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2020 – today
- 2024
[c40]Johnny Tian-Zheng Wei, Ryan Yixiang Wang, Robin Jia:
Proving membership in LLM pretraining data via data watermarks. ACL (Findings) 2024: 13306-13320- [c39]Ting-Yun Chang, Jesse Thomason, Robin Jia:
Do Localization Methods Actually Localize Memorized Data in LLMs? A Tale of Two Benchmarks. NAACL-HLT 2024: 3190-3211 - [c38]Wang Zhu, Alekh Agarwal, Mandar Joshi, Robin Jia, Jesse Thomason, Kristina Toutanova:
Efficient End-to-End Visual Document Understanding with Rationale Distillation. NAACL-HLT 2024: 8401-8424 - [i46]Johnny Tian-Zheng Wei, Ryan Yixiang Wang, Robin Jia:
Proving membership in LLM pretraining data via data watermarks. CoRR abs/2402.10892 (2024) - [i45]Deqing Fu, Ghazal Khalighinejad, Ollie Liu, Bhuwan Dhingra, Dani Yogatama, Robin Jia, Willie Neiswanger:
IsoBench: Benchmarking Multimodal Foundation Models on Isomorphic Representations. CoRR abs/2404.01266 (2024) - [i44]Wang Zhu, Ishika Singh, Robin Jia, Jesse Thomason:
Language Models can Infer Action Semantics for Classical Planners from Environment Feedback. CoRR abs/2406.02791 (2024) - [i43]Tianyi Zhou, Deqing Fu, Vatsal Sharan, Robin Jia:
Pre-trained Large Language Models Use Fourier Features to Compute Addition. CoRR abs/2406.03445 (2024) - [i42]Ting-Yun Chang, Jesse Thomason, Robin Jia:
When Parts are Greater Than Sums: Individual LLM Components Can Outperform Full Models. CoRR abs/2406.13131 (2024) - [i41]Jun Yan, Wenjie Jacky Mo, Xiang Ren, Robin Jia:
Rethinking Backdoor Detection Evaluation for Language Models. CoRR abs/2409.00399 (2024) - 2023
- [c37]Nelson F. Liu, Ananya Kumar, Percy Liang, Robin Jia
:
Are Sample-Efficient NLP Models More Robust? ACL (2) 2023: 1689-1709 - [c36]Ting-Yun Chang, Robin Jia:
Data Curation Alone Can Stabilize In-context Learning. ACL (1) 2023: 8123-8144 - [c35]Albert Xu, Xiang Ren, Robin Jia:
Contrastive Novelty-Augmented Learning: Anticipating Outliers with Large Language Models. ACL (1) 2023: 11778-11801 - [c34]Nelson F. Liu, Tony Lee, Robin Jia, Percy Liang:
Do Question Answering Modeling Improvements Hold Across Benchmarks? ACL (1) 2023: 13186-13218 - [c33]Ameya Godbole, Robin Jia:
Benchmarking Long-tail Generalization with Likelihood Splits. EACL (Findings) 2023: 933-953 - [c32]Qinyuan Ye, Harvey Yiyun Fu, Xiang Ren, Robin Jia:
How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench. EMNLP (Findings) 2023: 7493-7517 - [c31]Deqing Fu, Ameya Godbole, Robin Jia:
SCENE: Self-Labeled Counterfactuals for Extrapolating to Negative Examples. EMNLP 2023: 7832-7848 - [c30]Wang Zhu, Jesse Thomason, Robin Jia:
Chain-of-Questions Training with Latent Answers for Robust Multistep Question Answering. EMNLP 2023: 8845-8860 - [c29]Harvey Yiyun Fu, Qinyuan Ye, Albert Xu, Xiang Ren, Robin Jia:
Estimating Large Language Model Capabilities without Labeled Test Data. EMNLP (Findings) 2023: 9530-9546 - [i40]Deqing Fu, Ameya Godbole, Robin Jia:
SCENE: Self-Labeled Counterfactuals for Extrapolating to Negative Examples. CoRR abs/2305.07984 (2023) - [i39]Johnny Tian-Zheng Wei, Frederike Zufall, Robin Jia:
