Adam Fisch

Consistent Accelerated Inference via Confident Adaptive Transformers

2021 · arXiv (Cornell University)

We develop a novel approach for confidently accelerating inference in the large and expensive multilayer Transformers that are now ubiquitous in natural language processing (NLP). Amortized or approximate computational methods increase efficiency, but can come …

Confident Adaptive Language Modeling

2022 · arXiv (Cornell University)

Recent advances in Transformer-based large language models (LLMs) have led to significant performance improvements across many tasks. These gains come with a drastic increase in the models' size, potentially leading to slow and costly use …

Key-Value Memory Networks for Directly Reading Documents

2016

Directly reading documents and being able to answer questions from them is an unsolved challenge. To avoid its inherent difficulty, question answering (QA) has been directed towards using Knowledge Bases (KBs) instead, which has proven …

Reading Wikipedia to Answer Open-Domain Questions

2017 · arXiv (Cornell University)

This paper proposes to tackle open- domain question answering using Wikipedia as the unique knowledge source: the answer to any factoid question is a text span in a Wikipedia article. This task of machine reading …

Making Pre-trained Language Models Better Few-shot Learners

2021

Tianyu Gao, Adam Fisch, Danqi Chen. Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers). 2021.