Danilo Neves Ribeiro — accepted AI-conference papers

2023

STREET: A MULTI-TASK STRUCTURED REASONING AND EXPLANATION BENCHMARK

Danilo Neves Ribeiro, Shen Wang, Xiaofei Ma, Henghui Zhu, Rui Dong, Deguang Kong +7

ICLR 2023top-25%

We introduce STREET, a unified multi-task and multi-domain natural language reasoning and explanation benchmark. Unlike most existing question-answering (QA) datasets, we expect models to not only answer questions, but also produce step-by-step structured explanations describing how premises in the…

Cited by 27 Source ↗PDF ↗Scholar ↗

2022

Entailment Tree Explanations via Iterative Retrieval-Generation Reasoner

Danilo Neves Ribeiro, Shen Wang, Xiaofei Ma, Rui Dong, Xiaokai Wei, Henghui Zhu +5

NAACL 2022findings

Large language models have achieved high performance on various question answering (QA) benchmarks, but the explainability of their output remains elusive. Structured explanations, called entailment trees, were recently suggested as a way to explain the reasoning behind a QA system’s answer. In orde…

Cited by 44 Source ↗PDF ↗code ↗Scholar ↗