Alexander Ratner

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 44

Top Topics

Binary Classification

Top Venues

Publications

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
Found in the Middle: Calibrating Positional Attention Bias Improves Long Context Utilization. CoRR (2024)
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
Found in the middle: Calibrating Positional Attention Bias Improves Long Context Utilization. ACL (Findings) (2024)
Cheng-Yu Hsieh, Si-An Chen, Chun-Liang Li, Yasuhisa Fujii, Alexander Ratner, Chen-Yu Lee, Ranjay Krishna, Tomas Pfister
Tool Documentation Enables Zero-Shot Tool-Usage with Large Language Models. CoRR (2023)
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
DataComp: In search of the next generation of multimodal datasets. CoRR (2023)
Yue Yu, Yuchen Zhuang, Jieyu Zhang, Yu Meng, Alexander Ratner, Ranjay Krishna, Jiaming Shen, Chao Zhang
Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias. CoRR (2023)
Jieyu Zhang, Bohan Wang, Zhengyu Hu, Pang Wei Koh, Alexander Ratner
On the Trade-off of Intra-/Inter-class Diversity for Supervised Pre-training. CoRR (2023)
Cheng-Yu Hsieh, Chun-Liang Li, Chih-Kuan Yeh, Hootan Nakhost, Yasuhisa Fujii, Alexander Ratner, Ranjay Krishna, Chen-Yu Lee, Tomas Pfister
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes. CoRR (2023)
Dong He, Jieyu Zhang, Maureen Daum, Alexander Ratner, Magdalena Balazinska
MaskSearch: Querying Image Masks at Scale. CoRR (2023)
Cheng-Yu Hsieh, Jieyu Zhang, Alexander Ratner
Nemo: Guiding and Contextualizing Weak Supervision for Interactive Data Programming. CoRR (2022)
Jieyu Zhang, Linxin Song, Alexander Ratner
Leveraging Instance Features for Label Aggregation in Programmatic Weak Supervision. CoRR (2022)
Jieyu Zhang, Yujing Wang, Yaming Yang, Yang Luo, Alexander Ratner
Binary Classification with Positive Labeling Sources. CIKM (2022)
Jieyu Zhang, Bohan Wang, Xiangchen Song, Yujing Wang, Yaming Yang, Jing Bai, Alexander Ratner
Creating Training Sets via Weak Indirect Supervision. ICLR (2022)
Jieyu Zhang, Cheng-Yu Hsieh, Yue Yu, Chao Zhang, Alexander Ratner
A Survey on Programmatic Weak Supervision. CoRR (2022)
Jieyu Zhang, Yujing Wang, Yaming Yang, Yang Luo, Alexander Ratner
Binary Classification with Positive Labeling Sources. CoRR (2022)
Jieyu Zhang, Haonan Wang, Cheng-Yu Hsieh, Alexander Ratner
Understanding Programmatic Weak Supervision via Source-aware Influence Function. CoRR (2022)
Jieyu Zhang, Bohan Wang, Xiangchen Song, Yujing Wang, Yaming Yang, Jing Bai, Alexander Ratner
Creating Training Sets via Weak Indirect Supervision. CoRR (2021)
Jieyu Zhang, Yue Yu, NameError, Yujing Wang, Yaming Yang, Mao Yang, Alexander Ratner
WRENCH: A Comprehensive Benchmark for Weak Supervision. NeurIPS Datasets and Benchmarks (2021)
Jieyu Zhang, Yue Yu, Yinghao Li, Yujing Wang, Yaming Yang, Mao Yang, Alexander Ratner
WRENCH: A Comprehensive Benchmark for Weak Supervision. CoRR (2021)
Emily K. Mallory, Matthieu de Rochemonteix, Alexander Ratner, Ambika Acharya, Christopher Ré, Roselie A. Bright, Russ B. Altman
Extracting chemical reactions from text using Snorkel. BMC Bioinform. 21 (1) (2020)
Alexander Ratner, Stephen H. Bach, Henry R. Ehrenberg, Jason A. Fries, Sen Wu, Christopher Ré
Snorkel: rapid training data creation with weak supervision. VLDB J. 29 (2-3) (2020)
Khaled Saab, Jared Dunnmon, Roger E. Goldman, Alexander Ratner, Hersh Sagreiya, Christopher Ré, Daniel L. Rubin
Doubly Weak Supervision of Deep Learning Models for Head CT. MICCAI (3) (2019)
Paroma Varma, Frederic Sala, Ann He, Alexander Ratner, Christopher Ré
Learning Dependency Structures for Weak Supervision Models. CoRR (2019)
