Papers by David Omer
Morphological Inflection with Phonological Features (2023.acl-short)
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| Challenge: | Recent advances in morphological tasks can be difficult to solve when little training data is available or when generalizing to previously unseen lemmas. |
| Approach: | They propose two methods to manipulate phonemic data to include phonological features instead of characters. |
| Outcome: | The proposed methods yield comparable results to baseline models, with minor improvements in some languages. |
Morphological Reinflection with Multiple Arguments: An Extended Annotation schema and a Georgian Case Study (2022.acl-short)
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| Challenge: | morphological annotations are a common problem in some languages, but the flat structure of the current schema makes it impossible to treat them. |
| Approach: | They propose a general solution for polypersonal agreement in Georgian language . they extend the existing UniMorph annotation schema to address this problem . |
| Outcome: | The proposed framework covers all possible variants of argument marking, and is accurate and balanced. |
(Un)solving Morphological Inflection: Lemma Overlap Artificially Inflates Models’ Performance (2022.acl-short)
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| Challenge: | Inflection tasks have gained a lot of traction in recent years, mostly via SIGMORPHON's shared-tasks. |
| Approach: | They propose to use split-by-lemma to challenge the generalization capacity of morphological inflection models by employing harder train-test splits. |
| Outcome: | The proposed method is based on a split-by-lemma method that challenges the generalization capacity of the models. |
GmSLM : Generative Marmoset Spoken Language Modeling (2025.findings-emnlp)
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| Challenge: | Generative Marmoset Spoken Language Modeling (GmSLM) is an optimized spoken language model pipeline for Marmosaet vocal communication. |
| Approach: | They propose an optimized spoken language model pipeline for Marmoset vocal communication. |
| Outcome: | The proposed framework can be used to link vocal communication with brain activity in Marmoset monkeys. |
UniMorph 4.0: Universal Morphology (2022.lrec-1)
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Khuyagbaatar Batsuren, Omer Goldman, Salam Khalifa, Nizar Habash, Witold Kieraś, Gábor Bella, Brian Leonard, Garrett Nicolai, Kyle Gorman, Yustinus Ghanggo Ate, Maria Ryskina, Sabrina Mielke, Elena Budianskaya, Charbel El-Khaissi, Tiago Pimentel, Michael Gasser, William Abbott Lane, Mohit Raj, Matt Coler, Jaime Rafael Montoya Samame, Delio Siticonatzi Camaiteri, Esaú Zumaeta Rojas, Didier López Francis, Arturo Oncevay, Juan López Bautista, Gema Celeste Silva Villegas, Lucas Torroba Hennigen, Adam Ek, David Guriel, Peter Dirix, Jean-Philippe Bernardy, Andrey Scherbakov, Aziyana Bayyr-ool, Antonios Anastasopoulos, Roberto Zariquiey, Karina Sheifer, Sofya Ganieva, Hilaria Cruz, Ritván Karahóǧa, Stella Markantonatou, George Pavlidis, Matvey Plugaryov, Elena Klyachko, Ali Salehi, Candy Angulo, Jatayu Baxi, Andrew Krizhanovsky, Natalia Krizhanovskaya, Elizabeth Salesky, Clara Vania, Sardana Ivanova, Jennifer White, Rowan Hall Maudslay, Josef Valvoda, Ran Zmigrod, Paula Czarnowska, Irene Nikkarinen, Aelita Salchak, Brijesh Bhatt, Christopher Straughn, Zoey Liu, Jonathan North Washington, Yuval Pinter, Duygu Ataman, Marcin Wolinski, Totok Suhardijanto, Anna Yablonskaya, Niklas Stoehr, Hossep Dolatian, Zahroh Nuriah, Shyam Ratan, Francis M. Tyers, Edoardo M. Ponti, Grant Aiton, Aryaman Arora, Richard J. Hatcher, Ritesh Kumar, Jeremiah Young, Daria Rodionova, Anastasia Yemelina, Taras Andrushko, Igor Marchenko, Polina Mashkovtseva, Alexandra Serova, Emily Prud’hommeaux, Maria Nepomniashchaya, Fausto Giunchiglia, Eleanor Chodroff, Mans Hulden, Miikka Silfverberg, Arya D. McCarthy, David Yarowsky, Ryan Cotterell, Reut Tsarfaty, Ekaterina Vylomova
| Challenge: | The Universal Morphology project provides broad-coverage instantiated morphological inflection tables for hundreds of diverse languages. |
| Approach: | They propose a language-independent feature schema for rich morphological annotation and a type-level resource of annotated data in diverse languages realizing that schema. |
| Outcome: | The proposed schema has added 66 new languages, including 24 endangered languages. |
Eye Tracking and NLP (2025.acl-tutorials)
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| Challenge: | tutorial combines eye tracking during reading with NLP . outlines how eye movements in reading can be leveraged for NLP methods . |
| Approach: | The tutorial combines eye tracking during reading with NLP . it covers eye movements in reading, integrating eye movement data in NLP models . |
| Outcome: | The tutorial outlines how eye movements in reading can be leveraged for NLP . it provides the essential background for conducting research on joint modeling of eye movements and text. |