• Drawing with a social robot: Evaluating a vision-language model on spatial prepositions in an L2 drawing-based learning task 

  Paraskevi Daniilidou, Viktoria (2025-11-06)

  This study develops and evaluates a multimodal pipeline for studying interactive drawing in a robot-assisted language learning scenario with human participants. A social robot is paired with a vision-language model (VLM) ...

• Guided by Surprisal: Active Curriculum Language Modeling over a Hybrid Pre-training Method. Contributions to the BabyLM Challenge 

  Fysikoudi, Eleni (2025-10-30)

  This study investigates language modeling on developmentally plausible corpora under low-resource constraints, conducted within the scope of the BabyLM shared task, specifically focusing on the Strict-small track. We ...

• Enhancing NLU with Paraphrasing in Task-Oriented Dialogue Systems Toward Data-Efficient Generalization in Low-Resource Scenarios 

  Xue, Xiumei (2025-10-14)

  In task-oriented dialogue systems (TODS), Natural Language Understanding (NLU) is fundamental to interpreting user intent and extracting semantic information. However, training robust NLU models often requires large ...

• Adaptive Game-Based Swedish Language Learning A Hybrid AI Approach to Content Generation 

  Geng, Tianyi (2025-09-25)

  Abstract This thesis tests the performance of LLMs on pre-generated L2 Swedish learning content across beginner to intermediate CEFR levels (A1–B2) by employing them into a self-developed language learning game (including ...

• Effect of prompt strategy on the results of Code Generation by LLMs 

  Wang, Yiyi (2025-06-19)

  Abstract Large Language Models (LLMs) have made significant strides in automated code generation. For example, Github Copilot based on the CodeX model, is the first to generate complete functions directly from natural ...

• Breaking Barriers: Enhancing Universal Dependency Parsing for Amharic Advancing NLP for A Low-Resource Language 

  Jembere, Dawit (2025-06-19)

  This study advances Amharic dependency parsing by expanding and refining the existing Universal Dependencies (UD) Treebank (Seyoum, Miyao, and Mekonnen, 2018). As a morphologically rich and under-resourced language, ...

• Expert in the Loop: LLM Assistance for Technical Documentation Writing Case Study at Saab AB 

  Nieminen, Anni (2025-06-13)

  Abstract This study explores the potential of LLMs in the technical writing process at Saab Aeronautics. The technical writing process is investigated by interviewing technical writers, collecting insights regarding the ...

• Training for the Unexpected Approaching Universal Phone Recognition for Computer-Assisted IPA Transcription of Low-Resource Languages 

  Lee Suchardt, Jacob (2025-06-13)

  Abstract We set out to develop a language-agnostic ASR model for the phonetic transcription of speech into the International Phonetic Alphabet (IPA). While NLP and Automatic- Speech-Recognition (ASR) have made immense ...

• From Abstract Syntax to Natural Language Addressing Natural Language Generation Challenges in Arabic Using GFWordnet as Lexical Resources. 

  Zarzoura, Mohamed (2024-11-28)

  This thesis explores the development and evaluation of Arabic natural language generation using the Grammatical Framework (GF) within GFPedia. GFPedia is a framework that generates multilingual content using predefined ...

• FINDING MEANING IN A HAYSTACK: On How Vision and Language Models Process Figurative Language 

  Filippatou, Viktoria (2024-11-28)

  Figurative language is an integral part of human communication and everyday life. As a Natural Language Processing task it has long been the focus of attention in research, and recently it has been translated into a ...

• IMPLEMENTING A GROUNDING MODULE FOR AN NPC Testing grounding of novel names with state charts and LLMs 

  Astaiza Soriano, Nayat (2024-11-12)

  In this work we argue that any system that processes spoken human language should incorporate mechanisms for grounding, as it is an essential part of human communication. Because of this, we explore two name-grounding ...

• "MOVE TOWARDS THE BIG BLACK PIANO": HOW FINE-GRAINED FEATURES AFFECT THE GOAL OF NAVIGATION Improving salient landmark features in an end-to-end system 

  Le Glouanec, Bérénice (2024-10-30)

  Navigational instructions like ”Move towards the big black piano” or ”Head past the green armchair” are intuitive for humans, as they rely on salient landmarks to guide movement through space. This thesis explores how ...

• GENERATING ROUTE DESCRIPTIONS Automatic generation of route descriptions with visual elements from graph and salient landmarks 

  Akhavan, Kamaneh (2024-10-25)

  Can machines find the shortest route and guide us using intuitive, human-like instructions, such as ”move towards the big black piano” or ”head past the green armchair”? This thesis investigates the potential of machines ...

• EMERGENCE OF REFERRING EXPRESSIONS THROUGH LANGUAGE GAMES 

  Künkele, Dominik (2024-10-25)

  There has been a recent focus on how neural agents in language games ground referring expressions in visual 3D-scenes. This thesis explores when referring expressions emerge and if they align with referring expression ...

• WHEN EYES MEET LAUGHTER: Exploring Non-Verbal Cues in Human-Robot Interaction with Furhat 

  Giannitzi, Eleni (2024-10-25)

  Human-robot interaction is becoming increasingly popular, with social robots like Furhat playing key roles in enhancing communication through both verbal and non-verbal cues. This thesis investigates the impact of gaze ...

• Fine-Tuning Large Language Models for Practical Software Engineering: Case Studies in Automated Patch Generation 

  Zhou, Jiayun (2024-10-21)

  In recent years, software development has become increasingly complex, posing challenges in problem-solving, code optimization, and error correction. The rise of Artificial Intelligence (AI) and Large Language Models (LLMs) ...

• PERSONALIZED LANGUAGE LEARNING IN THE AGE OF AI. Leveraging Large Language Models for Optimal Learning Outcomes. 

  Zerkowska, Anika Milena (2024-06-25)

  In a new era marked by technological advancements and the AI boom, language learning is no longer limited to the classrooms. The emergence of Large Language Models (LLMs) propels further advancements within language ...

• Creating Synthetic Dialogue Datasets for NLU Training. An Approach Using Large Language Models 

  Laszlo, Bogdan (2024-06-20)

  This thesis explores the topic of using the GPT-4 large language model, to generate high-quality, diverse synthetic dialogue datasets for training Natural Language Understanding (NLU) models in task-oriented dialogue ...

• Automatic Idiomatic Expression Detection. Comparison Between GPT-4 and Gemini Pro Prompt Engineering & LSTM-RNN Construction 

  Hakkarainen, Stanislav; Engelbrecht, Katharina (2024-06-18)

  This thesis explores the concept of detecting non-literal phrases using Large Language Models (LLM) such as GPT-4 and Gemini Pro, as well as Recurrent Neural Networks (RNN), LSTM and BiLSTM models in particular. Through ...

• Logical properties of Natural Language Inference - Experiments with Synthetic Data to Study Consequence Relations in LSTMs 

  Monteiro, Hélder (2024-06-17)

  Natural language inference (NLI) datasets are great resources to train and benchmark models that infer entailment relations. However, these datasets are known to have issues such as lexical biases that affect the behaviour ...

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