activity
20172023
most citedDo We Still Need Clinical Language Models?

50 citations · 98 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CL2023★ 50 cited

Do We Still Need Clinical Language Models?

Eric Lehman, Evan Hernandez, Diwakar Mahajan +7

Although recent advances in scaling large language models (LLMs) have resulted in improvements on many NLP tasks, it remains unclear whether these models trained primarily with gen…

cs.CL2021★ 1 cited

A Generative Approach for Mitigating Structural Biases in Natural Language Inference

Dimion Asael, Zachary Ziegler, Yonatan Belinkov

Many natural language inference (NLI) datasets contain biases that allow models to perform well by only using a biased subset of the input, without considering the remainder featur…

physics.optics2019

Mechanisms of Spatiotemporal Mode-Locking

Logan G. Wright, Pavel Sidorenko, Hamed Pourbeyram +6

Mode-locking is a process in which different modes of an optical resonator establish, through nonlinear interactions, stable synchronization. This self-organization underlies light…

cs.CL2019

Encoder-Agnostic Adaptation for Conditional Language Generation

Zachary M. Ziegler, Luke Melas-Kyriazi, Sebastian Gehrmann +1

Large pretrained language models have changed the way researchers approach discriminative natural language understanding tasks, leading to the dominance of approaches that adapt a…

cs.CL2019

Neural Linguistic Steganography

Zachary M. Ziegler, Yuntian Deng, Alexander M. Rush

Whereas traditional cryptography encrypts a secret message into an unintelligible form, steganography conceals that communication is taking place by encoding a secret message into…

stat.ML2019★ 46 cited

Latent Normalizing Flows for Discrete Sequences

Zachary M. Ziegler, Alexander M. Rush

Normalizing flows are a powerful class of generative models for continuous random variables, showing both strong model flexibility and the potential for non-autoregressive generati…