activity
20192023
most citedThe GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

52 citations · 85 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CL2023★ 1 cited

The Dangers of trusting Stochastic Parrots: Faithfulness and Trust in Open-domain Conversational Question Answering

Sabrina Chiesurin, Dimitris Dimakopoulos, Marco Antonio Sobrevilla Cabezudo +4

Large language models are known to produce output which sounds fluent and convincing, but is also often wrong, e.g. "unfaithful" with respect to a rationale as retrieved from a kno…

cs.CL2021★ 25 cited

NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation

Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122

Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…

cs.CL2021★ 52 cited

The GEM Benchmark: Natural Language Generation, its Evaluation and Metrics

Sebastian Gehrmann, Tosin Adewumi, Karmanya Aggarwal +53

We introduce GEM, a living benchmark for natural language Generation (NLG), its Evaluation, and Metrics. Measuring progress in NLG relies on a constantly evolving ecosystem of auto…

cs.CL2020★ 7 cited

Efficient strategies for hierarchical text classification: External knowledge and auxiliary tasks

Kervy Rivas Rojas, Gina Bustamante, Arturo Oncevay +1

In hierarchical text classification, we perform a sequence of inference steps to predict the category of a document from top to bottom of a given class taxonomy. Most of the studie…

cs.CL2019

SEMA: an Extended Semantic Evaluation Metric for AMR

Rafael T. Anchieta, Marco A. S. Cabezudo, Thiago A. S. Pardo

Abstract Meaning Representation (AMR) is a recently designed semantic representation language intended to capture the meaning of a sentence, which may be represented as a single-ro…