Emre Can Acikgoz

I am a PhD fellow in Computer Science at UIUC advised by Prof. Dilek Hakkani-Tur and Prof. Gokhan Tur. My research focus is in Conversational and Generative AI.


I obtained my MSc in Computer Science at Koc University. I worked around Large Language Models and Multimodal Learning under the supervision of Deniz Yuret and Aykut Erdem.


Prior to my MSc, I recieved my BSc in Electrical and Electronics Engineering (AI focus) from Koc University, where I worked under the supervision of Deniz Yuret on supervised and unsupervised morphological analysis.


Email  /  GitHub  /  HuggingFace  /  Google Scholar  /  LinkedIn

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Research

My research is in Conversational Agents and Large Language Models.

2024


hippo Bridging the Bosphorus: Advancing Turkish Large Language Models through Strategies for Low-Resource Language Adaptation and Benchmarking
Emre Can Acikgoz, Mete Erdoğan, Deniz Yuret
EMNLP Workshop, 2024
arxiv / website / code / poster

This study evaluates the effectiveness of training strategies for large language models in low-resource languages like Turkish, focusing on model adaptation, development, and fine-tuning to enhance reasoning skills and address challenges such as data scarcity and catastrophic forgetting.

bridge Hippocrates: An Open-Source Framework for Advancing Large Language Models in Healthcare
Emre Can Acikgoz, Osman Batur İnce, Rayene Bech, Arda Anıl Boz, Ilker Kesen, Aykut Erdem, Erkut Erdem
arXiv, 2024
arxiv / website / poster

We present Hippocrates, an open-source LLM framework specifically developed for the medical domain. Also, we introduce Hippo, a family of 7B models tailored for the medical domain, fine-tuned from Mistral and LLaMA2 through continual pre-training, instruction tuning, and reinforcement learning from human and AI feedback.

vilma ViLMA: A Zero-Shot Benchmark for Linguistic and Temporal Grounding in Video-Language Models
Ilker Kesen, Andrea Pedrotti, Mustafa Dogan, Michele Cafagna, Emre Can Acikgoz, Letitia Parcalabescu, Iacer Calixto, Anette Frank, Albert Gatt, Aykut Erdem, Erkut Erdem
ICLR, 2024
arxiv / website / code

ViLMA (Video Language Model Assessment) presents a comprehensive benchmark for Video-Language Models, starting with a fundamental comprehension test and followed by a more advanced evaluation for temporal reasoning skills.

2022


mrl Transformers on Multilingual Clause-Level Morphology
Emre Can Acikgoz, Tilek Chubakov, Müge Kural, Gözde Gül Şahin, Deniz Yuret
EMNLP Workshop, 2022
arxiv / code / slides

This paper describes the winning approaches in MRL: The 1st Shared Task on Multilingual Clause-level Morphology. Our submission, which excelled in all three parts of the shared task — inflection, reinflection, and analysis — won the first prize in each category.

Tutor


Comp547: Deep Unsupervised Learning (Spring'24)
Comp541: Deep Learning (Fall'23)
Comp542: Natural Language Processing (Spring'23)
Comp541: Deep Learning (Fall'22)
Comp547: Deep Unsupervised Learning (Spring'22)

Talks


Huawei NLP/ML Community Seminer Series: Morphological Analysis with Large Language Models (2022, Virtual)
EMNLP MRL: Winning Paper Presentation (2022, Abu-Dhabi)


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