4 citations · 5 across the 3 of their papers we have counts for
5 papers · 1 filter
Fast Few-shot Debugging for NLU Test Suites
Christopher Malon, Kai Li, Erik Kruus
We study few-shot debugging of transformer based natural language understanding models, using recently popularized test suites to not just diagnose but correct a problem. Given a f…
Overcoming Poor Word Embeddings with Word Definitions
Christopher Malon
Modern natural language understanding models depend on pretrained subword embeddings, but applications may need to reason about words that were never or rarely seen during pretrain…
Generating Followup Questions for Interpretable Multi-hop Question Answering
Christopher Malon, Bing Bai
We propose a framework for answering open domain multi-hop questions in which partial information is read and used to generate followup questions, to finally be answered by a pretr…
Team Papelo: Transformer Networks at FEVER
Christopher Malon
We develop a system for the FEVER fact extraction and verification challenge that uses a high precision entailment classifier based on transformer networks pretrained with language…
Teaching Syntax by Adversarial Distraction
Juho Kim, Christopher Malon, Asim Kadav
Existing entailment datasets mainly pose problems which can be answered without attention to grammar or word order. Learning syntax requires comparing examples where different gram…