Sewon Min

According to our database1, Sewon Min authored at least 43 papers between 2017 and 2024.

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Bibliography

2024
Do Membership Inference Attacks Work on Large Language Models?
CoRR, 2024

Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens.
CoRR, 2024

2023
In-Context Pretraining: Language Modeling Beyond Document Boundaries.
CoRR, 2023

BTR: Binary Token Representations for Efficient Retrieval Augmented Language Models.
CoRR, 2023

SILO Language Models: Isolating Legal Risk In a Nonparametric Datastore.
CoRR, 2023

REPLUG: Retrieval-Augmented Black-Box Language Models.
CoRR, 2023

Measuring and Narrowing the Compositionality Gap in Language Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

FActScore: Fine-grained Atomic Evaluation of Factual Precision in Long Form Text Generation.
Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Retrieval-based Language Models and Applications.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics: Tutorial Abstracts, 2023

Towards Understanding Chain-of-Thought Prompting: An Empirical Study of What Matters.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

Nonparametric Masked Language Modeling.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

Z-ICL: Zero-Shot In-Context Learning with Pseudo-Demonstrations.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

CREPE: Open-Domain Question Answering with False Presuppositions.
Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022
INSCIT: Information-Seeking Conversations with Mixed-Initiative Interactions.
CoRR, 2022

Revisiting Calibration for Question Answering.
CoRR, 2022

MetaICL: Learning to Learn In Context.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Prompt Waywardness: The Curious Case of Discretized Interpretation of Continuous Prompts.
Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2022

Re-Examining Calibration: The Case of Question Answering.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

Rethinking the Role of Demonstrations: What Makes In-Context Learning Work?
Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

Exploring The Landscape of Distributional Robustness for Question Answering Models.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

FaVIQ: FAct Verification from Information-seeking Questions.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Noisy Channel Language Model Prompting for Few-Shot Text Classification.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2022

Zero- and Few-Shot NLP with Pretrained Language Models.
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 2022

2021
PROMPT WAYWARDNESS: The Curious Case of Discretized Interpretation of Continuous Prompts.
CoRR, 2021

RECONSIDER: Improved Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answering.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Joint Passage Ranking for Diverse Multi-Answer Retrieval.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

2020
RECONSIDER: Re-Ranking using Span-Focused Cross-Attention for Open Domain Question Answering.
CoRR, 2020

Dense Passage Retrieval for Open-Domain Question Answering.
CoRR, 2020


AmbigQA: Answering Ambiguous Open-domain Questions.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

Efficient One-Pass End-to-End Entity Linking for Questions.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

UnifiedQA: Crossing Format Boundaries With a Single QA System.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Dense Passage Retrieval for Open-Domain Question Answering.
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019
Knowledge Guided Text Retrieval and Reading for Open Domain Question Answering.
CoRR, 2019

Question Answering is a Format; When is it Useful?
CoRR, 2019

A Discrete Hard EM Approach for Weakly Supervised Question Answering.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

Multi-hop Reading Comprehension through Question Decomposition and Rescoring.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

Compositional Questions Do Not Necessitate Multi-hop Reasoning.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

On Making Reading Comprehension More Comprehensive.
Proceedings of the 2nd Workshop on Machine Reading for Question Answering, 2019

2018
Neural Speed Reading via Skim-RNN.
Proceedings of the 6th International Conference on Learning Representations, 2018

Efficient and Robust Question Answering from Minimal Context over Documents.
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, 2018

2017
Query-Reduction Networks for Question Answering.
Proceedings of the 5th International Conference on Learning Representations, 2017

Question Answering through Transfer Learning from Large Fine-grained Supervision Data.
Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017


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