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Walter Daelemans

7 accepted papers

2025

In Benchmarks We Trust ... Or Not?

EMNLP 2025

Standardized benchmarks are central to evaluating and comparing model performance in Natural Language Processing (NLP). However, Large Language Models (LLMs) have exposed shortcomings in existing benchmarks, and so far there is no clear solution. In this paper, we survey a wide scope of benchmarking

Cited by 0SourcePDFScholar
2025

Jump To Hyperspace: Comparing Euclidean and Hyperbolic Loss Functions for Hierarchical Multi-Label Text Classification

COLING 2025main

Hierarchical Multi-Label Text Classification (HMTC) is a challenging machine learning task where multiple labels from a hierarchically organized label set are assigned to a single text. In this study, we examine the effectiveness of Euclidean and hyperbolic loss functions to improve the performance…

Cited by 1SourcePDFScholar
2022

CoNTACT: A Dutch COVID-19 Adapted BERT for Vaccine Hesitancy and Argumentation Detection

COLING 2022main

We present CoNTACT: a Dutch language model adapted to the domain of COVID-19 tweets. The model was developed by continuing the pre-training phase of RobBERT (Delobelle et al., 2020) by using 2.8M Dutch COVID-19 related tweets posted in 2021. In order to test the performance of the model and compare…

Cited by 6SourcePDFScholar
2022

Domain- and Task-Adaptation for VaccinChatNL, a Dutch COVID-19 FAQ Answering Corpus and Classification Model

COLING 2022main

FAQs are important resources to find information. However, especially if a FAQ concerns many question-answer pairs, it can be a difficult and time-consuming job to find the answer you are looking for. A FAQ chatbot can ease this process by automatically retrieving the relevant answer to a user’s que…

Cited by 5SourcePDFScholar
2022

Open-Domain Dialog Evaluation Using Follow-Ups Likelihood

COLING 2022main

Automatic evaluation of open-domain dialogs remains an unsolved problem. Existing methods do not correlate strongly with human annotations. In this paper, we present a new automated evaluation method based on the use of follow-ups. We measure the probability that a language model will continue the c…

2021

Mapping probability word problems to executable representations

EMNLP 2021main

While solving math word problems automatically has received considerable attention in the NLP community, few works have addressed probability word problems specifically. In this paper, we employ and analyse various neural models for answering such word problems. In a two-step approach, the problem t…

Cited by 12SourcePDFScholar