11 citations · 12 across the 5 of their papers we have counts for
7 papers
Agentic AI for Human Resources: LLM-Driven Candidate Assessment
Kamer Ali Yuksel, Abdul Basit Anees, Ashraf Elneima +3
In this work, we present a modular and interpretable framework that uses Large Language Models (LLMs) to automate candidate assessment in recruitment. The system integrates diverse…
Bel Esprit: Multi-Agent Framework for Building AI Model Pipelines
Yunsu Kim, AhmedElmogtaba Abdelaziz, Thiago Castro Ferreira +2
As the demand for artificial intelligence (AI) grows to address complex real-world tasks, single models are often insufficient, requiring the integration of multiple models into pi…
AutoMode-ASR: Learning to Select ASR Systems for Better Quality and Cost
Ahmet Gündüz, Yunsu Kim, Kamer Ali Yuksel +3
We present AutoMode-ASR, a novel framework that effectively integrates multiple ASR systems to enhance the overall transcription quality while optimizing cost. The idea is to train…
Word-Level ASR Quality Estimation for Efficient Corpus Sampling and Post-Editing through Analyzing Attentions of a Reference-Free Metric
Golara Javadi, Kamer Ali Yuksel, Yunsu Kim +2
In the realm of automatic speech recognition (ASR), the quest for models that not only perform with high accuracy but also offer transparency in their decision-making processes is…
A Reference-less Quality Metric for Automatic Speech Recognition via Contrastive-Learning of a Multi-Language Model with Self-Supervision
Kamer Ali Yuksel, Thiago Ferreira, Ahmet Gunduz +2
The common standard for quality evaluation of automatic speech recognition (ASR) systems is reference-based metrics such as the Word Error Rate (WER), computed using manual ground-…
EvolveMT: an Ensemble MT Engine Improving Itself with Usage Only
Kamer Ali Yuksel, Ahmet Gunduz, Mohamed Al-Badrashiny +2
This paper presents EvolveMT for efficiently combining multiple machine translation (MT) engines. The proposed system selects the output from a single engine for each segment by ut…