Dan Friedman

According to our database, Dan Friedman authored at least 18 papers between 1990 and 2024.

Collaborative distances:

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

2024

Continual Memorization of Factoids in Large Language Models.

Howard Chen, Jiayi Geng, Adithya Bhaskar, Dan Friedman, Danqi Chen

CoRR, 2024

When a language model is optimized for reasoning, does it still show embers of autoregression? An analysis of OpenAI o1.

R. Thomas McCoy, Shunyu Yao, Dan Friedman, Mathew D. Hardy, Thomas L. Griffiths

CoRR, 2024

Representing Rule-based Chatbots with Transformers.

Dan Friedman, Abhishek Panigrahi, Danqi Chen

CoRR, 2024

Finding Transformer Circuits with Edge Pruning.

Adithya Bhaskar, Alexander Wettig, Dan Friedman, Danqi Chen

CoRR, 2024

Interpretability Illusions in the Generalization of Simplified Models.

Dan Friedman, Andrew Kyle Lampinen, Lucas Dixon, Danqi Chen, Asma Ghandeharioun

Proceedings of the Forty-first International Conference on Machine Learning, 2024

The Heuristic Core: Understanding Subnetwork Generalization in Pretrained Language Models.

Adithya Bhaskar, Dan Friedman, Danqi Chen

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

The Vendi Score: A Diversity Evaluation Metric for Machine Learning.

Dan Friedman, Adji Bousso Dieng

Trans. Mach. Learn. Res., 2023

Embers of Autoregression: Understanding Large Language Models Through the Problem They are Trained to Solve.

R. Thomas McCoy, Shunyu Yao, Dan Friedman, Matthew Hardy, Thomas L. Griffiths

CoRR, 2023

Learning Transformer Programs.

Dan Friedman, Alexander Wettig, Danqi Chen

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Measuring Inductive Biases of In-Context Learning with Underspecified Demonstrations.

Chenglei Si, Dan Friedman, Nitish Joshi, Shi Feng, Danqi Chen, He He

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

2022

Finding Dataset Shortcuts with Grammar Induction.

Dan Friedman, Alexander Wettig, Danqi Chen

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

Factual Probing Is [MASK]: Learning vs. Learning to Recall.

Zexuan Zhong, Dan Friedman, Danqi Chen

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

Single-dataset Experts for Multi-dataset Question Answering.

Dan Friedman, Ben Dodge, Danqi Chen

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

2019

Syntax-aware Neural Semantic Role Labeling with Supertags.

Jungo Kasai, Dan Friedman, Robert Frank, Dragomir R. Radev, Owen Rambow

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

ScisummNet: A Large Annotated Corpus and Content-Impact Models for Scientific Paper Summarization with Citation Networks.

Michihiro Yasunaga, Jungo Kasai, Rui Zhang, Alexander R. Fabbri, Irene Li, Dan Friedman, Dragomir R. Radev

Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2017

Deep density networks and uncertainty in recommender systems.

Yoel Zeldes, Stavros Theodorakis, Efrat Solodnik, Aviv Rotman, Gil Chamiel, Dan Friedman

CoRR, 2017

Linguistically Rich Vector Representations of Supertags for TAG Parsing.

Dan Friedman, Jungo Kasai, R. Thomas McCoy, Robert Frank, Forrest Davis, Owen Rambow

Proceedings of the 13th International Workshop on Tree Adjoining Grammars and Related Formalisms, 2017

1990

Congestion control in BBN packet-switched networks.

J. Robinson, Dan Friedman, Martha Steenstrup

Comput. Commun. Rev., 1990