Papers by Lori Levin
Adapting Word Embeddings to New Languages with Morphological and Phonological Subword Representations (D18-1)
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| Challenge: | Existing approaches to generalization to resource-rich languages are difficult . a recent study shows that word representations can be useful in low resource languages . |
| Approach: | They propose two approaches for improving generalization to low-resource languages by adapting continuous word representations using linguistically motivated subword units. |
| Outcome: | The proposed method improves generalization to low resource languages . it requires neither parallel corpora nor bilingual dictionaries and requires no parallel training . |
DeepCx: A transition-based approach for shallow semantic parsing with complex constructional triggers (D18-1)
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| Challenge: | Using DeepCx, we extend Shallow semantic parsing to include complex constructions . multi-word expressions and complex constructional arguments can express relational meanings - but little work has addressed tagging of such constructional triggers. |
| Approach: | They propose a neural-based surface construction labeling task that extends Shallow Semantic Parsing to include frames triggered by complex constructions. |
| Outcome: | The proposed system improves on the task of tagging causal language in English. |
Syntax and Semantics Meet in the “Middle”: Probing the Syntax-Semantics Interface of LMs Through Agentivity (2023.starsem-1)
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| Challenge: | a recent study examined how large language models handle interactions in meaning across words and larger syntactic forms. |
| Approach: | They propose to use a dataset to examine the linguistic properties of optionally transitive English verbs to examine their agentivity. |
| Outcome: | The proposed model outperforms all other models in the evaluation dataset . the results are better correlated with human judgements than syntactic and semantic corpus statistics . |
UCxn: Typologically-Informed Annotation of Constructions Atop Universal Dependencies (2024.lrec-main)
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Leonie Weissweiler, Nina Böbel, Kirian Guiller, Santiago Herrera, Wesley Samuel Scivetti, Arthur Lorenzi, Nurit Melnik, Archna Bhatia, Hinrich Schütze, Lori Levin, Amir Zeldes, Joakim Nivre, William Croft, Nathan Schneider
| Challenge: | Grammatical constructions that convey meaning through a particular combination of several morphosyntactic elements are not labeled holistically. |
| Approach: | They propose to augment UD annotations with a ‘UCxn’ annotation layer for such meaning-bearing grammatical constructions and to approach this in a typologically informed way so that morphosyntactic strategies can be compared across languages. |
| Outcome: | The proposed annotation layer could be used to annotate meaning-bearing constructions across languages and to compare them across languages. |
Wav2Gloss: Generating Interlinear Glossed Text from Speech (2024.acl-long)
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Taiqi He, Kwanghee Choi, Lindia Tjuatja, Nathaniel Robinson, Jiatong Shi, Shinji Watanabe, Graham Neubig, David Mortensen, Lori Levin
| Challenge: | Interlinear Glossed Text (IGT) is a form of linguistic annotation that can support documentation and resource creation for endangered languages. |
| Approach: | They propose a task in which these four annotation components are extracted automatically from speech and introduce a dataset to lay the groundwork for future research on IGT generation from speech. |
| Outcome: | The proposed dataset provides the first dataset to lay the groundwork for future research on IGT generation from speech, including end-to-end versus cascaded, monolingual versus multilingual, and single-task versus multiple-task approaches. |
Pre-tokenization of Multi-word Expressions in Cross-lingual Word Embeddings (2020.emnlp-main)
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| Challenge: | Multi-Word Expressions (MWEs) are common in every language, but they are not translated by cross-lingual word embeddings. |
| Approach: | They propose a method for word translation of Multi-Word Expressions (MWEs) they compile lists of MWEs in each language and tokenize them as single tokens before training word embeddings. |
| Outcome: | The proposed method can translate multi-word expressions to and from English in 10 languages. |
An Empirical Exploration of Local Ordering Pre-training for Structured Prediction (2020.findings-emnlp)
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| Challenge: | Recent studies have shown that pre-training contextualized encoders with language model objectives is effective for structured prediction. |
| Approach: | They propose a semi-supervised method for pre-training contextualized encoders with language model objectives. |
| Outcome: | The proposed method is effective on three typical structured prediction tasks in four languages. |
GlossLM: A Massively Multilingual Corpus and Pretrained Model for Interlinear Glossed Text (2024.emnlp-main)
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| Challenge: | Existing resources for standardized, easily accessible IGT data limit their applicability to linguistic research. |
| Approach: | They compile the largest existing corpus of interlinear glossed text data from a variety of sources and use it to generate annotated text. |
| Outcome: | The proposed model outperforms SOTA models on monolingual corpora by 6.6%. |
Parser combinators for Tigrinya and Oromo morphology (L18-1)
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Patrick Littell, Tom McCoy, Na-Rae Han, Shruti Rijhwani, Zaid Sheikh, David Mortensen, Teruko Mitamura, Lori Levin
| Challenge: | morphological parsers for two Afroasiatic languages are developed using a parser-combinator paradigm . the paradigm allows rapid development and ease of integration with other systems, but at a cost of non-optimal theoretical efficiency. |
| Approach: | They propose a rule-based morphological parser paradigm for Tigrinya and Oromo languages . they use a parsers-combinator paradigm instead of a finite-state paradigm . |
| Outcome: | The proposed paradigm allows rapid development and ease of integration with other systems, but at cost of non-optimal theoretical efficiency. |
A Resource for Computational Experiments on Mapudungun (2020.lrec-1)
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Mingjun Duan, Carlos Fasola, Sai Krishna Rallabandi, Rodolfo Vega, Antonios Anastasopoulos, Lori Levin, Alan W Black
| Challenge: | Low-resource languages still lag behind in documenting endangered languages . a large corpus of culturally significant conversations is available for computational experiments . |
| Approach: | They propose a resource for computational experiments on Mapudungun, a polysynthetic indigenous language spoken in Chile. |
| Outcome: | The proposed corpus provides 142 hours of culturally significant conversations in Mapudungun . the language is spoken by the Mapuche people of southern Chile and western argentina . |
Automatic Interlinear Glossing for Under-Resourced Languages Leveraging Translations (2020.coling-main)
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| Challenge: | Documentation is not a cure-all for language loss, but it is an important part of language preservation. |
| Approach: | They propose to use multi-source neural models to create automatic glossing models . they also explore cross-lingual transfer and a simple output length control mechanism . |
| Outcome: | The proposed model outperforms state-of-the-art models on low-resource scenarios. |
Constructions Are So Difficult That Even Large Language Models Get Them Right for the Wrong Reasons (2024.lrec-main)
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| Challenge: | In this paper, we examine the ability of large language models (LLMs) to identify different meanings in sentences that are superficially similar. |
| Approach: | They propose a challenge dataset for NLP with large lexical overlap which minimises the possibility of models discerning entailment solely based on token distinctions. |
| Outcome: | The proposed model fails to distinguish between constructions with three classes of adjectives which cannot be distinguished by surface features. |