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Found 11 papers, 0 papers with code
BiTeM at WNUT 2020 Shared Task-1: Named Entity Recognition over Wet Lab Protocols using an Ensemble of Contextual Language Models
Recent improvements in machine-reading technologies attracted much attention to automation problems and their possibilities.
SEME at SemEval-2024 Task 2: Comparing Masked and Generative Language Models on Natural Language Inference for Clinical Trials
This paper describes our submission to Task 2 of SemEval-2024: Safe Biomedical Natural Language Inference for Clinical Trials.
DS4DH at TREC Health Misinformation 2021: Multi-Dimensional Ranking Models with Transfer Learning and Rank Fusion
The TREC Health Misinformation track focused on the development of retrieval methods that provide relevant, correct and credible information for health related searches on the Web.
Named entity recognition in chemical patents using ensemble of contextual language models
The results show that ensemble of contextualized language models can provide an effective method to extract information from chemical patents.
Contextualized French Language Models for Biomedical Named Entity Recognition
Our best approach achieved an F1 -measure of 66{\%} for symptoms and signs, and pathology categories, being top 1 for subtask 1.
Automated Fact-Checking of Claims in Argumentative Parliamentary Debates
We present an automated approach to distinguish true, false, stretch, and dodge statements in questions and answers in the Canadian Parliament.
Using context to identify the language of face-saving
We created a corpus of utterances that attempt to save face from parliamentary debates and use it to automatically analyze the language of reputation defence.
Recognizing Reputation Defence Strategies in Critical Political Exchanges
We propose a new task of automatically detecting reputation defence strategies in the field of computational argumentation.
Classifying Frames at the Sentence Level in News Articles
Previous approaches to generic frame classification analyze frames at the document level.
Argumentation Quality Assessment: Theory vs. Practice
Argumentation quality is viewed differently in argumentation theory and in practical assessment approaches.
Computational Argumentation Quality Assessment in Natural Language
Research on computational argumentation faces the problem of how to automatically assess the quality of an argument or argumentation.
