Pang Wei Koh

Publication Activity (10 Years)

Years Active: 2010-2024
Publications (10 Years): 70

Top Topics

Top Venues

Publications

Jiashu Xu, Fei Wang, Mingyu Derek Ma, Pang Wei Koh, Chaowei Xiao, Muhao Chen
Instructional Fingerprinting of Large Language Models. CoRR (2024)
Shuyue Stella Li, Vidhisha Balachandran, Shangbin Feng, Jonathan Ilgen, Emma Pierson, Pang Wei Koh, Yulia Tsvetkov
MEDIQ: Question-Asking LLMs for Adaptive and Reliable Clinical Reasoning. CoRR (2024)
Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D. Hwang, Liwei Jiang, Jillian Fisher, Abhilasha Ravichander, Khyathi Raghavi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, Yejin Choi
The Generative AI Paradox: "What It Can Create, It May Not Understand". ICLR (2024)
Rulin Shao, Jacqueline He, Akari Asai, Weijia Shi, Tim Dettmers, Sewon Min, Luke Zettlemoyer, Pang Wei Koh
Scaling Retrieval-Based Language Models with a Trillion-Token Datastore. CoRR (2024)
Scott Geng, Cheng-Yu Hsieh, Vivek Ramanujan, Matthew Wallingford, Chun-Liang Li, Pang Wei Koh, Ranjay Krishna
The Unmet Promise of Synthetic Training Images: Using Retrieved Real Images Performs Better. CoRR (2024)
Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Guha, Sedrick Keh, Kushal Arora, Saurabh Garg, Rui Xin, Niklas Muennighoff, Reinhard Heckel, Jean Mercat, Mayee Chen, Suchin Gururangan, Mitchell Wortsman, Alon Albalak, Yonatan Bitton, Marianna Nezhurina, Amro Abbas, Cheng-Yu Hsieh, Dhruba Ghosh, Josh Gardner, Maciej Kilian, Hanlin Zhang, Rulin Shao, Sarah M. Pratt, Sunny Sanyal, Gabriel Ilharco, Giannis Daras, Kalyani Marathe, Aaron Gokaslan, Jieyu Zhang, Khyathi Raghavi Chandu, Thao Nguyen, Igor Vasiljevic, Sham M. Kakade, Shuran Song, Sujay Sanghavi, Fartash Faghri, Sewoong Oh, Luke Zettlemoyer, Kyle Lo, Alaaeldin El-Nouby, Hadi Pouransari, Alexander Toshev, Stephanie Wang, Dirk Groeneveld, Luca Soldaini, Pang Wei Koh, Jenia Jitsev, Thomas Kollar, Alexandros G. Dimakis, Yair Carmon, Achal Dave, Ludwig Schmidt, Vaishaal Shankar
DataComp-LM: In search of the next generation of training sets for language models. CoRR (2024)
Xinyi Xu, Zhaoxuan Wu, Rui Qiao, Arun Verma, Yao Shu, Jingtan Wang, Xinyuan Niu, Zhenfeng He, Jiangwei Chen, Zijian Zhou, Gregory Kang Ruey Lau, Hieu Dao, Lucas Agussurja, Rachael Hwee Ling Sim, Xiaoqiang Lin, Wenyang Hu, Zhongxiang Dai, Pang Wei Koh, Bryan Kian Hsiang Low
Data-Centric AI in the Age of Large Language Models. CoRR (2024)
Tong Chen, Akari Asai, Niloofar Mireshghallah, Sewon Min, James Grimmelmann, Yejin Choi, Hannaneh Hajishirzi, Luke Zettlemoyer, Pang Wei Koh
CopyBench: Measuring Literal and Non-Literal Reproduction of Copyright-Protected Text in Language Model Generation. CoRR (2024)
Akari Asai, Zexuan Zhong, Danqi Chen, Pang Wei Koh, Luke Zettlemoyer, Hannaneh Hajishirzi, Wen-tau Yih
Reliable, Adaptable, and Attributable Language Models with Retrieval. CoRR (2024)
Anshul Nasery, Jonathan Hayase, Pang Wei Koh, Sewoong Oh
PLeaS - Merging Models with Permutations and Least Squares. CoRR (2024)
Rajiv Movva, Pang Wei Koh, Emma Pierson
Annotation alignment: Comparing LLM and human annotations of conversational safety. CoRR (2024)
Jiashu Xu, Fei Wang, Mingyu Derek Ma, Pang Wei Koh, Chaowei Xiao, Muhao Chen
Instructional Fingerprinting of Large Language Models. NAACL-HLT (2024)
Zhiyuan Hu, Chumin Liu, Xidong Feng, Yilun Zhao, See-Kiong Ng, Anh Tuan Luu, Junxian He, Pang Wei Koh, Bryan Hooi
Uncertainty of Thoughts: Uncertainty-Aware Planning Enhances Information Seeking in Large Language Models. CoRR (2024)
Jaehun Jung, Ximing Lu, Liwei Jiang, Faeze Brahman, Peter West, Pang Wei Koh, Yejin Choi
Information-Theoretic Distillation for Reference-less Summarization. CoRR (2024)
Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn
Improving Domain Generalization with Domain Relations. ICLR (2024)
Thao Nguyen, Matthew Wallingford, Sebastin Santy, Wei-Chiu Ma, Sewoong Oh, Ludwig Schmidt, Pang Wei Koh, Ranjay Krishna
Multilingual Diversity Improves Vision-Language Representations. CoRR (2024)
Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Wei Koh, Mohit Iyyer, Luke Zettlemoyer, Hannaneh Hajishirzi
FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation. EMNLP (2023)
Miao Xiong, Ailin Deng, Pang Wei Koh, Jiaying Wu, Shen Li, Jianqing Xu, Bryan Hooi
Proximity-Informed Calibration for Deep Neural Networks. CoRR (2023)
Emma Pierson, Divya Shanmugam, Rajiv Movva, Jon M. Kleinberg, Monica Agrawal, Mark Dredze, Kadija Ferryman, Judy Wawira Gichoya, Dan Jurafsky, Pang Wei Koh, Karen Levy, Sendhil Mullainathan, Ziad Obermeyer, Harini Suresh, Keyon Vafa
Use large language models to promote equity. CoRR (2023)
Jieyu Zhang, Bohan Wang, Zhengyu Hu, Pang Wei Koh, Alexander J. Ratner
On the Trade-off of Intra-/Inter-class Diversity for Supervised Pre-training. NeurIPS (2023)
Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Wei Koh, Mohit Iyyer, Luke Zettlemoyer, Hannaneh Hajishirzi
FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation. 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)
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)
Anas Awadalla, Irena Gao, Josh Gardner, Jack Hessel, Yusuf Hanafy, Wanrong Zhu, Kalyani Marathe, Yonatan Bitton, Samir Yitzhak Gadre, Shiori Sagawa, Jenia Jitsev, Simon Kornblith, Pang Wei Koh, Gabriel Ilharco, Mitchell Wortsman, Ludwig Schmidt
OpenFlamingo: An Open-Source Framework for Training Large Autoregressive Vision-Language Models. CoRR (2023)
Irena Gao, Shiori Sagawa, Pang Wei Koh, Tatsunori Hashimoto, Percy Liang
Out-of-Domain Robustness via Targeted Augmentations. CoRR (2023)
Peter West, Ximing Lu, Nouha Dziri, Faeze Brahman, Linjie Li, Jena D. Hwang, Liwei Jiang, Jillian Fisher, Abhilasha Ravichander, Khyathi Chandu, Benjamin Newman, Pang Wei Koh, Allyson Ettinger, Yejin Choi
The Generative AI Paradox: "What It Can Create, It May Not Understand". 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 J. 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. NeurIPS (2023)
Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Irena Gao, Anas Awadalla, Pang Wei Koh, Daphne Ippolito, Katherine Lee, Florian Tramèr, Ludwig Schmidt
Are aligned neural networks adversarially aligned? CoRR (2023)
Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn
Leveraging Domain Relations for Domain Generalization. CoRR (2023)
Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Irena Gao, Pang Wei Koh, Daphne Ippolito, Florian Tramèr, Ludwig Schmidt
Are aligned neural networks adversarially aligned? NeurIPS (2023)
Irena Gao, Shiori Sagawa, Pang Wei Koh, Tatsunori Hashimoto, Percy Liang
Out-of-Domain Robustness via Targeted Augmentations. ICML (2023)
Huaxiu Yao, Caroline Choi, Bochuan Cao, Yoonho Lee, Pang Wei Koh, Chelsea Finn
Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time. NeurIPS (2022)
Huaxiu Yao, Caroline Choi, Bochuan Cao, Yoonho Lee, Pang Wei Koh, Chelsea Finn
Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time. CoRR (2022)
Blair Bilodeau, Natasha Jaques, Pang Wei Koh, Been Kim
Impossibility Theorems for Feature Attribution. CoRR (2022)
Pang Wei Koh, Jacob Steinhardt, Percy Liang
Stronger data poisoning attacks break data sanitization defenses. Mach. Learn. 111 (1) (2022)
Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang
Extending the WILDS Benchmark for Unsupervised Adaptation. ICLR (2022)
