Search Results for author: Rahmad Mahendra

Found 22 papers, 8 papers with code

ISWARA at WNUT-2020 Task 2: Identification of Informative COVID-19 English Tweets using BERT and FastText Embeddings

no code implementations EMNLP (WNUT) 2020 Wava Carissa Putri, Rani Aulia Hidayat, Isnaini Nurul Khasanah, Rahmad Mahendra

This paper presents Iswara’s participation in the WNUT-2020 Task 2 “Identification of Informative COVID-19 English Tweets using BERT and FastText Embeddings”, which tries to classify whether a certain tweet is considered informative or not.

Task 2 Word Embeddings

IndoCulture: Exploring Geographically-Influenced Cultural Commonsense Reasoning Across Eleven Indonesian Provinces

no code implementations2 Apr 2024 Fajri Koto, Rahmad Mahendra, Nurul Aisyah, Timothy Baldwin

Although commonsense reasoning is greatly shaped by cultural and geographical factors, previous studies on language models have predominantly centered on English cultures, potentially resulting in an Anglocentric bias.

Language Modelling

Two-Stage Classifier for COVID-19 Misinformation Detection Using BERT: a Study on Indonesian Tweets

2 code implementations30 Jun 2022 Douglas Raevan Faisal, Rahmad Mahendra

Although there were already several studies related to the detection of misinformation in social media data, most studies focused on the English dataset.

Language Modelling Misinformation +2

ITTC @ TREC 2021 Clinical Trials Track

no code implementations16 Feb 2022 Thinh Hung Truong, Yulia Otmakhova, Rahmad Mahendra, Timothy Baldwin, Jey Han Lau, Trevor Cohn, Lawrence Cavedon, Damiano Spina, Karin Verspoor

This paper describes the submissions of the Natural Language Processing (NLP) team from the Australian Research Council Industrial Transformation Training Centre (ITTC) for Cognitive Computing in Medical Technologies to the TREC 2021 Clinical Trials Track.

Retrieval

Multi-Task Active Learning for Neural Semantic Role Labeling on Low Resource Conversational Corpus

no code implementations WS 2018 Fariz Ikhwantri, Samuel Louvan, Kemal Kurniawan, Bagas Abisena, Valdi Rachman, Alfan Farizki Wicaksono, Rahmad Mahendra

In this paper, we propose a Multi-Task Active Learning framework for Semantic Role Labeling with Entity Recognition (ER) as the auxiliary task to alleviate the need for extensive data and use additional information from ER to help SRL.

Active Learning Multi-Task Learning +1

KOI at SemEval-2018 Task 5: Building Knowledge Graph of Incidents

no code implementations SEMEVAL 2018 Paramita Mirza, Fariz Darari, Rahmad Mahendra

We present KOI (Knowledge of Incidents), a system that given news articles as input, builds a knowledge graph (KOI-KG) of incidental events.

Clustering coreference-resolution +6

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