Robin Jia

According to our database, Robin Jia authored at least 48 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Proving membership in LLM pretraining data via data watermarks.

Johnny Tian-Zheng Wei, Ryan Yixiang Wang, Robin Jia

CoRR, 2024

2023

Does VLN Pretraining Work with Nonsensical or Irrelevant Instructions?

Wang Zhu, Ishika Singh, Yuan Huang, Robin Jia, Jesse Thomason

CoRR, 2023

Efficient End-to-End Visual Document Understanding with Rationale Distillation.

Wang Zhu, Alekh Agarwal, Mandar Joshi, Robin Jia, Jesse Thomason, Kristina Toutanova

CoRR, 2023

Do Localization Methods Actually Localize Memorized Data in LLMs?

Ting-Yun Chang, Jesse Thomason, Robin Jia

CoRR, 2023

Transformers Learn Higher-Order Optimization Methods for In-Context Learning: A Study with Linear Models.

Deqing Fu, Tian-Qi Chen, Robin Jia, Vatsal Sharan

CoRR, 2023

Operationalizing content moderation "accuracy" in the Digital Services Act.

Johnny Tian-Zheng Wei, Frederike Zufall, Robin Jia

CoRR, 2023

How Predictable Are Large Language Model Capabilities? A Case Study on BIG-bench.

Qinyuan Ye, Harvey Yiyun Fu, Xiang Ren, Robin Jia

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Estimating Large Language Model Capabilities without Labeled Test Data.

Harvey Yiyun Fu, Qinyuan Ye, Albert Xu, Xiang Ren, Robin Jia

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

SCENE: Self-Labeled Counterfactuals for Extrapolating to Negative Examples.

Deqing Fu, Ameya Godbole, Robin Jia

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Chain-of-Questions Training with Latent Answers for Robust Multistep Question Answering.

Wang Zhu, Jesse Thomason, Robin Jia

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Benchmarking Long-tail Generalization with Likelihood Splits.

Ameya Godbole, Robin Jia

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

Contrastive Novelty-Augmented Learning: Anticipating Outliers with Large Language Models.

Albert Xu, Xiang Ren, Robin Jia

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Do Question Answering Modeling Improvements Hold Across Benchmarks?

Nelson F. Liu, Tony Lee, Robin Jia, Percy Liang

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Are Sample-Efficient NLP Models More Robust?

Nelson F. Liu, Ananya Kumar, Percy Liang, Robin Jia

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2023

Data Curation Alone Can Stabilize In-context Learning.

Ting-Yun Chang, Robin Jia

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Careful Data Curation Stabilizes In-context Learning.

Ting-Yun Chang, Robin Jia

CoRR, 2022

CoNAL: Anticipating Outliers with Large Language Models.

Albert Xu, Xiang Ren, Robin Jia

CoRR, 2022

On the Robustness of Reading Comprehension Models to Entity Renaming.

Jun Yan, Yang Xiao, Sagnik Mukherjee, Bill Yuchen Lin, Robin Jia, Xiang Ren

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants.

Max Bartolo, Tristan Thrush, Sebastian Riedel, Pontus Stenetorp, Robin Jia, Douwe Kiela

Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Knowledge Base Question Answering by Case-based Reasoning over Subgraphs.

Rajarshi Das, Ameya Godbole, Ankita Naik, Elliot Tower, Manzil Zaheer, Hannaneh Hajishirzi, Robin Jia, Andrew McCallum

Proceedings of the International Conference on Machine Learning, 2022

Generalization Differences between End-to-End and Neuro-Symbolic Vision-Language Reasoning Systems.

Wang Zhu, Jesse Thomason, Robin Jia

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Analyzing Dynamic Adversarial Training Data in the Limit.

Eric Wallace, Adina Williams, Robin Jia, Douwe Kiela

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

On Continual Model Refinement in Out-of-Distribution Data Streams.

Bill Yuchen Lin, Sida Wang, Xi Victoria Lin, Robin Jia, Lin Xiao, Xiang Ren, Scott Yih

Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Question Answering Infused Pre-training of General-Purpose Contextualized Representations.