Operationalizing content moderation "accuracy" in the Digital Services Act. CoRR abs/2305.09601 (2023) - [i38]Harvey Yiyun Fu, Qinyuan Ye, Albert Xu, Xiang Ren, Robin Jia:
Estimating Large Language Model Capabilities without Labeled Test Data. CoRR abs/2305.14802 (2023) - [i37]Wang Zhu, Jesse Thomason, Robin Jia:
Chain-of-Questions Training with Latent Answers for Robust Multistep Question Answering. CoRR abs/2305.14901 (2023) - [i36]Qinyuan Ye, Harvey Yiyun Fu, Xiang Ren, Robin Jia:
How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench. CoRR abs/2305.14947 (2023) - [i35]Deqing Fu, Tian-Qi Chen, Robin Jia, Vatsal Sharan:
Transformers Learn Higher-Order Optimization Methods for In-Context Learning: A Study with Linear Models. CoRR abs/2310.17086 (2023) - [i34]Ting-Yun Chang, Jesse Thomason, Robin Jia:
Do Localization Methods Actually Localize Memorized Data in LLMs? CoRR abs/2311.09060 (2023) - [i33]Wang Zhu, Alekh Agarwal, Mandar Joshi, Robin Jia, Jesse Thomason, Kristina Toutanova:
Efficient End-to-End Visual Document Understanding with Rationale Distillation. CoRR abs/2311.09612 (2023) - [i32]Wang Zhu, Ishika Singh, Yuan Huang, Robin Jia, Jesse Thomason:
Does VLN Pretraining Work with Nonsensical or Irrelevant Instructions? CoRR abs/2311.17280 (2023) - 2022
- [c28]Eric Wallace, Adina Williams, Robin Jia, Douwe Kiela:
Analyzing Dynamic Adversarial Training Data in the Limit. ACL (Findings) 2022: 202-217 - [c27]Robin Jia, Mike Lewis, Luke Zettlemoyer:
Question Answering Infused Pre-training of General-Purpose Contextualized Representations. ACL (Findings) 2022: 711-728 - [c26]Bill Yuchen Lin, Sida Wang, Xi Victoria Lin, Robin Jia, Lin Xiao, Xiang Ren, Scott Yih:
On Continual Model Refinement in Out-of-Distribution Data Streams. ACL (1) 2022: 3128-3139 - [c25]Wang Zhu, Jesse Thomason, Robin Jia:
Generalization Differences between End-to-End and Neuro-Symbolic Vision-Language Reasoning Systems. EMNLP (Findings) 2022: 4697-4711 - [c24]Rajarshi Das, Ameya Godbole, Ankita Naik, Elliot Tower, Manzil Zaheer, Hannaneh Hajishirzi, Robin Jia, Andrew McCallum:
Knowledge Base Question Answering by Case-based Reasoning over Subgraphs. ICML 2022: 4777-4793 - [c23]Jun Yan, Yang Xiao, Sagnik Mukherjee, Bill Yuchen Lin, Robin Jia, Xiang Ren:
On the Robustness of Reading Comprehension Models to Entity Renaming. NAACL-HLT 2022: 508-520 - [c22]Max Bartolo, Tristan Thrush, Sebastian Riedel, Pontus Stenetorp, Robin Jia, Douwe Kiela:
Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants. NAACL-HLT 2022: 3754-3767 - [i31]Rajarshi Das, Ameya Godbole, Ankita Naik, Elliot Tower, Robin Jia, Manzil Zaheer, Hannaneh Hajishirzi, Andrew McCallum:
Knowledge Base Question Answering by Case-based Reasoning over Subgraphs. CoRR abs/2202.10610 (2022) - [i30]Bill Yuchen Lin, Sida Wang, Xi Victoria Lin, Robin Jia, Lin Xiao, Xiang Ren, Wen-tau Yih:
On Continual Model Refinement in Out-of-Distribution Data Streams. CoRR abs/2205.02014 (2022) - [i29]Nelson F. Liu, Ananya Kumar, Percy Liang, Robin Jia:
