Accepted Papers

The DeepLo 2022 proceedings are now available.


  • Introducing QuBERT: A Large Monolingual Corpus and BERT Model for Southern Quechua

Rodolfo Zevallos, John Ortega, William Chen, Richard Castro, Núria Bel, Cesar Toshio, Renzo Venturas, Hilario Aradiel and Nelsi Melgarejo


  • Improving Distantly Supervised Document-Level Relation Extraction Through Natural Language Inference

Clara Vania, Grace Lee and Andrea Pierleoni


  • IDANI: Inference-time Domain Adaptation via Neuron-level Interventions

Omer Antverg, Eyal Ben-David and Yonatan Belinkov


  • Generating unlabelled data for a tri-training approach in a low resourced NER task

Hugo Boulanger, Thomas Lavergne and Sophie Rosset


  • ANTS: A Framework for Retrieval of Text Segments in Unstructured Documents

Brian Chivers, Mason P. Jiang, Wonhee Lee, Amy Ng, Natalya I. Rapstine and Alex Storer


  • Cross-TOP: Zero-Shot Cross-Schema Task-Oriented Parsing

Melanie A. Rubino, Nicolas Guenon des mesnards, Uday Shah, Nanjiang Jiang, Weiqi Sun and Konstantine Arkoudas


  • Help from the Neighbors: Estonian Dialect Normalization Using a Finnish Dialect Generator

Mika Hämäläinen, Khalid Alnajjar and Tuuli Tuisk


  • Exploring diversity in back translation for low-resource machine translation

Laurie Burchell, Alexandra Birch and Kenneth Heafield


  • Punctuation Restoration in Spanish Customer Support Transcripts using Transfer Learning

Xiliang Zhu, Shayna Gardiner, David Rossouw, Tere Roldán and Simon Corston-Oliver


  • [🏆 Spotlight Paper] Pre-training Data Quality and Quantity for a Low-Resource Language: New Corpus and BERT Models for Maltese

Kurt Micallef, Albert Gatt, Marc Tanti, Lonneke van der Plas and Claudia Borg


  • Event Extractor with Only a Few Examples

Pengfei Yu, Zixuan Zhang, Clare Voss, Jonathan May and Heng Ji


  • Task Transfer and Domain Adaptation for Zero-Shot Question Answering

Xiang Pan, Alex Sheng, David Shimshoni, Aditya Singhal, Sara Rosenthal and Avirup Sil


  • Let the Model Decide its Curriculum for Multitask Learning

Neeraj Varshney, Swaroop Mishra and Chitta Baral


  • AfriTeVA: Extending “Small Data” Pretraining Approaches to Sequence-to-Sequence Models

Odunayo Jude Ogundepo, Akintunde Oladipo, Mofetoluwa Adeyemi, Kelechi Ogueji and Jimmy Lin


  • Few-shot Learning for Sumerian Named Entity Recognition

Guanghai Wang, Yudong Liu and James Hearne


  • Deep Learning-Based Morphological Segmentation for Indigenous Languages: A Study Case on Innu-Aimun

Ngoc Tan Le, Antoine Cadotte, Mathieu Boivin, Fatiha Sadat and Jimena Terraza


  • [🏆 Spotlight Paper] Clean or Annotate: How to Spend a Limited Data Collection Budget

Derek Chen, Zhou Yu and Samuel R. Bowman


  • Unsupervised Knowledge Graph Generation Using Semantic Similarity Matching

Lixian Liu, Amin Omidvar, Zongyang Ma, Ameeta Agrawal and Aijun An


  • FarFetched: Entity-centric Reasoning and Claim Validation for the Greek Language based on Textually Represented Environments

Dimitris Papadopoulos, Katerina Metropoulou, Nikolaos Papadakis and Nikolaos Matsatsinis


  • Alternative non-BERT model choices for the textual classification in low-resource languages and environments

Syed Mustavi Maheen, Moshiur Rahman Faisal, Md. Rafakat Rahman and Md. Shahriar Karim


  • Generating Complement Data for Aspect Term Extraction with GPT-2

Amir Pouran Ben Veyseh, Franck Dernoncourt, Bonan Min and Thien Huu Nguyen


  • How to Translate Your Samples and Choose Your Shots? Analyzing Translate-train & Few-shot Cross-lingual Transfer

Iman Jundi and Gabriella Lapesa


  • Unified NMT models for the Indian subcontinent, transcending script-barriers

Gokul N.C.