CAM 2.0: End-to-End Open Domain Comparative Question Answering System

Ahmad Shallouf, Hanna Herasimchyk, Mikhail Salnikov, Rudy Alexandro Garrido Veliz, Natia Mestvirishvili, Alexander Panchenko, Chris Biemann, Irina Nikishina

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Abstract
Comparative Question Answering (CompQA) is a Natural Language Processing task that combines Question Answering and Argument Mining approaches to answer subjective comparative questions in an efficient argumentative manner. In this paper, we present an end-to-end (full pipeline) system for answering comparative questions called CAM 2.0 as well as a public leaderboard called CompUGE that unifies the existing datasets under a single easy-to-use evaluation suite. As compared to previous web-form-based CompQA systems, it features question identification, object and aspect labeling, stance classification, and summarization using up-to-date models. We also select the most time- and memory-effective pipeline by comparing separately fine-tuned Transformer Encoder models which show state-of-the-art performance on the subtasks with Generative LLMs in few-shot and LoRA setups. We also conduct a user study for a whole-system evaluation.
Anthology ID:
2024.lrec-main.238
Volume:
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
Venues:
LREC | COLING
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
2657–2672
Language:
URL:
https://aclanthology.org/2024.lrec-main.238
DOI:
Bibkey:
Cite (ACL):
Ahmad Shallouf, Hanna Herasimchyk, Mikhail Salnikov, Rudy Alexandro Garrido Veliz, Natia Mestvirishvili, Alexander Panchenko, Chris Biemann, and Irina Nikishina. 2024. CAM 2.0: End-to-End Open Domain Comparative Question Answering System. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 2657–2672, Torino, Italia. ELRA and ICCL.
Cite (Informal):
CAM 2.0: End-to-End Open Domain Comparative Question Answering System (Shallouf et al., LREC-COLING 2024)
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