Are Sample-Efficient NLP Models More Robust? CoRR abs/2210.06456 (2022) - [i28]Ameya Godbole, Robin Jia:
Benchmarking Long-tail Generalization with Likelihood Splits. CoRR abs/2210.06799 (2022) - [i27]Wang Zhu, Jesse Thomason, Robin Jia:
Generalization Differences between End-to-End and Neuro-Symbolic Vision-Language Reasoning Systems. CoRR abs/2210.15037 (2022) - [i26]Albert Xu, Xiang Ren, Robin Jia:
CoNAL: Anticipating Outliers with Large Language Models. CoRR abs/2211.15718 (2022) - [i25]Ting-Yun Chang, Robin Jia:
Careful Data Curation Stabilizes In-context Learning. CoRR abs/2212.10378 (2022) - 2021
- [c21]Ana Valeria Gonzalez, Gagan Bansal, Angela Fan, Yashar Mehdad, Robin Jia, Srinivasan Iyer:
Do Explanations Help Users Detect Errors in Open-Domain QA? An Evaluation of Spoken vs. Visual Explanations. ACL/IJCNLP (Findings) 2021: 1103-1116 - [c20]Pedro Rodriguez, Joe Barrow, Alexander Miserlis Hoyle, John P. Lalor, Robin Jia, Jordan L. Boyd-Graber:
Evaluation Examples are not Equally Informative: How should that change NLP Leaderboards? ACL/IJCNLP (1) 2021: 4486-4503 - [c19]Johnny Tian-Zheng Wei, Robin Jia:
The statistical advantage of automatic NLG metrics at the system level. ACL/IJCNLP (1) 2021: 6840-6854 - [c18]Grusha Prasad, Yixin Nie, Mohit Bansal, Robin Jia, Douwe Kiela, Adina Williams:
To what extent do human explanations of model behavior align with actual model behavior? BlackboxNLP@EMNLP 2021: 1-14 - [c17]Koustuv Sinha, Robin Jia, Dieuwke Hupkes, Joelle Pineau, Adina Williams, Douwe Kiela:
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little. EMNLP (1) 2021: 2888-2913 - [c16]Max Bartolo, Tristan Thrush, Robin Jia, Sebastian Riedel, Pontus Stenetorp, Douwe Kiela:
Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation. EMNLP (1) 2021: 8830-8848 - [c15]Douwe Kiela, Max Bartolo, Yixin Nie, Divyansh Kaushik, Atticus Geiger, Zhengxuan Wu, Bertie Vidgen, Grusha Prasad, Amanpreet Singh, Pratik Ringshia, Zhiyi Ma, Tristan Thrush, Sebastian Riedel, Zeerak Waseem, Pontus Stenetorp, Robin Jia, Mohit Bansal, Christopher Potts, Adina Williams:
Dynabench: Rethinking Benchmarking in NLP. NAACL-HLT 2021: 4110-4124 - [c14]Mina Lee, Chris Donahue, Robin Jia, Alexander Iyabor, Percy Liang:
Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality. NAACL-HLT 2021: 4362-4379 - [c13]Zhiyi Ma, Kawin Ethayarajh, Tristan Thrush, Somya Jain, Ledell Wu, Robin Jia, Christopher Potts, Adina Williams, Douwe Kiela:
Dynaboard: An Evaluation-As-A-Service Platform for Holistic Next-Generation Benchmarking. NeurIPS 2021: 10351-10367 - [i24]Nelson F. Liu, Tony Lee, Robin Jia, Percy Liang:
Can Small and Synthetic Benchmarks Drive Modeling Innovation? A Retrospective Study of Question Answering Modeling Approaches. CoRR abs/2102.01065 (2021) - [i23]Koustuv Sinha, Robin Jia, Dieuwke Hupkes, Joelle Pineau, Adina Williams, Douwe Kiela:
Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little. CoRR abs/2104.06644 (2021) - [i22]Max Bartolo, Tristan Thrush, Robin Jia, Sebastian Riedel, Pontus Stenetorp, Douwe Kiela:
Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation. CoRR abs/2104.08678 (2021) - [i21]Douwe Kiela, Max Bartolo, Yixin Nie, Divyansh Kaushik, Atticus Geiger, Zhengxuan Wu, Bertie Vidgen, Grusha Prasad, Amanpreet Singh, Pratik Ringshia, Zhiyi Ma, Tristan Thrush, Sebastian Riedel, Zeerak Waseem, Pontus Stenetorp, Robin Jia, Mohit Bansal, Christopher Potts, Adina Williams:
Dynabench: Rethinking Benchmarking in NLP. CoRR abs/2104.14337 (2021) - [i20]Johnny Tian-Zheng Wei, Robin Jia:
The statistical advantage of automatic NLG metrics at the system level. CoRR abs/2105.12437 (2021) - [i19]Mina Lee, Chris Donahue, Robin Jia, Alexander Iyabor, Percy Liang:
Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality. CoRR abs/2106.04102 (2021) - [i18]Zhiyi Ma, Kawin Ethayarajh, Tristan Thrush, Somya Jain, Ledell Wu, Robin Jia, Christopher Potts, Adina Williams, Douwe Kiela:
Dynaboard: An Evaluation-As-A-Service Platform for Holistic Next-Generation Benchmarking. CoRR abs/2106.06052 (2021) - [i17]Robin Jia, Mike Lewis, Luke Zettlemoyer:
Question Answering Infused Pre-training of General-Purpose Contextualized Representations. CoRR abs/2106.08190 (2021) - [i16]Eric Wallace, Adina Williams, Robin Jia, Douwe Kiela:
Analyzing Dynamic Adversarial Training Data in the Limit. CoRR abs/2110.08514 (2021) - [i15]Jun Yan, Yang Xiao, Sagnik Mukherjee, Bill Yuchen Lin, Robin Jia, Xiang Ren:
On the Robustness of Reading Comprehension Models to Entity Renaming. CoRR abs/2110.08555 (2021) - [i14]Max Bartolo, Tristan Thrush, Sebastian Riedel, Pontus Stenetorp, Robin Jia, Douwe Kiela:
Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants. CoRR abs/2112.09062 (2021) - 2020
- [b1]Robin Jia:
Building robust natural language processing systems. Stanford University, USA, 2020 - [c12]Erik Jones, Robin Jia, Aditi Raghunathan, Percy Liang:
Robust Encodings: A Framework for Combating Adversarial Typos. ACL 2020: 2752-2765 - [c11]Amita Kamath, Robin Jia, Percy Liang:
Selective Question Answering under Domain Shift. ACL 2020: 5684-5696 - [c10]Stephen Mussmann, Robin Jia, Percy Liang:
On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks. EMNLP (Findings) 2020: 3400-3413 - [c9]Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald, Dan Jurafsky:
With Little Power Comes Great Responsibility. EMNLP (1) 2020: 9263-9274 - [i13]Erik Jones, Robin Jia, Aditi Raghunathan, Percy Liang:
Robust Encodings: A Framework for Combating Adversarial Typos. CoRR abs/2005.01229 (2020) - [i12]Amita Kamath, Robin Jia, Percy Liang:
Selective Question Answering under Domain Shift. CoRR abs/2006.09462 (2020) - [i11]Stephen Mussmann, Robin Jia, Percy Liang:
On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks. CoRR abs/2010.05103 (2020) - [i10]Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald, Dan Jurafsky:
With Little Power Comes Great Responsibility. CoRR abs/2010.06595 (2020) - [i9]Grusha Prasad, Yixin Nie, Mohit Bansal, Robin Jia, Douwe Kiela, Adina Williams:
