48 citations · 176 across the 9 of their papers we have counts for
13 papers
Learning to Reject with a Fixed Predictor: Application to Decontextualization
Christopher Mohri, Daniel Andor, Eunsol Choi +1
We study the problem of classification with a reject option for a fixed predictor, applicable in natural language processing. We introduce a new problem formulation for this scenar…
Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models
Bernd Bohnet, Vinh Q. Tran, Pat Verga +19
Large language models (LLMs) have shown impressive results while requiring little or no direct supervision. Further, there is mounting evidence that LLMs may have potential in info…
Honest Students from Untrusted Teachers: Learning an Interpretable Question-Answering Pipeline from a Pretrained Language Model
Jacob Eisenstein, Daniel Andor, Bernd Bohnet +2
Explainable question answering systems should produce not only accurate answers but also rationales that justify their reasoning and allow humans to check their work. But what sort…
Scaling Up Models and Data with and
Adam Roberts, Hyung Won Chung, Anselm Levskaya +40
Recent neural network-based language models have benefited greatly from scaling up the size of training datasets and the number of parameters in the models themselves. Scaling can…
QED: A Framework and Dataset for Explanations in Question Answering
Matthew Lamm, Jennimaria Palomaki, Chris Alberti +4
A question answering system that in addition to providing an answer provides an explanation of the reasoning that leads to that answer has potential advantages in terms of debuggab…
Measuring Domain Portability and ErrorPropagation in Biomedical QA
Stefan Hosein, Daniel Andor, Ryan McDonald
In this work we present Google's submission to the BioASQ 7 biomedical question answering (QA) task (specifically Task 7b, Phase B). The core of our systems are based on BERT QA mo…