code. DEEM@SIGMOD Eran Bringer, Abraham Israeli, Yoav Shoham, Alexander Ratner, Christopher Ré
2019	J	`jnl`	Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices. CoRR Vincent S. Chen, Sen Wu, Zhenzhen Weng, Alexander Ratner, Christopher Ré
2019	—	`conf`	Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale. SIGMOD Conference Stephen H. Bach, Daniel Rodriguez, Yintao Liu, Chong Luo, Haidong Shao, Cassandra Xia, Souvik Sen, Alexander Ratner, Braden Hancock, Houman Alborzi, Rahul Kuchhal, Christopher Ré, Rob Malkin
2019	J	`jnl`	SysML: The New Frontier of Machine Learning Systems. CoRR Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric S. Chung, Bill Dally, Jeff Dean, Inderjit S. Dhillon, Alexandros G. Dimakis, Pradeep Dubey, Charles Elkan, Grigori Fursin, Gregory R. Ganger, Lise Getoor, Phillip B. Gibbons, Garth A. Gibson, Joseph E. Gonzalez, Justin Gottschlich, Song Han, Kim M. Hazelwood, Furong Huang, Martin Jaggi, Kevin Jamieson, Michael I. Jordan, Gauri Joshi, Rania Khalaf, Jason Knight, Jakub Konecný, Tim Kraska, Arun Kumar, Anastasios Kyrillidis, Jing Li, Samuel Madden, H. Brendan McMahan, Erik Meijer, Ioannis Mitliagkas, Rajat Monga, Derek Gordon Murray, Dimitris S. Papailiopoulos, Gennady Pekhimenko, Theodoros Rekatsinas, Afshin Rostamizadeh, Christopher Ré, Christopher De Sa, Hanie Sedghi, Siddhartha Sen, Virginia Smith, Alex Smola, Dawn Song, Evan Randall Sparks, Ion Stoica, Vivienne Sze, Madeleine Udell, Joaquin Vanschoren, Shivaram Venkataraman, Rashmi Vinayak, Markus Weimer, Andrew Gordon Wilson, Eric P. Xing, Matei Zaharia, Ce Zhang, Ameet Talwalkar
2019	A*	`conf`	Training Complex Models with Multi-Task Weak Supervision. AAAI Alexander Ratner, Braden Hancock, Jared Dunnmon, Frederic Sala, Shreyash Pandey, Christopher Ré
2018	J	`jnl`	Knowledge Base Construction in the Machine-learning Era. ACM Queue Alexander Ratner, Christopher Ré
2018	J	`jnl`	Research for practice: knowledge base construction in the machine-learning era. Commun. ACM Alexander Ratner, Christopher Ré, Peter Bailis
2018	J	`jnl`	Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale. CoRR Stephen H. Bach, Daniel Rodriguez, Yintao Liu, Chong Luo, Haidong Shao, Cassandra Xia, Souvik Sen, Alexander Ratner, Braden Hancock, Houman Alborzi, Rahul Kuchhal, Christopher Ré, Rob Malkin
2018	—	`conf`	Snorkel MeTaL: Weak Supervision for Multi-Task Learning. DEEM@SIGMOD Alexander Ratner, Braden Hancock, Jared Dunnmon, Roger E. Goldman, Christopher Ré
2018	J	`jnl`	Training Complex Models with Multi-Task Weak Supervision. CoRR Alexander Ratner, Braden Hancock, Jared Dunnmon, Frederic Sala, Shreyash Pandey, Christopher Ré
2017	J	`jnl`	Incremental knowledge base construction using DeepDive. VLDB J. Christopher De Sa, Alexander Ratner, Christopher Ré, Jaeho Shin, Feiran Wang, Sen Wu, Ce Zhang
2017	A*	`conf`	Learning the Structure of Generative Models without Labeled Data. ICML Stephen H. Bach, Bryan Dawei He, Alexander Ratner, Christopher Ré
2017	J	`jnl`	Learning the Structure of Generative Models without Labeled Data. CoRR Stephen H. Bach, Bryan Dawei He, Alexander Ratner, Christopher Ré
2017	A	`conf`	Snorkel: A System for Lightweight Extraction. CIDR Alexander Ratner, Stephen H. Bach, Henry R. Ehrenberg, Jason Alan Fries, Sen Wu, Christopher Ré
2017	J	`jnl`	Snorkel: Rapid Training Data Creation with Weak Supervision. CoRR Alexander Ratner, Stephen H. Bach, Henry R. Ehrenberg, Jason Alan Fries, Sen Wu, Christopher Ré
2017	J	`jnl`	Snorkel: Rapid Training Data Creation with Weak Supervision. Proc. VLDB Endow. Alexander Ratner, Stephen H. Bach, Henry R. Ehrenberg, Jason Alan Fries, Sen Wu, Christopher Ré
2017	J	`jnl`	SwellShark: A Generative Model for Biomedical Named Entity Recognition without Labeled Data. CoRR Jason A. Fries, Sen Wu, Alexander Ratner, Christopher Ré
2016	J	`jnl`	Data Programming: Creating Large Training Sets, Quickly. CoRR Alexander Ratner, Christopher De Sa, Sen Wu, Daniel Selsam, Christopher Ré
2016	J	`jnl`	DeepDive: Declarative Knowledge Base Construction. SIGMOD Rec. Christopher De Sa, Alexander Ratner, Christopher Ré, Jaeho Shin, Feiran Wang, Sen Wu, Ce Zhang