most citedYour Model Is Not Predicting Depression Well And That Is Why: A Case Study of PRIMATE Dataset

2 citations · 3 across the 7 of their papers we have counts for

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7 papers

cs.CL2025

GliLem: Leveraging GliNER for Contextualized Lemmatization in Estonian

Aleksei Dorkin, Kairit Sirts

We present GliLem -- a novel hybrid lemmatization system for Estonian that enhances the highly accurate rule-based morphological analyzer Vabamorf with an external disambiguation m…

cs.CL2025

Prune or Retrain: Optimizing the Vocabulary of Multilingual Models for Estonian

Aleksei Dorkin, Taido Purason, Kairit Sirts

Adapting multilingual language models to specific languages can enhance both their efficiency and performance. In this study, we explore how modifying the vocabulary of a multiling…

cs.CL2024

TartuNLP @ AXOLOTL-24: Leveraging Classifier Output for New Sense Detection in Lexical Semantics

Aleksei Dorkin, Kairit Sirts

We present our submission to the AXOLOTL-24 shared task. The shared task comprises two subtasks: identifying new senses that words gain with time (when comparing newer and older ti…

cs.CL2024

Sõnajaht: Definition Embeddings and Semantic Search for Reverse Dictionary Creation

Aleksei Dorkin, Kairit Sirts

We present an information retrieval based reverse dictionary system using modern pre-trained language models and approximate nearest neighbors search algorithms. The proposed appro…

cs.CL20241 cited

Evaluating Lexicon Incorporation for Depression Symptom Estimation

Kirill Milintsevich, Gaël Dias, Kairit Sirts

This paper explores the impact of incorporating sentiment, emotion, and domain-specific lexicons into a transformer-based model for depression symptom estimation. Lexicon informati…

cs.CL2024

Comparison of Current Approaches to Lemmatization: A Case Study in Estonian

Aleksei Dorkin, Kairit Sirts

This study evaluates three different lemmatization approaches to Estonian -- Generative character-level models, Pattern-based word-level classification models, and rule-based morph…