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researcher

Murat Kantarcioglu

12 papers hereh-index 353 citations19 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author3
  • last author9

Across the 12 of 12 papers where every author was matched, so the position is known.

fields
  • cs.LG4
  • cs.AI3
  • cs.CL1
  • cs.CR1
  • cs.CY1
  • cs.HC1
same name
  • Murat Kantarcioglu — 36 papers, h 59
  • Murat Kantarcioglu — 9 papers, h 3
  • Murat Kantarcioglu — 8 papers, h 2
  • Murat Kantarcioglu — 6 papers, h 3
  • Murat Kantarcioglu — 4 papers, h 2
  • Murat Kantarcioglu — 2 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20232026
most citedUsing AI Uncertainty Quantification to Improve Human Decision-Making

2 citations · 2 across the 12 of their papers we have counts for

collaborators
Showing 2025Show all

4 papers · 1 filter

cs.CY2025

Ask ChatGPT: Caveats and Mitigations for Individual Users of AI Chatbots

Chengen Wang, Murat Kantarcioglu

As ChatGPT and other Large Language Model (LLM)-based AI chatbots become increasingly integrated into individuals' daily lives, important research questions arise. What concerns an…

cs.LG2025

Graph Generative Models Evaluation with Masked Autoencoder

Chengen Wang, Murat Kantarcioglu

In recent years, numerous graph generative models (GGMs) have been proposed. However, evaluating these models remains a considerable challenge, primarily due to the difficulty in e…

cs.LG2025

A Review of DeepSeek Models' Key Innovative Techniques

Chengen Wang, Murat Kantarcioglu

DeepSeek-V3 and DeepSeek-R1 are leading open-source Large Language Models (LLMs) for general-purpose tasks and reasoning, achieving performance comparable to state-of-the-art close…

cs.LG2025

A Systematic Evaluation of Generative Models on Tabular Transportation Data

Chengen Wang, Alvaro Cardenas, Gurcan Comert +1

The sharing of large-scale transportation data is beneficial for transportation planning and policymaking. However, it also raises significant security and privacy concerns, as the…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.