Yanai Elazar
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
27
Venues
7
Active years
2018–2025
Best venue rank
A*
Where they publish
Papers
27 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2025 | AAAI | Calibrating Large Language Models with Sample Consistency. | Qing Lyu, Kumar Shridhar, Chaitanya Malaviya, Li Zhang, Yanai Elazar, Niket Tandon, Marianna Apidianaki, Mrinmaya Sachan, Chris Callison-Burch |
| 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 | Hybrid Preferences: Learning to Route Instances for Human vs. AI Feedback. | Lester James Validad Miranda, Yizhong Wang, Yanai Elazar, Sachin Kumar, Valentina Pyatkin, Faeze Brahman, Noah A. Smith, Hannaneh Hajishirzi, Pradeep Dasigi |
| 2025 | ICLR | Generalization v.s. Memorization: Tracing Language Models' Capabilities Back to Pretraining Data. | Xinyi Wang, Antonis Antoniades, Yanai Elazar, Alfonso Amayuelas, Alon Albalak, Kexun Zhang, William Yang Wang |
| 2025 | ICLR | On Linear Representations and Pretraining Data Frequency in Language Models. | Jack Merullo, Noah A. Smith, Sarah Wiegreffe, Yanai Elazar |
| 2024 | ACL | OLMo: Accelerating the Science of Language Models. | Dirk Groeneveld, Iz Beltagy, Evan Pete Walsh, Akshita Bhagia, Rodney Kinney, Oyvind Tafjord, Ananya Harsh Jha, Hamish Ivison, Ian Magnusson, Yizhong Wang, Shane Arora, David Atkinson, Russell Authur, Khyathi Raghavi Chandu, Arman Cohan, Jennifer Dumas, Yanai Elazar, Yuling Gu, Jack Hessel, Tushar Khot, William Merrill, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Valentina Pyatkin, Abhilasha Ravichander, Dustin Schwenk, Saurabh Shah, Will Smith, Emma Strubell, Nishant Subramani, Mitchell Wortsman, Pradeep Dasigi, Nathan Lambert, Kyle Richardson, Luke Zettlemoyer, Jesse Dodge, Kyle Lo, Luca Soldaini, Noah A. Smith, Hannaneh Hajishirzi |
| 2024 | ACL | Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research. | Luca Soldaini, Rodney Kinney, Akshita Bhagia, Dustin Schwenk, David Atkinson, Russell Authur, Ben Bogin, Khyathi Raghavi Chandu, Jennifer Dumas, Yanai Elazar, Valentin Hofmann, Ananya Harsh Jha, Sachin Kumar, Li Lucy, Xinxi Lyu, Nathan Lambert, Ian Magnusson, Jacob Morrison, Niklas Muennighoff, Aakanksha Naik, Crystal Nam, Matthew E. Peters, Abhilasha Ravichander, Kyle Richardson, Zejiang Shen, Emma Strubell, Nishant Subramani, Oyvind Tafjord, Pete Walsh, Luke Zettlemoyer, Noah A. Smith, Hannaneh Hajishirzi, Iz Beltagy, Dirk Groeneveld, Jesse Dodge, Kyle Lo |
| 2024 | EMNLP | Measuring and Improving Attentiveness to Partial Inputs with Counterfactuals. | Yanai Elazar, Bhargavi Paranjape, Hao Peng, Sarah Wiegreffe, Khyathi Raghavi Chandu, Vivek Srikumar, Sameer Singh, Noah A. Smith |
| 2024 | EMNLP | Applying Intrinsic Debiasing on Downstream Tasks: Challenges and Considerations for Machine Translation. | Bar Iluz, Yanai Elazar, Asaf Yehudai, Gabriel Stanovsky |
| 2024 | EMNLP | Evaluating n-Gram Novelty of Language Models Using Rusty-DAWG. | William Merrill, Noah A. Smith, Yanai Elazar |
| 2024 | EMNLP | Detection and Measurement of Syntactic Templates in Generated Text. | Chantal Shaib, Yanai Elazar, Junyi Jessy Li, Byron C. Wallace |
| 2024 | ICLR | What's In My Big Data? | Yanai Elazar, Akshita Bhagia, Ian Magnusson, Abhilasha Ravichander, Dustin Schwenk, Alane Suhr, Evan Pete Walsh, Dirk Groeneveld, Luca Soldaini, Sameer Singh, Hannaneh Hajishirzi, Noah A. Smith, Jesse Dodge |
| 2024 | ICLR | Backtracking Mathematical Reasoning of Language Models to the Pretraining Data. | Yasaman Razeghi, Hamish Ivison, Sameer Singh, Yanai Elazar |
| 2024 | NAACL | The Bias Amplification Paradox in Text-to-Image Generation. | Preethi Seshadri, Sameer Singh, Yanai Elazar |
| 2023 | ACL | Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation. | Marius Mosbach, Tiago Pimentel, Shauli Ravfogel, Dietrich Klakow, Yanai Elazar |
| 2023 | EACL | CIKQA: Learning Commonsense Inference with a Unified Knowledge-in-the-loop QA Paradigm. | Hongming Zhang, Yintong Huo, Yanai Elazar, Yangqiu Song, Yoav Goldberg, Dan Roth |
| 2022 | EMNLP | Lexical Generalization Improves with Larger Models and Longer Training. | Elron Bandel, Yoav Goldberg, Yanai Elazar |
| 2021 | EACL | First Align, then Predict: Understanding the Cross-Lingual Ability of Multilingual BERT. | Benjamin Muller, Yanai Elazar, Benot Sagot, Djam Seddah |
| 2021 | EMNLP | Back to Square One: Artifact Detection, Training and Commonsense Disentanglement in the Winograd Schema. | Yanai Elazar, Hongming Zhang, Yoav Goldberg, Dan Roth |
| 2021 | EMNLP | Contrastive Explanations for Model Interpretability. | Alon Jacovi, Swabha Swayamdipta, Shauli Ravfogel, Yanai Elazar, Yejin Choi, Yoav Goldberg |
| 2020 | ACL | Null It Out: Guarding Protected Attributes by Iterative Nullspace Projection. | Shauli Ravfogel, Yanai Elazar, Hila Gonen, Michael Twiton, Yoav Goldberg |
| 2020 | EMNLP | Evaluating Models' Local Decision Boundaries via Contrast Sets. | Matt Gardner, Yoav Artzi, Victoria Basmova, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hannaneh Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, Ally Zhang, Ben Zhou |
| 2020 | EMNLP | Do Language Embeddings capture Scales? | Xikun Zhang, Deepak Ramachandran, Ian Tenney, Yanai Elazar, Dan Roth |
| 2019 | ACL | How Large Are Lions? Inducing Distributions over Quantitative Attributes. | Yanai Elazar, Abhijit Mahabal, Deepak Ramachandran, Tania Bedrax-Weiss, Dan Roth |
| 2019 | EMNLP | Adversarial Removal of Demographic Attributes Revisited. | Maria Barrett, Yova Kementchedjhieva, Yanai Elazar, Desmond Elliott, Anders Sgaard |
| 2019 | ICPRAM | Privacy and Fairness in Recommender Systems via Adversarial Training of User Representations. | Yehezkel S. Resheff, Yanai Elazar, Moni Shahar, Oren Sar Shalom |
| 2018 | EMNLP | Adversarial Removal of Demographic Attributes from Text Data. | Yanai Elazar, Yoav Goldberg |