To what extent do human explanations of model behavior align with actual model behavior? CoRR abs/2012.13354 (2020) - [i8]Ana Valeria Gonzalez, Gagan Bansal, Angela Fan, Robin Jia, Yashar Mehdad, Srinivasan Iyer:
Human Evaluation of Spoken vs. Visual Explanations for Open-Domain QA. CoRR abs/2012.15075 (2020)
2010 – 2019
- 2019
- [c8]Adam Fisch, Alon Talmor, Robin Jia, Minjoon Seo, Eunsol Choi, Danqi Chen:
MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension. MRQA@EMNLP 2019: 1-13 - [c7]Robin Jia, Aditi Raghunathan, Kerem Göksel, Percy Liang:
Certified Robustness to Adversarial Word Substitutions. EMNLP/IJCNLP (1) 2019: 4127-4140 - [c6]Robin Jia, Cliff Wong, Hoifung Poon:
Document-Level N-ary Relation Extraction with Multiscale Representation Learning. NAACL-HLT (1) 2019: 3693-3704 - [e2]Adam Fisch, Alon Talmor, Robin Jia, Minjoon Seo, Eunsol Choi, Danqi Chen:
Proceedings of the 2nd Workshop on Machine Reading for Question Answering, MRQA@EMNLP 2019, Hong Kong, China, November 4, 2019. Association for Computational Linguistics 2019, ISBN 978-1-950737-81-9 [contents] - [i7]Robin Jia, Cliff Wong, Hoifung Poon:
Document-Level N-ary Relation Extraction with Multiscale Representation Learning. CoRR abs/1904.02347 (2019) - [i6]Robin Jia, Aditi Raghunathan, Kerem Göksel, Percy Liang:
Certified Robustness to Adversarial Word Substitutions. CoRR abs/1909.00986 (2019) - [i5]Adam Fisch, Alon Talmor, Robin Jia, Minjoon Seo, Eunsol Choi, Danqi Chen:
MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension. CoRR abs/1910.09753 (2019) - 2018
- [c5]Pranav Rajpurkar, Robin Jia, Percy Liang:
Know What You Don't Know: Unanswerable Questions for SQuAD. ACL (2) 2018: 784-789 - [c4]Juncen Li, Robin Jia, He He, Percy Liang:
Delete, Retrieve, Generate: a Simple Approach to Sentiment and Style Transfer. NAACL-HLT 2018: 1865-1874 - [e1]Eunsol Choi, Minjoon Seo, Danqi Chen, Robin Jia, Jonathan Berant:
Proceedings of the Workshop on Machine Reading for Question Answering@ACL 2018, Melbourne, Australia, July 19, 2018. Association for Computational Linguistics 2018, ISBN 978-1-948087-39-1 [contents] - [i4]Juncen Li, Robin Jia, He He, Percy Liang:
Delete, Retrieve, Generate: A Simple Approach to Sentiment and Style Transfer. CoRR abs/1804.06437 (2018) - [i3]Pranav Rajpurkar, Robin Jia, Percy Liang:
Know What You Don't Know: Unanswerable Questions for SQuAD. CoRR abs/1806.03822 (2018) - 2017
- [c3]Robin Jia, Percy Liang:
Adversarial Examples for Evaluating Reading Comprehension Systems. EMNLP 2017: 2021-2031 - [c2]Robin Jia, Larry P. Heck, Dilek Hakkani-Tür, Georgi Nikolov:
Learning concepts through conversations in spoken dialogue systems. ICASSP 2017: 5725-5729 - [i2]Robin Jia, Percy Liang:
Adversarial Examples for Evaluating Reading Comprehension Systems. CoRR abs/1707.07328 (2017) - 2016
- [c1]Robin Jia, Percy Liang:
Data Recombination for Neural Semantic Parsing. ACL (1) 2016 - [i1]Robin Jia, Percy Liang:
Data Recombination for Neural Semantic Parsing. CoRR abs/1606.03622 (2016)
Coauthor Index
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