default search action
ALP@RANLP 2023: Varna, Bulgaria
- Adam Anderson, Shai Gordin, Bin Li, Yudong Liu, Marco Carlo Passarotti:
Proceedings of the Ancient Language Processing Workshop, ALP@RANLP 2023, Varna, Bulgaria, 8 September, 2023. INCOMA Ltd., Shoumen, Bulgaria / ACL 2023, ISBN 978-954-452-087-8 - Frontmatter.
- Marijke Beersmans, Evelien de Graaf, Tim Van de Cruys, Margherita Fantoli:
Training and Evaluation of Named Entity Recognition Models for Classical Latin. 1-12 - Kevin Krahn, Derrick Tate, Andrew C. Lamicela:
Sentence Embedding Models for Ancient Greek Using Multilingual Knowledge Distillation. 13-22 - Martijn Naaijer, Constantijn Sikkel, Mathias Coeckelbergs, Jisk Attema, Willem Th. Van Peursen:
A Transformer-based parser for Syriac morphology. 23-29 - Frederick Riemenschneider, Anette Frank:
Graecia capta ferum victorem cepit. Detecting Latin Allusions to Ancient Greek Literature. 30-38 - Gianluca Vico, Gerasimos Spanakis:
Larth: Dataset and Machine Translation for Etruscan. 39-48 - Silvia Stopponi, Nilo Pedrazzini, Saskia Peels, Barbara McGillivray, Malvina Nissim:
Evaluation of Distributional Semantic Models of Ancient Greek: Preliminary Results and a Road Map for Future Work. 49-58 - Federica Gamba, Daniel Zeman:
Latin Morphology through the Centuries: Ensuring Consistency for Better Language Processing. 59-67 - Ercong Nie, Helmut Schmid, Hinrich Schütze:
Cross-Lingual Constituency Parsing for Middle High German: A Delexicalized Approach. 68-79 - Yixuan Zhang, Haonan Li:
Can Large Langauge Model Comprehend Ancient Chinese? A Preliminary Test on ACLUE. 80-87 - Davide Picca, Caroline Richard:
Unveiling Emotional Landscapes in Plautus and Terentius Comedies: A Computational Approach for Qualitative Analysis. 88-95 - Kai Jin, Dan Zhao, Wuying Liu:
Morphological and Semantic Evaluation of Ancient Chinese Machine Translation. 96-102 - Philipp Koch, Gilary Vera Nuñez, Esteban Garces Arias, Christian Heumann, Matthias Schöffel, Alexander Häberlin, Matthias Aßenmacher:
A tailored Handwritten-Text-Recognition System for Medieval Latin. 103-110 - Colin Swaelens, Ilse De Vos, Els Lefever:
Evaluating Existing Lemmatisers on Unedited Byzantine Greek Poetry. 111-116 - Yue Qi, Liu Liu, Bin Li, Dongbo Wang:
Vector Based Stylistic Analysis on Ancient Chinese Books: Take the Three Commentaries on the Spring and Autumn Annals as an Example. 117-121 - Bolin Chang, Yiguo Yuan, Bin Li, Zhixing Xu, Minxuan Feng, Dongbo Wang:
A Joint Model of Automatic Word Segmentation and Part-Of-Speech Tagging for Ancient Classical Texts Based on Radicals. 122-132 - Hansel Guzman-Soto, Yudong Liu:
Introducing an Open Source Library for Sumerian Text Analysis. 133-137 - Dongxin Hu:
Coding Design of Oracle Bone Inscriptions Input Method Based on "ZhongHuaZiKu" Database. 138-147 - Alek Keersmaekers, Wouter Mercelis, Toon Van Hal:
Word Sense Disambiguation for Ancient Greek: Sourcing a training corpus through translation alignment. 148-159 - Tariq Yousef, Lisa Mischer, Hamid Reza Hakimi, Maxim Romanov:
Enhancing State-of-the-Art NLP Models for Classical Arabic. 160-169 - Charlie Cowen-Breen, Creston Brooks, Barbara Graziosi, Johannes Haubold:
Logion: Machine-Learning Based Detection and Correction of Textual Errors in Greek Philology. 170-178 - Tariq Yousef, Chiara Palladino, Farnoosh Shamsian:
Classical Philology in the Time of AI: Exploring the Potential of Parallel Corpora in Ancient Language. 179-192 - Ellie Bennett, Aleksi Sahala:
Using Word Embeddings for Identifying Emotions Relating to the Body in a Neo-Assyrian Corpus. 193-202 - Aleksi Sahala, Krister Lindén:
A Neural Pipeline for POS-tagging and Lemmatizing Cuneiform Languages. 203-212 - Bo An:
Tibetan Dependency Parsing with Graph Convolutional Neural Networks. 213-221 - Congjun Long, Bo An:
On the Development of Interlinearized Ancient Literature of Ethnic Minorities: A Case Study of the Interlinearization of Ancient Written Tibetan Literature. 222-231
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.