5 citations · 7 across the 12 of their papers we have counts for
12 papers
Compiling Rewrite Rules to Finite-State Transducers with the Worsening Trick
Mans Hulden, Michael Ginn
Finite-state transducers (FSTs) are essential for modeling string rewriting in computational linguistics and natural language processing (NLP), particularly for phonological and mo…
Speculative Decoding and the Curse of Multilinguality
Nirajan Paudel, Michael Ginn, Luc De Nardi +1
Speculative decoding is a popular technique for large language model (LLM) inference, enabling faster generation by drafting multiple tokens with a smaller draft model. However, th…
Massively Multilingual Joint Segmentation and Glossing
Michael Ginn, Lindia Tjuatja, Enora Rice +5
Automated interlinear gloss prediction with neural networks is a promising approach to accelerate language documentation efforts. However, while state-of-the-art models like GlossL…
Neural Induction of Finite-State Transducers
Michael Ginn, Alexis Palmer, Mans Hulden
Finite-State Transducers (FSTs) are effective models for string-to-string rewriting tasks, often providing the efficiency necessary for high-performance applications, but construct…
Is linguistically-motivated data augmentation worth it?
Ray Groshan, Michael Ginn, Alexis Palmer
Data augmentation, a widely-employed technique for addressing data scarcity, involves generating synthetic data examples which are then used to augment available training data. Res…
Tree Transformers are an Ineffective Model of Syntactic Constituency
Michael Ginn
Linguists have long held that a key aspect of natural language syntax is the recursive organization of language units into constituent structures, and research has suggested that c…
Historia Magistra Vitae: Dynamic Topic Modeling of Roman Literature using Neural Embeddings
Michael Ginn, Mans Hulden
Dynamic topic models have been proposed as a tool for historical analysis, but traditional approaches have had limited usefulness, being difficult to configure, interpret, and eval…
Can we teach language models to gloss endangered languages?
Michael Ginn, Mans Hulden, Alexis Palmer
Interlinear glossed text (IGT) is a popular format in language documentation projects, where each morpheme is labeled with a descriptive annotation. Automating the creation of inte…
GlossLM: A Massively Multilingual Corpus and Pretrained Model for Interlinear Glossed Text
Michael Ginn, Lindia Tjuatja, Taiqi He +4
Language documentation projects often involve the creation of annotated text in a format such as interlinear glossed text (IGT), which captures fine-grained morphosyntactic analyse…
Robust Generalization Strategies for Morpheme Glossing in an Endangered Language Documentation Context
Michael Ginn, Alexis Palmer
Generalization is of particular importance in resource-constrained settings, where the available training data may represent only a small fraction of the distribution of possible t…
Taxonomic Loss for Morphological Glossing of Low-Resource Languages
Michael Ginn, Alexis Palmer
Morpheme glossing is a critical task in automated language documentation and can benefit other downstream applications greatly. While state-of-the-art glossing systems perform very…
SIGMORPHON 2023 Shared Task of Interlinear Glossing: Baseline Model
Michael Ginn
Language documentation is a critical aspect of language preservation, often including the creation of Interlinear Glossed Text (IGT). Creating IGT is time-consuming and tedious, an…