Search Results for author:
Found 16 papers, 3 papers with code
Detecting Turkish Synonyms Used in Different Time Periods
Dynamic structure of languages poses significant challenges in applying natural language processing models on historical texts, causing decreased performance in various downstream tasks.
NativQA: Multilingual Culturally-Aligned Natural Query for LLMs
Natural Question Answering (QA) datasets play a crucial role in evaluating the capabilities of large language models (LLMs), ensuring their effectiveness in real-world applications.
Turkronicles: Diachronic Resources for the Fast Evolving Turkish Language
Thus, we first introduce Turkronicles which is a diachronic corpus for Turkish derived from the Official Gazette of T\"urkiye.
I Know You Did Not Write That! A Sampling Based Watermarking Method for Identifying Machine Generated Text
Potential harms of Large Language Models such as mass misinformation and plagiarism can be partially mitigated if there exists a reliable way to detect machine generated text.
New Metrics to Encourage Innovation and Diversity in Information Retrieval Approaches
In addition, we show that our metrics achieve higher evaluation stability and discriminative power than the standard metrics we modify.
Catch Me If You Can: Deceiving Stance Detection and Geotagging Models to Protect Privacy of Individuals on Twitter
Our experiments show that the performance of BERT-based models fined tuned for stance detection decreases significantly due to typos, but it is not affected by paraphrasing.
Patent Search Using Triplet Networks Based Fine-Tuned SciBERT
In this paper, we propose a novel method for the prior-art search task.
Overview of the CLEF--2021 CheckThat! Lab on Detecting Check-Worthy Claims, Previously Fact-Checked Claims, and Fake News
We describe the fourth edition of the CheckThat!
An Information Retrieval Approach to Building Datasets for Hate Speech Detection
Our key insight is that the rarity and subjectivity of hate speech are akin to that of relevance in information retrieval (IR).
Understanding and Predicting Characteristics of Test Collections in Information Retrieval
Research community evaluations in information retrieval, such as NIST's Text REtrieval Conference (TREC), build reusable test collections by pooling document rankings submitted by many teams.
TrClaim-19: The First Collection for Turkish Check-Worthy Claim Detection with Annotator Rationales
Massive misinformation spread over Internet has many negative impacts on our lives.
Embeddings-Based Clustering for Target Specific Stances: The Case of a Polarized Turkey
On June 24, 2018, Turkey conducted a highly consequential election in which the Turkish people elected their president and parliament in the first election under a new presidential system.
Ranked #1 on
Stance Detection
on Trump Midterm Elections 2018
Too Many Claims to Fact-Check: Prioritizing Political Claims Based on Check-Worthiness
In this paper, we propose a model prioritizing the claims based on their check-worthiness.
Embedding-based Qualitative Analysis of Polarization in Turkey
During the election period, the Turkish people extensively shared their political opinions on Twitter.
Social and Information Networks
Efficient Test Collection Construction via Active Learning
To create a new IR test collection at low cost, it is valuable to carefully select which documents merit human relevance judgments.
