output
20172025
most citedSupporting Qualitative Analysis with Large Language Models: Combining Codebook with GPT-3 for Deductive Coding

224 citations

Showing 2018Show all

10 papers · 1 filter

cs.LG2018★ 43 cited

How Reasonable are Common-Sense Reasoning Tasks: A Case-Study on the Winograd Schema Challenge and SWAG

Paul Trichelair, Ali Emami, Adam Trischler +2

Recent studies have significantly improved the state-of-the-art on common-sense reasoning (CSR) benchmarks like the Winograd Schema Challenge (WSC) and SWAG. The question we ask in…

cs.CL2018

The Knowref Coreference Corpus: Removing Gender and Number Cues for Difficult Pronominal Anaphora Resolution

Ali Emami, Paul Trichelair, Adam Trischler +3

We introduce a new benchmark for coreference resolution and NLI, Knowref, that targets common-sense understanding and world knowledge. Previous coreference resolution tasks can lar…

cs.CL2018

Multi-Multi-View Learning: Multilingual and Multi-Representation Entity Typing

Yadollah Yaghoobzadeh, Hinrich Schütze

Knowledge bases (KBs) are paramount in NLP. We employ multiview learning for increasing accuracy and coverage of entity type information in KBs. We rely on two metaviews: language…

cs.CL2018★ 4 cited

A Knowledge Hunting Framework for Common Sense Reasoning

Ali Emami, Noelia De La Cruz, Adam Trischler +2

We introduce an automatic system that achieves state-of-the-art results on the Winograd Schema Challenge (WSC), a common sense reasoning task that requires diverse, complex forms o…

cs.CL2018★ 10 cited

One Size Does Not Fit All: Generating and Evaluating Variable Number of Keyphrases

Xingdi Yuan, Tong Wang, Rui Meng +4

Different texts shall by nature correspond to different number of keyphrases. This desideratum is largely missing from existing neural keyphrase generation models. In this study, w…

cs.CL2018★ 2 cited

Lessons learned in multilingual grounded language learning

Ákos Kádár, Desmond Elliott, Marc-Alexandre Côté +2

Recent work has shown how to learn better visual-semantic embeddings by leveraging image descriptions in more than one language. Here, we investigate in detail which conditions aff…