1 code implementation • Findings (EMNLP) 2021 • Jarana Manotumruksa, Jeff Dalton, Edgar Meij, Emine Yilmaz
While state-of-the-art Dialogue State Tracking (DST) models show promising results, all of them rely on a traditional cross-entropy loss function during the training process, which may not be optimal for improving the joint goal accuracy.
no code implementations • 6 Jul 2023 • Helia Hashemi, Yong Zhuang, Sachith Sri Ram Kothur, Srivas Prasad, Edgar Meij, W. Bruce Croft
In information retrieval (IR), domain adaptation is the process of adapting a retrieval model to a new domain whose data distribution is different from the source domain.
1 code implementation • In2Writing (ACL) 2022 • Nikos Voskarides, Edgar Meij, Sabrina Sauer, Maarten de Rijke
Given an incomplete narrative that specifies a main event and a context, we aim to retrieve news articles that discuss relevant events that would enable the continuation of the narrative.
no code implementations • EMNLP (NLP+CSS) 2020 • Katherine A. Keith, Christoph Teichmann, Brendan O'Connor, Edgar Meij
We find for this application (1) some annotator disagreements of economic policy uncertainty can be attributed to ambiguity in language, and (2) switching measurements from keyword-matching to supervised machine learning classifiers results in low correlation, a concerning implication for the validity of the index.
no code implementations • 18 Jun 2020 • Edgar Meij, Tara Safavi, Chenyan Xiong, Gianluca Demartini, Miriam Redi, Fatma Özcan
The KG-BIAS 2020 workshop touches on biases and how they surface in knowledge graphs (KGs), biases in the source data that is used to create KGs, methods for measuring or remediating bias in KGs, but also identifying other biases such as how and which languages are represented in automatically constructed KGs or how personal KGs might incur inherent biases.
no code implementations • EMNLP 2020 • Tara Safavi, Danai Koutra, Edgar Meij
We first conduct an evaluation under the standard closed-world assumption (CWA), in which predicted triples not already in the knowledge graph are considered false, and show that existing calibration techniques are effective for KGE under this common but narrow assumption.
no code implementations • 16 Mar 2020 • Antonia Saravanou, Giorgio Stefanoni, Edgar Meij
The volume of news content has increased significantly in recent years and systems to process and deliver this information in an automated fashion at scale are becoming increasingly prevalent.
1 code implementation • 1 Feb 2020 • Shuo Zhang, Edgar Meij, Krisztian Balog, Ridho Reinanda
We refer to this process as novel entity discovery and, to the best of our knowledge, it is the first endeavor on mining the unlinked cells in web tables.
no code implementations • 7 May 2018 • Nikos Voskarides, Edgar Meij, Ridho Reinanda, Abhinav Khaitan, Miles Osborne, Giorgio Stefanoni, Prabhanjan Kambadur, Maarten de Rijke
KG fact contextualization is the task of augmenting a given KG fact with additional and useful KG facts.