activity
20212026
most citedIncreasing Data Diversity with Iterative Sampling to Improve Performance

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

REIGN: Refurbished Embeddings with Integrated Guidance Networks for Efficient Context-Length Scaling

Devrim Çavuşoğlu, Emre Akbaş

Dense retrieval over long documents is expensive. Token-level encoders scale quadratically in sequence length, and most long-context embedding models reach 32K tokens only through…

cs.CL2024

DisGeM: Distractor Generation for Multiple Choice Questions with Span Masking

Devrim Cavusoglu, Secil Sen, Ulas Sert

Recent advancements in Natural Language Processing (NLP) have impacted numerous sub-fields such as natural language generation, natural language inference, question answering, and…

cs.CL2024

A multi-level multi-label text classification dataset of 19th century Ottoman and Russian literary and critical texts

Gokcen Gokceoglu, Devrim Cavusoglu, Emre Akbas +1

This paper introduces a multi-level, multi-label text classification dataset comprising over 3000 documents. The dataset features literary and critical texts from 19th-century Otto…

cs.CV2024

DroBoost: An Intelligent Score and Model Boosting Method for Drone Detection

Ogulcan Eryuksel, Kamil Anil Ozfuttu, Fatih Cagatay Akyon +4

Drone detection is a challenging object detection task where visibility conditions and quality of the images may be unfavorable, and detections might become difficult due to comple…

cs.LG20211 cited

Increasing Data Diversity with Iterative Sampling to Improve Performance

Devrim Cavusoglu, Ogulcan Eryuksel, Sinan Altinuc

As a part of the Data-Centric AI Competition, we propose a data-centric approach to improve the diversity of the training samples by iterative sampling. The method itself relies st…