Pang Wei Koh
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
31
Venues
8
Active years
2011–2025
Best venue rank
A*
Where they publish
Papers
31 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | ACL | OLMoTrace: Tracing Language Model Outputs Back to Trillions of Training Tokens. | Jiacheng Liu, Taylor Blanton, Yanai Elazar, Sewon Min, Yen-Sung Chen, Arnavi Chheda-Kothary, Huy Tran, Byron Bischoff, Eric Marsh, Michael Schmitz, Cassidy Trier, Aaron Sarnat, Jenna James, Jon Borchardt, Bailey Kuehl, Evie Yu-Yen Cheng, Karen Farley, Taira Anderson, David Albright, Carissa Schoenick, Luca Soldaini, Dirk Groeneveld, Rock Yuren Pang, Pang Wei Koh, Noah A. Smith, Sophie Lebrecht, Yejin Choi, Hannaneh Hajishirzi, Ali Farhadi, Jesse Dodge |
| 2025 | ACL | Exploring How Generative MLLMs Perceive More Than CLIP with the Same Vision Encoder. | Siting Li, Pang Wei Koh, Simon Shaolei Du |
| 2025 | CVPR | PLeaS - Merging Models with Permutations and Least Squares. | Anshul Nasery, Jonathan Hayase, Pang Wei Koh, Sewoong Oh |
| 2025 | ICLR | Group-robust Sample Reweighting for Subpopulation Shifts via Influence Functions. | Rui Qiao, Zhaoxuan Wu, Jingtan Wang, Pang Wei Koh, Bryan Kian Hsiang Low |
| 2025 | ICLR | Language models scale reliably with over-training and on downstream tasks. | Samir Yitzhak Gadre, Georgios Smyrnis, Vaishaal Shankar, Suchin Gururangan, Mitchell Wortsman, Rulin Shao, Jean Mercat, Alex Fang, Jeffrey Li, Sedrick Keh, Rui Xin, Marianna Nezhurina, Igor Vasiljevic, Luca Soldaini, Jenia Jitsev, Alex Dimakis, Gabriel Ilharco, Pang Wei Koh, Shuran Song, Thomas Kollar, et al. |
| 2025 | ICML | NICE Data Selection for Instruction Tuning in LLMs with Non-differentiable Evaluation Metric. | Jingtan Wang, Xiaoqiang Lin, Rui Qiao, Pang Wei Koh, Chuan-Sheng Foo, Bryan Kian Hsiang Low |
| 2025 | ICML | S4S: Solving for a Fast Diffusion Model Solver. | Eric Frankel, Sitan Chen, Jerry Li, Pang Wei Koh, Lillian J. Ratliff, Sewoong Oh |
| 2025 | ICML | DataDecide: How to Predict Best Pretraining Data with Small Experiments. | Ian Magnusson, Nguyen Tai, Ben Bogin, David Heineman, Jena D. Hwang, Luca Soldaini, Akshita Bhagia, Jiacheng Liu, Dirk Groeneveld, Oyvind Tafjord, Noah A. Smith, Pang Wei Koh, Jesse Dodge |
| 2024 | EMNLP | CopyBench: Measuring Literal and Non-Literal Reproduction of Copyright-Protected Text in Language Model Generation. | Tong Chen, Akari Asai, Niloofar Mireshghallah, Sewon Min, James Grimmelmann, Yejin Choi, Hannaneh Hajishirzi, Luke Zettlemoyer, Pang Wei Koh |
| 2024 | EMNLP | Merge to Learn: Efficiently Adding Skills to Language Models with Model Merging. | Jacob Morrison, Noah A. Smith, Hannaneh Hajishirzi, Pang Wei Koh, Jesse Dodge, Pradeep Dasigi |
| 2024 | EMNLP | Annotation alignment: Comparing LLM and human annotations of conversational safety. | Rajiv Movva, Pang Wei Koh, Emma Pierson |
| 2024 | EMNLP | Position Paper: Data-Centric AI in the Age of Large Language Models. | 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 |
| 2024 | ICLR | The Generative AI Paradox: "What It Can Create, It May Not Understand". | 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 |
| 2024 | ICLR | Improving Domain Generalization with Domain Relations. | Huaxiu Yao, Xinyu Yang, Xinyi Pan, Shengchao Liu, Pang Wei Koh, Chelsea Finn |
| 2024 | NAACL | Instructional Fingerprinting of Large Language Models. | Jiashu Xu, Fei Wang, Mingyu Derek Ma, Pang Wei Koh, Chaowei Xiao, Muhao Chen |
| 2023 | EMNLP | FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation. | Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Wei Koh, Mohit Iyyer, Luke Zettlemoyer, Hannaneh Hajishirzi |
| 2023 | ICML | Out-of-Domain Robustness via Targeted Augmentations. | Irena Gao, Shiori Sagawa, Pang Wei Koh, Tatsunori Hashimoto, Percy Liang |
| 2022 | ICLR | Extending the WILDS Benchmark for Unsupervised Adaptation. | 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 |
| 2021 | ICLR | Selective Classification Can Magnify Disparities Across Groups. | Erik Jones, Shiori Sagawa, Pang Wei Koh, Ananya Kumar, Percy Liang |
| 2021 | ICML | WILDS: A Benchmark of in-the-Wild Distribution Shifts. | 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 |
| 2021 | ICML | Just Train Twice: Improving Group Robustness without Training Group Information. | Evan Zheran Liu, Behzad Haghgoo, Annie S. Chen, Aditi Raghunathan, Pang Wei Koh, Shiori Sagawa, Percy Liang, Chelsea Finn |
| 2021 | ICML | Accuracy on the Line: on the Strong Correlation Between Out-of-Distribution and In-Distribution Generalization. | John Miller, Rohan Taori, Aditi Raghunathan, Shiori Sagawa, Pang Wei Koh, Vaishaal Shankar, Percy Liang, Yair Carmon, Ludwig Schmidt |
| 2021 | KDD | Supporting COVID-19 Policy Response with Large-scale Mobility-based Modeling. | 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 |
| 2020 | ACL | ExpBERT: Representation Engineering with Natural Language Explanations. | Shikhar Murty, Pang Wei Koh, Percy Liang |
| 2020 | ICLR | Distributionally Robust Neural Networks. | Shiori Sagawa, Pang Wei Koh, Tatsunori B. Hashimoto, Percy Liang |
| 2020 | ICML | Concept Bottleneck Models. | Pang Wei Koh, Thao Nguyen, Yew Siang Tang, Stephen Mussmann, Emma Pierson, Been Kim, Percy Liang |
| 2020 | ICML | An Investigation of Why Overparameterization Exacerbates Spurious Correlations. | Shiori Sagawa, Aditi Raghunathan, Pang Wei Koh, Percy Liang |
| 2019 | AISTATS | Inferring Multidimensional Rates of Aging from Cross-Sectional Data. | Emma Pierson, Pang Wei Koh, Tatsunori B. Hashimoto, Daphne Koller, Jure Leskovec, Nick Eriksson, Percy Liang |
| 2017 | ICML | Understanding Black-box Predictions via Influence Functions. | Pang Wei Koh, Percy Liang |
| 2011 | ICML | Learning Deep Energy Models. | Jiquan Ngiam, Zhenghao Chen, Pang Wei Koh, Andrew Y. Ng |
| 2011 | ICML | On Random Weights and Unsupervised Feature Learning. | Andrew M. Saxe, Pang Wei Koh, Zhenghao Chen, Maneesh Bhand, Bipin Suresh, Andrew Y. Ng |