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
Cross-Modal Data Programming Enables Rapid Medical Machine Learning. CoRR (2019)
Eran Bringer, Abraham Israeli, Yoav Shoham, Alexander Ratner, Christopher Ré
Osprey: Weak Supervision of Imbalanced Extraction Problems without Code. DEEM@SIGMOD (2019)
Paroma Varma, Frederic Sala, Ann He, Alexander Ratner, Christopher Ré
Learning Dependency Structures for Weak Supervision Models. ICML (2019)
Alexander Ratner, Braden Hancock, Jared Dunnmon, Frederic Sala, Shreyash Pandey, Christopher Ré
Training Complex Models with Multi-Task Weak Supervision. AAAI (2019)
Vincent S. Chen, Sen Wu, Zhenzhen Weng, Alexander Ratner, Christopher Ré
Slice-based Learning: A Programming Model for Residual Learning in Critical Data Slices. CoRR (2019)
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
Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale. SIGMOD Conference (2019)
Alexander Ratner, Dan Alistarh, Gustavo Alonso, David G. Andersen, Peter Bailis, Sarah Bird, Nicholas Carlini, Bryan Catanzaro, Eric 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 G. 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 R. 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
SysML: The New Frontier of Machine Learning Systems. CoRR (2019)
Tri Dao, Albert Gu, Alexander Ratner, Virginia Smith, Chris De Sa, Christopher Ré
A Kernel Theory of Modern Data Augmentation. ICML (2019)
Alexander Ratner, Christopher Ré
Knowledge Base Construction in the Machine-learning Era. ACM Queue 16 (3) (2018)
Alexander Ratner, Christopher Ré, Peter Bailis
Research for practice: knowledge base construction in the machine-learning era. Commun. ACM 61 (11) (2018)
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
Snorkel DryBell: A Case Study in Deploying Weak Supervision at Industrial Scale. CoRR (2018)
Alexander Ratner, Braden Hancock, Jared Dunnmon, Frederic Sala, Shreyash Pandey, Christopher Ré
Training Complex Models with Multi-Task Weak Supervision. CoRR (2018)
Alexander Ratner, Braden Hancock, Jared Dunnmon, Roger E. Goldman, Christopher Ré
Snorkel MeTaL: Weak Supervision for Multi-Task Learning. DEEM@SIGMOD (2018)
Alexander Ratner, Stephen H. Bach, Henry R. Ehrenberg, Jason Alan Fries, Sen Wu, Christopher Ré
Snorkel: Rapid Training Data Creation with Weak Supervision. Proc. VLDB Endow. 11 (3) (2017)
Alexander Ratner, Stephen H. Bach, Henry R. Ehrenberg, Jason Alan Fries, Sen Wu, Christopher Ré
Snorkel: A System for Lightweight Extraction. CIDR (2017)
Jason A. Fries, Sen Wu, Alexander Ratner, Christopher Ré
SwellShark: A Generative Model for Biomedical Named Entity Recognition without Labeled Data. CoRR (2017)
Alexander Ratner, Stephen H. Bach, Henry R. Ehrenberg, Jason Alan Fries, Sen Wu, Christopher Ré
Snorkel: Rapid Training Data Creation with Weak Supervision. CoRR (2017)
Christopher De Sa, Alexander Ratner, Christopher Ré, Jaeho Shin, Feiran Wang, Sen Wu, Ce Zhang
Incremental knowledge base construction using DeepDive. VLDB J. 26 (1) (2017)
Stephen H. Bach, Bryan Dawei He, Alexander Ratner, Christopher Ré
Learning the Structure of Generative Models without Labeled Data. CoRR (2017)
Stephen H. Bach, Bryan Dawei He, Alexander Ratner, Christopher Ré
Learning the Structure of Generative Models without Labeled Data. ICML (2017)
Alexander Ratner, Christopher De Sa, Sen Wu, Daniel Selsam, Christopher Ré
Data Programming: Creating Large Training Sets, Quickly. CoRR (2016)
Christopher De Sa, Alexander Ratner, Christopher Ré, Jaeho Shin, Feiran Wang, Sen Wu, Ce Zhang
DeepDive: Declarative Knowledge Base Construction. SIGMOD Rec. 45 (1) (2016)