Yanai Elazar

According to our database1, Yanai Elazar authored at least 49 papers between 2018 and 2024.

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Bibliography

2024
A Survey on Data Selection for Language Models.
Trans. Mach. Learn. Res., 2024

Data Contamination Report from the 2024 CONDA Shared Task.
CoRR, 2024

Generalization v.s. Memorization: Tracing Language Models' Capabilities Back to Pretraining Data.
CoRR, 2024

Detection and Measurement of Syntactic Templates in Generated Text.
CoRR, 2024

Evaluating n-Gram Novelty of Language Models Using Rusty-DAWG.
CoRR, 2024

Applying Intrinsic Debiasing on Downstream Tasks: Challenges and Considerations for Machine Translation.
CoRR, 2024

Calibrating Large Language Models with Sample Consistency.
CoRR, 2024

OLMo: Accelerating the Science of Language Models.
CoRR, 2024

Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research.
CoRR, 2024

The Bias Amplification Paradox in Text-to-Image Generation.
Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), 2024

Backtracking Mathematical Reasoning of Language Models to the Pretraining Data.
Proceedings of the Second Tiny Papers Track at ICLR 2024, 2024

What's In My Big Data?
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Estimating the Causal Effect of Early ArXiving on Paper Acceptance.
Proceedings of the Causal Learning and Reasoning, 2024



2023
A taxonomy and review of generalization research in NLP.
Nat. Mac. Intell., October, 2023

Paloma: A Benchmark for Evaluating Language Model Fit.
CoRR, 2023

Measuring and Improving Attentiveness to Partial Inputs with Counterfactuals.
CoRR, 2023

What's In My Big Data?
CoRR, 2023

At Your Fingertips: Extracting Piano Fingering Instructions from Videos.
CoRR, 2023

CIKQA: Learning Commonsense Inference with a Unified Knowledge-in-the-loop QA Paradigm.
Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation.
Proceedings of the Findings of the Association for Computational Linguistics: ACL 2023, 2023

2022
Text-based NP Enrichment.
Trans. Assoc. Comput. Linguistics, 2022

State-of-the-art generalisation research in NLP: a taxonomy and review.
CoRR, 2022

Measuring Causal Effects of Data Statistics on Language Model's 'Factual' Predictions.
CoRR, 2022

Lexical Generalization Improves with Larger Models and Longer Training.
Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021
Revisiting Few-shot Relation Classification: Evaluation Data and Classification Schemes.
Trans. Assoc. Comput. Linguistics, 2021

Amnesic Probing: Behavioral Explanation With Amnesic Counterfactuals.
Trans. Assoc. Comput. Linguistics, 2021

Erratum: Measuring and Improving Consistency in Pretrained Language Models.
Trans. Assoc. Comput. Linguistics, 2021

Measuring and Improving Consistency in Pretrained Language Models.
Trans. Assoc. Comput. Linguistics, 2021

Back to Square One: Bias Detection, Training and Commonsense Disentanglement in the Winograd Schema.
CoRR, 2021

Contrastive Explanations for Model Interpretability.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Back to Square One: Artifact Detection, Training and Commonsense Disentanglement in the Winograd Schema.
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

First Align, then Predict: Understanding the Cross-Lingual Ability of Multilingual BERT.
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume, 2021

2020
oLMpics - On what Language Model Pre-training Captures.
Trans. Assoc. Comput. Linguistics, 2020

When Bert Forgets How To POS: Amnesic Probing of Linguistic Properties and MLM Predictions.
CoRR, 2020

Evaluating NLP Models via Contrast Sets.
CoRR, 2020


Do Language Embeddings capture Scales?
Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2020

Unsupervised Distillation of Syntactic Information from Contextualized Word Representations.
Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2020

It's not Greek to mBERT: Inducing Word-Level Translations from Multilingual BERT.
Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2020

Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

The Extraordinary Failure of Complement Coercion Crowdsourcing.
Proceedings of the First Workshop on Insights from Negative Results in NLP, 2020

2019
Where's My Head? Definition, Dataset and Models for Numeric Fused-Heads Identification and Resolution.
Trans. Assoc. Comput. Linguistics, 2019

Privacy and Fairness in Recommender Systems via Adversarial Training of User Representations.
Proceedings of the 8th International Conference on Pattern Recognition Applications and Methods, 2019

Adversarial Removal of Demographic Attributes Revisited.
Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, 2019

How Large Are Lions? Inducing Distributions over Quantitative Attributes.
Proceedings of the 57th Conference of the Association for Computational Linguistics, 2019

2018
Privacy-Adversarial User Representations in Recommender Systems.
CoRR, 2018

Adversarial Removal of Demographic Attributes from Text Data.
Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, Brussels, Belgium, October 31, 2018


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