21 citations · 54 across the 18 of their papers we have counts for
19 papers
Identity-Aware Semi-Supervised Learning for Comic Character Re-Identification
Gürkan Soykan, Deniz Yuret, Tevfik Metin Sezgin
Character re-identification, recognizing characters consistently across different panels in comics, presents significant challenges due to limited annotated data and complex variat…
Machine learning in and out of equilibrium
Shishir Adhikari, Alkan Kabakçıoğlu, Alexander Strang +2
The algorithms used to train neural networks, like stochastic gradient descent (SGD), have close parallels to natural processes that navigate a high-dimensional parameter space --…
A Comprehensive Gold Standard and Benchmark for Comics Text Detection and Recognition
Gürkan Soykan, Deniz Yuret, Tevfik Metin Sezgin
This study focuses on improving the optical character recognition (OCR) data for panels in the COMICS dataset, the largest dataset containing text and images from comic books. To d…
Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE 2022): Workshop and Shared Task Report
Ali Hürriyetoğlu, Hristo Tanev, Vanni Zavarella +3
We provide a summary of the fifth edition of the CASE workshop that is held in the scope of EMNLP 2022. The workshop consists of regular papers, two keynotes, working papers of sha…
Transformers on Multilingual Clause-Level Morphology
Emre Can Acikgoz, Tilek Chubakov, Müge Kural +2
This paper describes our winning systems in MRL: The 1st Shared Task on Multilingual Clause-level Morphology (EMNLP 2022 Workshop) designed by KUIS AI NLP team. We present our work…
Domain-Adaptive Self-Supervised Pre-Training for Face & Body Detection in Drawings
Barış Batuhan Topal, Deniz Yuret, Tevfik Metin Sezgin
Drawings are powerful means of pictorial abstraction and communication. Understanding diverse forms of drawings, including digital arts, cartoons, and comics, has been a major prob…
Self-Supervised Learning with an Information Maximization Criterion
Serdar Ozsoy, Shadi Hamdan, Sercan Ö. Arik +2
Self-supervised learning allows AI systems to learn effective representations from large amounts of data using tasks that do not require costly labeling. Mode collapse, i.e., the m…
Mukayese: Turkish NLP Strikes Back
Ali Safaya, Emirhan Kurtuluş, Arda Göktoğan +1
Having sufficient resources for language X lifts it from the under-resourced languages class, but not necessarily from the under-researched class. In this paper, we address the pro…
CRAFT: A Benchmark for Causal Reasoning About Forces and inTeractions
Tayfun Ates, M. Samil Atesoglu, Cagatay Yigit +6
Humans are able to perceive, understand and reason about causal events. Developing models with similar physical and causal understanding capabilities is a long-standing goal of art…
Cross-context News Corpus for Protest Events related Knowledge Base Construction
Ali Hürriyetoğlu, Erdem Yörük, Deniz Yüret +4
We describe a gold standard corpus of protest events that comprise of various local and international sources from various countries in English. The corpus contains document, sente…
KUISAIL at SemEval-2020 Task 12: BERT-CNN for Offensive Speech Identification in Social Media
Ali Safaya, Moutasem Abdullatif, Deniz Yuret
In this paper, we describe our approach to utilize pre-trained BERT models with Convolutional Neural Networks for sub-task A of the Multilingual Offensive Language Identification s…
Modulating Bottom-Up and Top-Down Visual Processing via Language-Conditional Filters
İlker Kesen, Ozan Arkan Can, Erkut Erdem +2
How to best integrate linguistic and perceptual processing in multi-modal tasks that involve language and vision is an important open problem. In this work, we argue that the commo…
Learning from Implicit Information in Natural Language Instructions for Robotic Manipulations
Ozan Arkan Can, Pedro Zuidberg Dos Martires, Andreas Persson +5
Human-robot interaction often occurs in the form of instructions given from a human to a robot. For a robot to successfully follow instructions, a common representation of the worl…
A new dataset and model for learning to understand navigational instructions
Ozan Arkan Can, Deniz Yuret
In this paper, we present a state-of-the-art model and introduce a new dataset for grounded language learning. Our goal is to develop a model that can learn to follow new instructi…
Morphological analysis using a sequence decoder
Ekin Akyürek, Erenay Dayanık, Deniz Yuret
We introduce Morse, a recurrent encoder-decoder model that produces morphological analyses of each word in a sentence. The encoder turns the relevant information about the word and…
Transfer Learning for Low-Resource Neural Machine Translation
Barret Zoph, Deniz Yuret, Jonathan May +1
The encoder-decoder framework for neural machine translation (NMT) has been shown effective in large data scenarios, but is much less effective for low-resource languages. We prese…
Substitute Based SCODE Word Embeddings in Supervised NLP Tasks
Volkan Cirik, Deniz Yuret
We analyze a word embedding method in supervised tasks. It maps words on a sphere such that words co-occurring in similar contexts lie closely. The similarity of contexts is measur…
Mode-coupling points to functionally important residues in Myosin II
Onur Varol, Deniz Yuret, Burak Erman +1
Relevance of mode coupling to energy/information transfer during protein function, particularly in the context of allosteric interactions is widely accepted. However, existing evid…
FASTSUBS: An Efficient and Exact Procedure for Finding the Most Likely Lexical Substitutes Based on an N-gram Language Model
Deniz Yuret
Lexical substitutes have found use in areas such as paraphrasing, text simplification, machine translation, word sense disambiguation, and part of speech induction. However the com…