Serina Chang, Mandy L. Wilson, Bryan L. Lewis, Zakaria Mehrab, Komal K. Dudakiya, Emma Pierson, Pang Wei Koh, Jaline Gerardin, Beth Redbird, David Grusky, Madhav Marathe, Jure Leskovec
Supporting COVID-19 Policy Response with Large-scale Mobility-based Modeling. KDD (2021)
Erik Jones, Shiori Sagawa, Pang Wei Koh, Ananya Kumar, Percy Liang
Selective Classification Can Magnify Disparities Across Groups. ICLR (2021)
Serina Chang, Emma Pierson, Pang Wei Koh, Jaline Gerardin, Beth Redbird, David Grusky, Jure Leskovec
Mobility network models of COVID-19 explain inequities and inform reopening. Nat. 589 (7840) (2021)
Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, Rodrigo Castellon, Niladri S. Chatterji, Annie S. Chen, Kathleen Creel, Jared Quincy Davis, Dorottya Demszky, Chris Donahue, Moussa Doumbouya, Esin Durmus, Stefano Ermon, John Etchemendy, Kawin Ethayarajh, Li Fei-Fei, Chelsea Finn, Trevor Gale, Lauren Gillespie, Karan Goel, Noah D. Goodman, Shelby Grossman, Neel Guha, Tatsunori Hashimoto, Peter Henderson, John Hewitt, Daniel E. Ho, Jenny Hong, Kyle Hsu, Jing Huang, Thomas Icard, Saahil Jain, Dan Jurafsky, Pratyusha Kalluri, Siddharth Karamcheti, Geoff Keeling, Fereshte Khani, Omar Khattab, Pang Wei Koh, Mark S. Krass, Ranjay Krishna, Rohith Kuditipudi, et al.
On the Opportunities and Risks of Foundation Models. CoRR (2021)
John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt
Accuracy on the Line: On the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization. CoRR (2021)
Evan Zheran Liu, Behzad Haghgoo, Annie S. Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn
Just Train Twice: Improving Group Robustness without Training Group Information. CoRR (2021)
John P. Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt
Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization. ICML (2021)
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Irena Gao, Tony Lee, Etienne David, Ian Stavness, Wei Guo, Berton Earnshaw, Imran Haque, Sara M. Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang
WILDS: A Benchmark of in-the-Wild Distribution Shifts. ICML (2021)
Evan Zheran Liu, Behzad Haghgoo, Annie S. Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn
Just Train Twice: Improving Group Robustness without Training Group Information. ICML (2021)
Shiori Sagawa, Pang Wei Koh, Tony Lee, Irena Gao, Sang Michael Xie, Kendrick Shen, Ananya Kumar, Weihua Hu, Michihiro Yasunaga, Henrik Marklund, Sara Beery, Etienne David, Ian Stavness, Wei Guo, Jure Leskovec, Kate Saenko, Tatsunori Hashimoto, Sergey Levine, Chelsea Finn, Percy Liang
Extending the WILDS Benchmark for Unsupervised Adaptation. CoRR (2021)
Shiori Sagawa, Aditi Raghunathan, Pang Wei Koh, Percy Liang
An Investigation of Why Overparameterization Exacerbates Spurious Correlations. CoRR (2020)
Erik Jones, Shiori Sagawa, Pang Wei Koh, Ananya Kumar, Percy Liang
Selective Classification Can Magnify Disparities Across Groups. CoRR (2020)
Pang Wei Koh, Thao Nguyen, Yew Siang Tang, Stephen Mussmann, Emma Pierson, Been Kim, Percy Liang
Concept Bottleneck Models. CoRR (2020)
Pang Wei Koh, Shiori Sagawa, Henrik Marklund, Sang Michael Xie, Marvin Zhang, Akshay Balsubramani, Weihua Hu, Michihiro Yasunaga, Richard Lanas Phillips, Sara Beery, Jure Leskovec, Anshul Kundaje, Emma Pierson, Sergey Levine, Chelsea Finn, Percy Liang
WILDS: A Benchmark of in-the-Wild Distribution Shifts. CoRR (2020)
