Search Results for author: Dimitra Gkatzia

Found 28 papers, 1 papers with code

CAPE: Context-Aware Private Embeddings for Private Language Learning

2 code implementations EMNLP 2021 Richard Plant, Dimitra Gkatzia, Valerio Giuffrida

Deep learning-based language models have achieved state-of-the-art results in a number of applications including sentiment analysis, topic labelling, intent classification and others.

intent-classification Intent Classification +2

Content Selection in Data-to-Text Systems: A Survey

no code implementations26 Oct 2016 Dimitra Gkatzia

Data-to-text systems are powerful in generating reports from data automatically and thus they simplify the presentation of complex data.

Data-to-Text Generation

An Ensemble method for Content Selection for Data-to-text Systems

no code implementations9 Jun 2015 Dimitra Gkatzia, Helen Hastie

We present a novel approach for automatic report generation from time-series data, in the context of student feedback generation.

General Classification Multi-Label Classification +2

Improving the Naturalness and Expressivity of Language Generation for Spanish

no code implementations WS 2017 Cristina Barros, Dimitra Gkatzia, Elena Lloret

We present a flexible Natural Language Generation approach for Spanish, focused on the surface realisation stage, which integrates an inflection module in order to improve the naturalness and expressivity of the generated language.

Text Generation

Chefbot: A Novel Framework for the Generation of Commonsense-enhanced Responses for Task-based Dialogue Systems

no code implementations INLG (ACL) 2021 Carl Strathearn, Dimitra Gkatzia

Conversational systems aim to generate responses that are accurate, relevant and engaging, either through utilising neural end-to-end models or through slot filling.

Chatbot Response Generation +2

It’s Commonsense, isn’t it? Demystifying Human Evaluations in Commonsense-Enhanced NLG Systems

no code implementations EACL (HumEval) 2021 Miruna-Adriana Clinciu, Dimitra Gkatzia, Saad Mahamood

Common sense is an integral part of human cognition which allows us to make sound decisions, communicate effectively with others and interpret situations and utterances.

Common Sense Reasoning Text Generation

Twenty Years of Confusion in Human Evaluation: NLG Needs Evaluation Sheets and Standardised Definitions

no code implementations INLG (ACL) 2020 David M. Howcroft, Anya Belz, Miruna-Adriana Clinciu, Dimitra Gkatzia, Sadid A. Hasan, Saad Mahamood, Simon Mille, Emiel van Miltenburg, Sashank Santhanam, Verena Rieser

Human assessment remains the most trusted form of evaluation in NLG, but highly diverse approaches and a proliferation of different quality criteria used by researchers make it difficult to compare results and draw conclusions across papers, with adverse implications for meta-evaluation and reproducibility.

Experimental Design

Task2Dial: A Novel Task and Dataset for Commonsense enhanced Task-based Dialogue Grounded in Documents

no code implementations3 Apr 2022 Carl Strathearn, Dimitra Gkatzia

This paper proposes a novel task on commonsense-enhanced task-based dialogue grounded in documents and describes the Task2Dial dataset, a novel dataset of document-grounded task-based dialogues, where an Information Giver (IG) provides instructions (by consulting a document) to an Information Follower (IF), so that the latter can successfully complete the task.

You Are What You Write: Preserving Privacy in the Era of Large Language Models

no code implementations20 Apr 2022 Richard Plant, Valerio Giuffrida, Dimitra Gkatzia

Large scale adoption of large language models has introduced a new era of convenient knowledge transfer for a slew of natural language processing tasks.

Privacy Preserving Sentiment Analysis +1

Task2Dial: A Novel Task and Dataset for Commonsense-enhanced Task-based Dialogue Grounded in Documents

no code implementations dialdoc (ACL) 2022 Carl Strathearn, Dimitra Gkatzia

This paper proposes a novel task on commonsense-enhanced task-based dialogue grounded in documents and describes the Task2Dial dataset, a novel dataset of document-grounded task-based dialogues, where an Information Giver (IG) provides instructions (by consulting a document) to an Information Follower (IF), so that the latter can successfully complete the task.

Multi3Generation: Multitask, Multilingual, Multimodal Language Generation

no code implementations EAMT 2022 Anabela Barreiro, José GC de Souza, Albert Gatt, Mehul Bhatt, Elena Lloret, Aykut Erdem, Dimitra Gkatzia, Helena Moniz, Irene Russo, Fabio Kepler, Iacer Calixto, Marcin Paprzycki, François Portet, Isabelle Augenstein, Mirela Alhasani

This paper presents the Multitask, Multilingual, Multimodal Language Generation COST Action – Multi3Generation (CA18231), an interdisciplinary network of research groups working on different aspects of language generation.

Text Generation

GEMv2: Multilingual NLG Benchmarking in a Single Line of Code

no code implementations22 Jun 2022 Sebastian Gehrmann, Abhik Bhattacharjee, Abinaya Mahendiran, Alex Wang, Alexandros Papangelis, Aman Madaan, Angelina McMillan-Major, Anna Shvets, Ashish Upadhyay, Bingsheng Yao, Bryan Wilie, Chandra Bhagavatula, Chaobin You, Craig Thomson, Cristina Garbacea, Dakuo Wang, Daniel Deutsch, Deyi Xiong, Di Jin, Dimitra Gkatzia, Dragomir Radev, Elizabeth Clark, Esin Durmus, Faisal Ladhak, Filip Ginter, Genta Indra Winata, Hendrik Strobelt, Hiroaki Hayashi, Jekaterina Novikova, Jenna Kanerva, Jenny Chim, Jiawei Zhou, Jordan Clive, Joshua Maynez, João Sedoc, Juraj Juraska, Kaustubh Dhole, Khyathi Raghavi Chandu, Laura Perez-Beltrachini, Leonardo F. R. Ribeiro, Lewis Tunstall, Li Zhang, Mahima Pushkarna, Mathias Creutz, Michael White, Mihir Sanjay Kale, Moussa Kamal Eddine, Nico Daheim, Nishant Subramani, Ondrej Dusek, Paul Pu Liang, Pawan Sasanka Ammanamanchi, Qi Zhu, Ratish Puduppully, Reno Kriz, Rifat Shahriyar, Ronald Cardenas, Saad Mahamood, Salomey Osei, Samuel Cahyawijaya, Sanja Štajner, Sebastien Montella, Shailza, Shailza Jolly, Simon Mille, Tahmid Hasan, Tianhao Shen, Tosin Adewumi, Vikas Raunak, Vipul Raheja, Vitaly Nikolaev, Vivian Tsai, Yacine Jernite, Ying Xu, Yisi Sang, Yixin Liu, Yufang Hou

This problem is especially pertinent in natural language generation which requires ever-improving suites of datasets, metrics, and human evaluation to make definitive claims.

Benchmarking Text Generation

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