Robin Jia, Mike Lewis, Luke Zettlemoyer

Proceedings of the Findings of the Association for Computational Linguistics: ACL 2022, 2022

2021

Can Small and Synthetic Benchmarks Drive Modeling Innovation? A Retrospective Study of Question Answering Modeling Approaches.

Nelson F. Liu, Tony Lee, Robin Jia, Percy Liang

CoRR, 2021

Dynaboard: An Evaluation-As-A-Service Platform for Holistic Next-Generation Benchmarking.

Zhiyi Ma, Kawin Ethayarajh, Tristan Thrush, Somya Jain, Ledell Wu, Robin Jia, Christopher Potts, Adina Williams, Douwe Kiela

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Swords: A Benchmark for Lexical Substitution with Improved Data Coverage and Quality.

Mina Lee, Chris Donahue, Robin Jia, Alexander Iyabor, Percy Liang

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Dynabench: Rethinking Benchmarking in NLP.

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

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Masked Language Modeling and the Distributional Hypothesis: Order Word Matters Pre-training for Little.

Koustuv Sinha, Robin Jia, Dieuwke Hupkes, Joelle Pineau, Adina Williams, Douwe Kiela

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation.

Max Bartolo, Tristan Thrush, Robin Jia, Sebastian Riedel, Pontus Stenetorp, Douwe Kiela

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

To what extent do human explanations of model behavior align with actual model behavior?

Grusha Prasad, Yixin Nie, Mohit Bansal, Robin Jia, Douwe Kiela, Adina Williams

Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2021

The statistical advantage of automatic NLG metrics at the system level.

Johnny Tian-Zheng Wei, Robin Jia

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Evaluation Examples are not Equally Informative: How should that change NLP Leaderboards?

Pedro Rodriguez, Joe Barrow, Alexander Miserlis Hoyle, John P. Lalor, Robin Jia, Jordan L. Boyd-Graber

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

Do Explanations Help Users Detect Errors in Open-Domain QA? An Evaluation of Spoken vs. Visual Explanations.

Ana Valeria Gonzalez, Gagan Bansal, Angela Fan, Yashar Mehdad, Robin Jia, Srinivasan Iyer

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020

Building robust natural language processing systems.

Robin Jia

PhD thesis, 2020

Human Evaluation of Spoken vs. Visual Explanations for Open-Domain QA.

Ana Valeria Gonzalez, Gagan Bansal, Angela Fan, Robin Jia, Yashar Mehdad, Srinivasan Iyer

CoRR, 2020

On the Importance of Adaptive Data Collection for Extremely Imbalanced Pairwise Tasks.

Stephen Mussmann, Robin Jia, Percy Liang

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

With Little Power Comes Great Responsibility.

Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald, Dan Jurafsky

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Selective Question Answering under Domain Shift.

Amita Kamath, Robin Jia, Percy Liang

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

Robust Encodings: A Framework for Combating Adversarial Typos.

Erik Jones, Robin Jia, Aditi Raghunathan, Percy Liang

Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019

Document-Level N-ary Relation Extraction with Multiscale Representation Learning.

Robin Jia, Cliff Wong, Hoifung Poon

Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2019

Certified Robustness to Adversarial Word Substitutions.

Robin Jia, Aditi Raghunathan, Kerem Göksel, Percy Liang

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

MRQA 2019 Shared Task: Evaluating Generalization in Reading Comprehension.

Adam Fisch, Alon Talmor, Robin Jia, Minjoon Seo, Eunsol Choi, Danqi Chen

Proceedings of the 2nd Workshop on Machine Reading for Question Answering, 2019

2018

Delete, Retrieve, Generate: a Simple Approach to Sentiment and Style Transfer.

Juncen Li, Robin Jia, He He, Percy Liang

Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2018

Know What You Don't Know: Unanswerable Questions for SQuAD.

Pranav Rajpurkar, Robin Jia, Percy Liang

Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017

Learning concepts through conversations in spoken dialogue systems.

Robin Jia, Larry P. Heck, Dilek Hakkani-Tür, Georgi Nikolov

Proceedings of the 2017 IEEE International Conference on Acoustics, 2017

Adversarial Examples for Evaluating Reading Comprehension Systems.

Robin Jia, Percy Liang

Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing, 2017

2016

Data Recombination for Neural Semantic Parsing.

Robin Jia, Percy Liang

Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, 2016