3 citations · 6 across the 17 of their papers we have counts for
18 papers
Exploring Profiles of Cognitive Distortions Associated with Mental Health Disorders
Alina Anikejeva, Kairit Sirts
Cognitive distortions, distorted patterns of thinking, have been increasingly studied in computational mental health research. Although they are related to many, if not all, mental…
EstLLM: Enhancing Estonian Capabilities in Multilingual LLMs via Continued Pretraining and Post-Training
Aleksei Dorkin, Taido Purason, Emil Kalbaliyev +7
Large language models (LLMs) are predominantly trained on English-centric data, resulting in uneven performance for smaller languages. We study whether continued pretraining (CPT)…
Creation of the Estonian Subjectivity Dataset: Assessing the Degree of Subjectivity on a Scale
Karl Gustav Gailit, Kadri Muischnek, Kairit Sirts
This article presents the creation of an Estonian-language dataset for document-level subjectivity, analyzes the resulting annotations, and reports an initial experiment of automat…
Estonian WinoGrande Dataset: Comparative Analysis of LLM Performance on Human and Machine Translation
Marii Ojastu, Hele-Andra Kuulmets, Aleksei Dorkin +3
In this paper, we present a localized and culturally adapted Estonian translation of the test set from the widely used commonsense reasoning benchmark, WinoGrande. We detail the tr…
Towards Consistent Detection of Cognitive Distortions: LLM-Based Annotation and Dataset-Agnostic Evaluation
Neha Sharma, Navneet Agarwal, Kairit Sirts
Text-based automated Cognitive Distortion detection is a challenging task due to its subjective nature, with low agreement scores observed even among expert human annotators, leadi…
Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures
Tyler A. Chang, Catherine Arnett, Abdelrahman Sadallah +377
To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and cultures. In this paper, we pre…
TartuNLP at SemEval-2025 Task 5: Subject Tagging as Two-Stage Information Retrieval
Aleksei Dorkin, Kairit Sirts
We present our submission to the Task 5 of SemEval-2025 that aims to aid librarians in assigning subject tags to the library records by producing a list of likely relevant tags for…
Exploratory Study into Relations between Cognitive Distortions and Emotional Appraisals
Navneet Agarwal, Kairit Sirts
In recent years, there has been growing interest in studying cognitive distortions and emotional appraisals from both computational and psychological perspectives. Despite consider…
Assessing the Reliability and Validity of GPT-4 in Annotating Emotion Appraisal Ratings
Deniss Ruder, Andero Uusberg, Kairit Sirts
Appraisal theories suggest that emotions arise from subjective evaluations of events, referred to as appraisals. The taxonomy of appraisals is quite diverse, and they are usually g…
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…
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…
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…
Context is Important in Depressive Language: A Study of the Interaction Between the Sentiments and Linguistic Markers in Reddit Discussions
Neha Sharma, Kairit Sirts
Research exploring linguistic markers in individuals with depression has demonstrated that language usage can serve as an indicator of mental health. This study investigates the im…
TartuNLP at EvaLatin 2024: Emotion Polarity Detection
Aleksei Dorkin, Kairit Sirts
This paper presents the TartuNLP team submission to EvaLatin 2024 shared task of the emotion polarity detection for historical Latin texts. Our system relies on two distinct approa…
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…
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…
TartuNLP @ SIGTYP 2024 Shared Task: Adapting XLM-RoBERTa for Ancient and Historical Languages
Aleksei Dorkin, Kairit Sirts
We present our submission to the unconstrained subtask of the SIGTYP 2024 Shared Task on Word Embedding Evaluation for Ancient and Historical Languages for morphological annotation…
Your Model Is Not Predicting Depression Well And That Is Why: A Case Study of PRIMATE Dataset
Kirill Milintsevich, Kairit Sirts, Gaël Dias
This paper addresses the quality of annotations in mental health datasets used for NLP-based depression level estimation from social media texts. While previous research relies on…