Miles Brundage, Shahar Avin, Jasmine Wang, Haydn Belfield, Gretchen Krueger, Gillian K. Hadfield, Heidy Khlaaf, Jingying Yang, Helen Toner, Ruth Fong, Tegan Maharaj, Pang Wei Koh, Sara Hooker, Jade Leung, Andrew Trask, Emma Bluemke, Jonathan Lebensold, Cullen O'Keefe, Mark Koren, Théo Ryffel, J. B. Rubinovitz, Tamay Besiroglu, Federica Carugati, Jack Clark, Peter Eckersley, Sarah de Haas, Maritza Johnson, Ben Laurie, Alex Ingerman, Igor Krawczuk, Amanda Askell, Rosario Cammarota, Andrew Lohn, David Krueger, Charlotte Stix, Peter Henderson, Logan Graham, Carina Prunkl, Bianca Martin, Elizabeth Seger, Noa Zilberman, Seán Ó hÉigeartaigh, Frens Kroeger, Girish Sastry, Rebecca Kagan, Adrian Weller, Brian Tse, Elizabeth Barnes, Allan Dafoe, Paul Scharre, Ariel Herbert-Voss, Martijn Rasser, Shagun Sodhani, Carrick Flynn, Thomas Krendl Gilbert, Lisa Dyer, Saif Khan, Yoshua Bengio, Markus Anderljung
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. CoRR (2020)
Shiori Sagawa, Pang Wei Koh, Tatsunori B. Hashimoto, Percy Liang
Distributionally Robust Neural Networks. ICLR (2020)
Shiori Sagawa, Aditi Raghunathan, Pang Wei Koh, Percy Liang
An Investigation of Why Overparameterization Exacerbates Spurious Correlations. ICML (2020)
Shikhar Murty, Pang Wei Koh, Percy Liang
ExpBERT: Representation Engineering with Natural Language Explanations. CoRR (2020)
Shikhar Murty, Pang Wei Koh, Percy Liang
ExpBERT: Representation Engineering with Natural Language Explanations. ACL (2020)
Pang Wei Koh, Thao Nguyen, Yew Siang Tang, Stephen Mussmann, Emma Pierson, Been Kim, Percy Liang
Concept Bottleneck Models. ICML (2020)
Emma Pierson, Pang Wei Koh, Tatsunori B. Hashimoto, Daphne Koller, Jure Leskovec, Nick Eriksson, Percy Liang
Inferring Multidimensional Rates of Aging from Cross-Sectional Data. AISTATS (2019)
Sawyer Birnbaum, Volodymyr Kuleshov, S. Zayd Enam, Pang Wei Koh, Stefano Ermon
Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise Modulations. NeurIPS (2019)
Pang Wei Koh, Kai-Siang Ang, Hubert H. K. Teo, Percy Liang
On the Accuracy of Influence Functions for Measuring Group Effects. NeurIPS (2019)
Pang Wei Koh, Kai-Siang Ang, Hubert H. K. Teo, Percy Liang
On the Accuracy of Influence Functions for Measuring Group Effects. CoRR (2019)
Pang Wei Koh
Identifying and exploiting influential training examples. AAAI Spring Symposium: Interpretable AI for Well-being (2019)
Shiori Sagawa, Pang Wei Koh, Tatsunori B. Hashimoto, Percy Liang
Distributionally Robust Neural Networks for Group Shifts: On the Importance of Regularization for Worst-Case Generalization. CoRR (2019)
Sawyer Birnbaum, Volodymyr Kuleshov, S. Zayd Enam, Pang Wei Koh, Stefano Ermon
Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise Modulations. CoRR (2019)
Pang Wei Koh, Jacob Steinhardt, Percy Liang
Stronger Data Poisoning Attacks Break Data Sanitization Defenses. CoRR (2018)
Emma Pierson, Pang Wei Koh, Tatsunori B. Hashimoto, Daphne Koller, Jure Leskovec, Nicholas Eriksson, Percy Liang
Inferring Multi-Dimensional Rates of Aging from Cross-Sectional Data. CoRR (2018)
Pang Wei Koh, Percy Liang
Understanding Black-box Predictions via Influence Functions. ICML (2017)
Jacob Steinhardt, Pang Wei Koh, Percy Liang
Certified Defenses for Data Poisoning Attacks. NIPS (2017)
Jacob Steinhardt, Pang Wei Koh, Percy Liang
Certified Defenses for Data Poisoning Attacks. CoRR (2017)
Pang Wei Koh, Emma Pierson, Anshul Kundaje
Denoising genome-wide histone ChIP-seq with convolutional neural networks. Bioinform. 33 (14) (2017)
Pang Wei Koh, Percy Liang
Understanding Black-box Predictions via Influence Functions. CoRR (2017)
Jiquan Ngiam, Zhenghao Chen, Pang Wei Koh, Andrew Y. Ng
Learning Deep Energy Models. ICML (2011)
Andrew M. Saxe, Pang Wei Koh, Zhenghao Chen, Maneesh Bhand, Bipin Suresh, Andrew Y. Ng
On Random Weights and Unsupervised Feature Learning. ICML (2011)
Jiquan Ngiam, Pang Wei Koh, Zhenghao Chen, Sonia A. Bhaskar, Andrew Y. Ng
Sparse Filtering. NIPS (2011)
Quoc V. Le, Jiquan Ngiam, Zhenghao Chen, Daniel Jin hao Chia, Pang Wei Koh, Andrew Y. Ng
Tiled convolutional neural networks. NIPS (2010)