Dan Friedman
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Factual probing is [mask]: Learning vs. learning to recall
Z Zhong, D Friedman, D Chen
arXiv preprint arXiv:2104.05240, 2021
Scisummnet: A large annotated corpus and content-impact models for scientific paper summarization with citation networks
M Yasunaga, J Kasai, R Zhang, AR Fabbri, I Li, D Friedman, DR Radev
Proceedings of the AAAI conference on artificial intelligence 33 (01), 7386-7393, 2019
Embers of autoregression: Understanding large language models through the problem they are trained to solve
RT McCoy, S Yao, D Friedman, M Hardy, TL Griffiths
arXiv preprint arXiv:2309.13638, 2023
Syntax-aware neural semantic role labeling with supertags
J Kasai, D Friedman, R Frank, D Radev, O Rambow
arXiv preprint arXiv:1903.05260, 2019
The vendi score: A diversity evaluation metric for machine learning
D Dan Friedman, AB Dieng
Transactions on machine learning research, 2023
Single-dataset experts for multi-dataset question answering
D Friedman, B Dodge, D Chen
arXiv preprint arXiv:2109.13880, 2021
Measuring inductive biases of in-context learning with underspecified demonstrations
C Si, D Friedman, N Joshi, S Feng, D Chen, H He
arXiv preprint arXiv:2305.13299, 2023
Learning transformer programs
D Friedman, A Wettig, D Chen
Advances in Neural Information Processing Systems 36, 2024
Finding dataset shortcuts with grammar induction
D Friedman, A Wettig, D Chen
arXiv preprint arXiv:2210.11560, 2022
Interpretability illusions in the generalization of simplified models
D Friedman, AK Lampinen, L Dixon, D Chen, A Ghandeharioun
What Spurious Features Can Pretrained Language Models Combat?
C Si, D Friedman, N Joshi, S Feng, D Chen, H He
Linguistically rich vector representations of supertags for TAG parsing
D Friedman, J Kasai, RT McCoy, R Frank, F Davis, O Rambow
Proceedings of the 13th International Workshop on Tree Adjoining Grammars …, 2017
The Heuristic Core: Understanding Subnetwork Generalization in Pretrained Language Models
A Bhaskar, D Friedman, D Chen
arXiv preprint arXiv:2403.03942, 2024
Comparing Representational and Functional Similarity in Small Transformer Language Models
D Friedman, AK Lampinen, L Dixon, D Chen, A Ghandeharioun
UniReps: the First Workshop on Unifying Representations in Neural Models, 2023
Algorithms for Codenames
D Friedman, A Panigrahi
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