Search Results for author: Constanza Fierro

Found 8 papers, 2 papers with code

Does Instruction Tuning Make LLMs More Consistent?

no code implementations23 Apr 2024 Constanza Fierro, Jiaang Li, Anders Søgaard

The purpose of instruction tuning is enabling zero-shot performance, but instruction tuning has also been shown to improve chain-of-thought reasoning and value alignment (Si et al., 2023).

Learning to Plan and Generate Text with Citations

no code implementations4 Apr 2024 Constanza Fierro, Reinald Kim Amplayo, Fantine Huot, Nicola De Cao, Joshua Maynez, Shashi Narayan, Mirella Lapata

The increasing demand for the deployment of LLMs in information-seeking scenarios has spurred efforts in creating verifiable systems, which generate responses to queries along with supporting evidence.

Long Form Question Answering

MuLan: A Study of Fact Mutability in Language Models

1 code implementation3 Apr 2024 Constanza Fierro, Nicolas Garneau, Emanuele Bugliarello, Yova Kementchedjhieva, Anders Søgaard

Facts are subject to contingencies and can be true or false in different circumstances.

$μ$PLAN: Summarizing using a Content Plan as Cross-Lingual Bridge

no code implementations23 May 2023 Fantine Huot, Joshua Maynez, Chris Alberti, Reinald Kim Amplayo, Priyanka Agrawal, Constanza Fierro, Shashi Narayan, Mirella Lapata

Cross-lingual summarization consists of generating a summary in one language given an input document in a different language, allowing for the dissemination of relevant content across speakers of other languages.


Factual Consistency of Multilingual Pretrained Language Models

1 code implementation Findings (ACL) 2022 Constanza Fierro, Anders Søgaard

However, for that, we need to know how reliable this knowledge is, and recent work has shown that monolingual English language models lack consistency when predicting factual knowledge, that is, they fill-in-the-blank differently for paraphrases describing the same fact.


Predicting Unplanned Readmissions with Highly Unstructured Data

no code implementations19 Mar 2020 Constanza Fierro, Jorge Pérez, Javier Mora

Deep learning techniques have been successfully applied to predict unplanned readmissions of patients in medical centers.

200K+ Crowdsourced Political Arguments for a New Chilean Constitution

no code implementations WS 2017 Constanza Fierro, Claudio Fuentes, Jorge P{\'e}rez, Mauricio Quezada

In this paper we present the dataset of 200, 000+ political arguments produced in the local phase of the 2016 Chilean constitutional process.

Argument Mining General Classification +1

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