S
Semih Yagcioglu
Researcher at Hacettepe University
Publications - 10
Citations - 264
Semih Yagcioglu is an academic researcher from Hacettepe University. The author has contributed to research in topics: Procedural knowledge & Recurrent neural network. The author has an hindex of 6, co-authored 9 publications receiving 175 citations.
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Proceedings ArticleDOI
RecipeQA: A Challenge Dataset for Multimodal Comprehension of Cooking Recipes
TL;DR: The authors introduce RecipeQA, a dataset for multimodal comprehension of cooking recipes, which comprises of approximately 20k instructional recipes with multiple modalities such as titles, descriptions and aligned set of images.
Proceedings ArticleDOI
A Distributed Representation Based Query Expansion Approach for Image Captioning
TL;DR: The core idea of the method is to translate the given visual query into a distributional semantics based form, which is generated by the average of the sentence vectors extracted from the captions of images visually similar to the input image.
Posted Content
RecipeQA: A Challenge Dataset for Multimodal Comprehension of Cooking Recipes
TL;DR: This work introduces RecipeQA, a dataset for multimodal comprehension of cooking recipes, a set of comprehension and reasoning tasks that require joint understanding of images and text, capturing the temporal flow of events and making sense of procedural knowledge.
Journal ArticleDOI
Neural Natural Language Generation: A Survey on Multilinguality, Multimodality, Controllability and Learning
Erkut Erdem,Menekşe Kuyu,Semih Yagcioglu,Anette Frank,Letitia Parcalabescu,B. Plank,Andrii Babii,Oleksii Turuta,Aykut Erdem,Iacer Calixto,Elena Lloret,Elena Apostol,Ciprian-Octavian Truica,Branislava Šandrih,Sanda Martincic Ipsic,Gábor Berend,Albert Gatt,Gražina Korvel +17 more
TL;DR: This state-of-the-art report investigates the recent developments and applications of NNLG in its full extent from a multidimensional view, covering critical perspectives such as multimodality, multilinguality, controllability and learning strategies.
Proceedings ArticleDOI
TasvirEt: A benchmark dataset for automatic Turkish description generation from images
Mesut Erhan Unal,Begum Citamak,Semih Yagcioglu,Aykut Erdem,Erkut Erdem,Nazli Ikizler Cinbis,Ruket Cakici +6 more
TL;DR: The findings indicate that the new Turkish dataset and the approaches used here can be successfully used for automatically describing images in Turkish.