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2020 – today
- 2024
- [c34]Rajiv Movva, Pang Wei Koh, Emma Pierson:
Annotation alignment: Comparing LLM and human annotations of conversational safety. EMNLP 2024: 9048-9062 - [c33]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:
Position Paper: Data-Centric AI in the Age of Large Language Models. EMNLP (Findings) 2024: 11895-11913 - [c32]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. EMNLP 2024: 15134-15158 - [c31]Jacob Morrison, Noah A. Smith, Hannaneh Hajishirzi, Pang Wei Koh, Jesse Dodge, Pradeep Dasigi:
Merge to Learn: Efficiently Adding Skills to Language Models with Model Merging. EMNLP (Findings) 2024: 15604-15621 - [c30]Shuyue Stella Li, Vidhisha Balachandran, Shangbin Feng, Emma Pierson, Pang Wei Koh, Yulia Tsvetkov:
Beyond the Stethoscope: Operationalizing Interactive Clinical Reasoning in Large Language Models via Proactive Information Seeking. ICHI 2024: 567 - [c29]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 - [c28]Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn:
Improving Domain Generalization with Domain Relations. ICLR 2024 - [c27]Jiashu Xu, Fei Wang, Mingyu Derek Ma, Pang Wei Koh, Chaowei Xiao, Muhao Chen:
Instructional Fingerprinting of Large Language Models. NAACL-HLT 2024: 3277-3306 - [i45]Jiashu Xu, Fei Wang, Mingyu Derek Ma, Pang Wei Koh, Chaowei Xiao, Muhao Chen:
Instructional Fingerprinting of Large Language Models. CoRR abs/2401.12255 (2024) - [i44]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 abs/2402.03271 (2024) - [i43]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 abs/2403.03187 (2024) - [i42]Jaehun Jung, Ximing Lu, Liwei Jiang, Faeze Brahman, Peter West, Pang Wei Koh, Yejin Choi:
Information-Theoretic Distillation for Reference-less Summarization. CoRR abs/2403.13780 (2024) - [i41]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 abs/2405.16915 (2024) - [i40]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 abs/2406.00922 (2024) - [i39]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 abs/2406.05184 (2024) - [i38]Rajiv Movva, Pang Wei Koh, Emma Pierson:
Annotation alignment: Comparing LLM and human annotations of conversational safety. CoRR abs/2406.06369 (2024) - [i37]Jeffrey Li, Alex Fang, Georgios Smyrnis, Maor Ivgi, Matt Jordan, Samir Yitzhak Gadre, Hritik Bansal, Etash Kumar 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 abs/2406.11794 (2024) - [i36]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 abs/2406.14473 (2024) - [i35]Anshul Nasery, Jonathan Hayase, Pang Wei Koh, Sewoong Oh:
PLeaS - Merging Models with Permutations and Least Squares. CoRR abs/2407.02447 (2024) - [i34]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 abs/2407.07087 (2024) - [i33]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 abs/2407.12854 (2024) - [i32]Xiaochuang Han, Marjan Ghazvininejad, Pang Wei Koh, Yulia Tsvetkov:
JPEG-LM: LLMs as Image Generators with Canonical Codec Representations. CoRR abs/2408.08459 (2024) - [i31]Niklas Muennighoff, Luca Soldaini, Dirk Groeneveld, Kyle Lo, Jacob Morrison, Sewon Min, Weijia Shi, Pete Walsh, Oyvind Tafjord, Nathan Lambert, Yuling Gu, Shane Arora, Akshita Bhagia, Dustin Schwenk, David Wadden, Alexander Wettig, Binyuan Hui, Tim Dettmers, Douwe Kiela, Ali Farhadi, Noah A. Smith, Pang Wei Koh, Amanpreet Singh, Hannaneh Hajishirzi:
OLMoE: Open Mixture-of-Experts Language Models. CoRR abs/2409.02060 (2024) - [i30]Jacob Morrison, Noah A. Smith, Hannaneh Hajishirzi, Pang Wei Koh, Jesse Dodge, Pradeep Dasigi:
Merge to Learn: Efficiently Adding Skills to Language Models with Model Merging. CoRR abs/2410.12937 (2024) - 2023
- [c26]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: 12076-12100 - [c25]Irena Gao, Shiori Sagawa, Pang Wei Koh, Tatsunori Hashimoto, Percy Liang:
Out-of-Domain Robustness via Targeted Augmentations. ICML 2023: 10800-10834 - [c24]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 - [c23]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 - [c22]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 - [i29]Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn:
Leveraging Domain Relations for Domain Generalization. CoRR abs/2302.02609 (2023) - [i28]Irena Gao, Shiori Sagawa, Pang Wei Koh, Tatsunori Hashimoto, Percy Liang:
Out-of-Domain Robustness via Targeted Augmentations. CoRR abs/2302.11861 (2023) - [i27]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 abs/2304.14108 (2023) - [i26]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 abs/2305.12224 (2023) - [i25]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 abs/2305.14251 (2023) - [i24]Miao Xiong, Ailin Deng, Pang Wei Koh, Jiaying Wu, Shen Li, Jianqing Xu, Bryan Hooi:
Proximity-Informed Calibration for Deep Neural Networks. CoRR abs/2306.04590 (2023) - [i23]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 abs/2306.15447 (2023) - [i22]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 abs/2308.01390 (2023) - [i21]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". CoRR abs/2311.00059 (2023) - [i20]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 abs/2312.14804 (2023) - 2022
- [j3]Pang Wei Koh
Stronger data poisoning attacks break data sanitization defenses. Mach. Learn. 111(1): 1-47 (2022) - [c21]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
Extending the WILDS Benchmark for Unsupervised Adaptation. ICLR 2022 - [c20]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 - [i19]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 abs/2211.14238 (2022) - [i18]Blair L. Bilodeau, Natasha Jaques, Pang Wei Koh, Been Kim:
Impossibility Theorems for Feature Attribution. CoRR abs/2212.11870 (2022) - 2021
- [j2]Serina Chang
Mobility network models of COVID-19 explain inequities and inform reopening. Nat. 589(7840): 82-87 (2021) - [c19]Erik Jones, Shiori Sagawa, Pang Wei Koh, Ananya Kumar, Percy Liang:
Selective Classification Can Magnify Disparities Across Groups. ICLR 2021 - [c18]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 S. 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: 5637-5664 - [c17]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: 6781-6792 - [c16]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. ICML 2021: 7721-7735 - [c15]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 V. Marathe, Jure Leskovec
Supporting COVID-19 Policy Response with Large-scale Mobility-based Modeling. KDD 2021: 2632-2642 - [i17]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 abs/2107.04649 (2021) - [i16]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 abs/2107.09044 (2021) - [i15]Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ B. 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 E. 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 abs/2108.07258 (2021) - [i14]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 abs/2112.05090 (2021) - 2020
- [c14]Shikhar Murty, Pang Wei Koh, Percy Liang:
ExpBERT: Representation Engineering with Natural Language Explanations. ACL 2020: 2106-2113 - [c13]Shiori Sagawa, Pang Wei Koh, Tatsunori B. Hashimoto, Percy Liang:
Distributionally Robust Neural Networks. ICLR 2020 - [c12]Pang Wei Koh, Thao Nguyen, Yew Siang Tang, Stephen Mussmann, Emma Pierson, Been Kim, Percy Liang:
Concept Bottleneck Models. ICML 2020: 5338-5348 - [c11]Shiori Sagawa, Aditi Raghunathan, Pang Wei Koh, Percy Liang:
An Investigation of Why Overparameterization Exacerbates Spurious Correlations. ICML 2020: 8346-8356 - [i13]Miles Brundage, Shahar Avin, Jasmine Wang, Haydn Belfield
Toward Trustworthy AI Development: Mechanisms for Supporting Verifiable Claims. CoRR abs/2004.07213 (2020) - [i12]Shikhar Murty, Pang Wei Koh, Percy Liang:
ExpBERT: Representation Engineering with Natural Language Explanations. CoRR abs/2005.01932 (2020) - [i11]Shiori Sagawa, Aditi Raghunathan, Pang Wei Koh, Percy Liang:
An Investigation of Why Overparameterization Exacerbates Spurious Correlations. CoRR abs/2005.04345 (2020) - [i10]Pang Wei Koh, Thao Nguyen, Yew Siang Tang, Stephen Mussmann, Emma Pierson, Been Kim, Percy Liang:
Concept Bottleneck Models. CoRR abs/2007.04612 (2020) - [i9]Erik Jones, Shiori Sagawa, Pang Wei Koh, Ananya Kumar, Percy Liang:
Selective Classification Can Magnify Disparities Across Groups. CoRR abs/2010.14134 (2020) - [i8]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 abs/2012.07421 (2020)
2010 – 2019
- 2019
- [c10]Pang Wei Koh:
Identifying and exploiting influential training examples. AAAI Spring Symposium: Interpretable AI for Well-being 2019 - [c9]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: 97-107 - [c8]Pang Wei Koh, Kai-Siang Ang, Hubert H. K. Teo, Percy Liang:
On the Accuracy of Influence Functions for Measuring Group Effects. NeurIPS 2019: 5255-5265 - [c7]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: 10287-10298 - [i7]Pang Wei Koh, Kai-Siang Ang, Hubert H. K. Teo, Percy Liang:
On the Accuracy of Influence Functions for Measuring Group Effects. CoRR abs/1905.13289 (2019) - [i6]Sawyer Birnbaum, Volodymyr Kuleshov, S. Zayd Enam, Pang Wei Koh, Stefano Ermon:
Temporal FiLM: Capturing Long-Range Sequence Dependencies with Feature-Wise Modulations. CoRR abs/1909.06628 (2019) - [i5]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 abs/1911.08731 (2019) - 2018
- [i4]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 abs/1807.04709 (2018) - [i3]Pang Wei Koh, Jacob Steinhardt, Percy Liang:
Stronger Data Poisoning Attacks Break Data Sanitization Defenses. CoRR abs/1811.00741 (2018) - 2017
- [j1]Pang Wei Koh, Emma Pierson, Anshul Kundaje
Denoising genome-wide histone ChIP-seq with convolutional neural networks. Bioinform. 33(14): i225-i233 (2017) - [c6]Pang Wei Koh, Percy Liang:
Understanding Black-box Predictions via Influence Functions. ICML 2017: 1885-1894 - [c5]Jacob Steinhardt, Pang Wei Koh, Percy Liang:
Certified Defenses for Data Poisoning Attacks. NIPS 2017: 3517-3529 - [i2]Pang Wei Koh, Percy Liang:
Understanding Black-box Predictions via Influence Functions. CoRR abs/1703.04730 (2017) - [i1]Jacob Steinhardt, Pang Wei Koh, Percy Liang:
Certified Defenses for Data Poisoning Attacks. CoRR abs/1706.03691 (2017) - 2011
- [c4]Andrew M. Saxe, Pang Wei Koh, Zhenghao Chen, Maneesh Bhand, Bipin Suresh, Andrew Y. Ng:
On Random Weights and Unsupervised Feature Learning. ICML 2011: 1089-1096 - [c3]Jiquan Ngiam, Zhenghao Chen, Pang Wei Koh, Andrew Y. Ng:
Learning Deep Energy Models. ICML 2011: 1105-1112 - [c2]Jiquan Ngiam, Pang Wei Koh, Zhenghao Chen, Sonia A. Bhaskar, Andrew Y. Ng:
Sparse Filtering. NIPS 2011: 1125-1133 - 2010
- [c1]Quoc V. Le, Jiquan Ngiam, Zhenghao Chen, Daniel Jin hao Chia, Pang Wei Koh, Andrew Y. Ng:
Tiled convolutional neural networks. NIPS 2010: 1279-1287
Coauthor Index
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