8 citations · 22 across the 20 of their papers we have counts for
20 papers
Cultural Awareness is Represented but Not Decoded: Tracing Mythological Knowledge across 18 Open-Source LLMs
Iaroslav Chelombitko, Ekaterina Chelombitko, Mika Hämäläinen
Open-source LLMs reliably name Zeus, Jupiter, and Thor, but recover their counterparts in less-represented traditions like Finnish, Slavic, Egyptian, or Chinese mythology far less…
Subword-Based Comparative Linguistics across 242 Languages Using Wikipedia Glottosets
Iaroslav Chelombitko, Mika Hämäläinen, Aleksey Komissarov
We present a large-scale comparative study of 242 Latin and Cyrillic-script languages using subword-based methodologies. By constructing 'glottosets' from Wikipedia lexicons, we in…
From NLG Evaluation to Modern Student Assessment in the Era of ChatGPT: The Great Misalignment Problem and Pedagogical Multi-Factor Assessment (P-MFA)
Mika Hämäläinen, Kimmo Leiviskä
This paper explores the growing epistemic parallel between NLG evaluation and grading of students in a Finnish University. We argue that both domains are experiencing a Great Misal…
On Psychology of AI -- Does Primacy Effect Affect ChatGPT and Other LLMs?
Mika Hämäläinen
We study the primacy effect in three commercial LLMs: ChatGPT, Gemini and Claude. We do this by repurposing the famous experiment Asch (1946) conducted using human subjects. The ex…
Threefold model for AI Readiness: A Case Study with Finnish Healthcare SMEs
Mohammed Alnajjar, Khalid Alnajjar, Mika Hämäläinen
This study examines AI adoption among Finnish healthcare SMEs through semi-structured interviews with six health-tech companies. We identify three AI engagement categories: AI-curi…
Analyzing Pokémon and Mario Streamers' Twitch Chat with LLM-based User Embeddings
Mika Hämäläinen, Jack Rueter, Khalid Alnajjar
We present a novel digital humanities method for representing our Twitch chatters as user embeddings created by a large language model (LLM). We cluster these embeddings automatica…
Leveraging Transformer-Based Models for Predicting Inflection Classes of Words in an Endangered Sami Language
Khalid Alnajjar, Mika Hämäläinen, Jack Rueter
This paper presents a methodology for training a transformer-based model to classify lexical and morphosyntactic features of Skolt Sami, an endangered Uralic language characterized…
DAG: Dictionary-Augmented Generation for Disambiguation of Sentences in Endangered Uralic Languages using ChatGPT
Mika Hämäläinen
We showcase that ChatGPT can be used to disambiguate lemmas in two endangered languages ChatGPT is not proficient in, namely Erzya and Skolt Sami. We augment our prompt by providin…
Predicting Sustainable Development Goals Using Course Descriptions -- from LLMs to Conventional Foundation Models
Lev Kharlashkin, Melany Macias, Leo Huovinen +1
We present our work on predicting United Nations sustainable development goals (SDG) for university courses. We use an LLM named PaLM 2 to generate training data given a noisy huma…
Sentiment Analysis Using Aligned Word Embeddings for Uralic Languages
Khalid Alnajjar, Mika Hämäläinen, Jack Rueter
In this paper, we present an approach for translating word embeddings from a majority language into 4 minority languages: Erzya, Moksha, Udmurt and Komi-Zyrian. Furthermore, we ali…
Ring That Bell: A Corpus and Method for Multimodal Metaphor Detection in Videos
Khalid Alnajjar, Mika Hämäläinen, Shuo Zhang
We present the first openly available multimodal metaphor annotated corpus. The corpus consists of videos including audio and subtitles that have been annotated by experts. Further…
Modern French Poetry Generation with RoBERTa and GPT-2
Mika Hämäläinen, Khalid Alnajjar, Thierry Poibeau
We present a novel neural model for modern poetry generation in French. The model consists of two pretrained neural models that are fine-tuned for the poem generation task. The enc…
Emotion Conditioned Creative Dialog Generation
Khalid Alnajjar, Mika Hämäläinen
We present a DialGPT based model for generating creative dialog responses that are conditioned based on one of the following emotions: anger, disgust, fear, happiness, pain, sadnes…
Automatic Generation of Factual News Headlines in Finnish
Maximilian Koppatz, Khalid Alnajjar, Mika Hämäläinen +1
We present a novel approach to generating news headlines in Finnish for a given news story. We model this as a summarization task where a model is given a news article, and its tas…
Video Games as a Corpus: Sentiment Analysis using Fallout New Vegas Dialog
Mika Hämäläinen, Khalid Alnajjar, Thierry Poibeau
We present a method for extracting a multilingual sentiment annotated dialog data set from Fallout New Vegas. The game developers have preannotated every line of dialog in the game…
When to Laugh and How Hard? A Multimodal Approach to Detecting Humor and its Intensity
Khalid Alnajjar, Mika Hämäläinen, Jörg Tiedemann +2
Prerecorded laughter accompanying dialog in comedy TV shows encourages the audience to laugh by clearly marking humorous moments in the show. We present an approach for automatical…
Multilingual Persuasion Detection: Video Games as an Invaluable Data Source for NLP
Teemu Pöyhönen, Mika Hämäläinen, Khalid Alnajjar
Role-playing games (RPGs) have a considerable amount of text in video game dialogues. Quite often this text is semi-annotated by the game developers. In this paper, we extract a mu…
Harnessing Multilingual Resources to Question Answering in Arabic
Khalid Alnajjar, Mika Hämäläinen
The goal of the paper is to predict answers to questions given a passage of Qur'an. The answers are always found in the passage, so the task of the model is to predict where an ans…
Processing M.A. Castrén's Materials: Multilingual Typed and Handwritten Manuscripts
Niko Partanen, Jack Rueter, Mika Hämäläinen +1
The study forms a technical report of various tasks that have been performed on the materials collected and published by Finnish ethnographer and linguist, Matthias Alexander Castr…
TFW2V: An Enhanced Document Similarity Method for the Morphologically Rich Finnish Language
Quan Duong, Mika Hämäläinen, Khalid Alnajjar
Measuring the semantic similarity of different texts has many important applications in Digital Humanities research such as information retrieval, document clustering and text summ…