4 citations · 4 across the 3 of their papers we have counts for
5 papers
Adding Recurrence to Pretrained Transformers for Improved Efficiency and Context Size
Davis Yoshida, Allyson Ettinger, Kevin Gimpel
Fine-tuning a pretrained transformer for a downstream task has become a standard method in NLP in the last few years. While the results from these models are impressive, applying t…
PeTra: A Sparsely Supervised Memory Model for People Tracking
Shubham Toshniwal, Allyson Ettinger, Kevin Gimpel +1
We propose PeTra, a memory-augmented neural network designed to track entities in its memory slots. PeTra is trained using sparse annotation from the GAP pronoun resolution dataset…
Spying on your neighbors: Fine-grained probing of contextual embeddings for information about surrounding words
Josef Klafka, Allyson Ettinger
Although models using contextual word embeddings have achieved state-of-the-art results on a host of NLP tasks, little is known about exactly what information these embeddings enco…
What BERT is not: Lessons from a new suite of psycholinguistic diagnostics for language models
Allyson Ettinger
Pre-training by language modeling has become a popular and successful approach to NLP tasks, but we have yet to understand exactly what linguistic capacities these pre-training pro…
Towards Linguistically Generalizable NLP Systems: A Workshop and Shared Task
Allyson Ettinger, Sudha Rao, Hal Daumé +1
This paper presents a summary of the first Workshop on Building Linguistically Generalizable Natural Language Processing Systems, and the associated Build It Break It, The Language…