6 citations · 15 across the 21 of their papers we have counts for
23 papers
VeriEvolve: Evaluator-First Evolution for Tool-Using Agents
Yueshen Li, Kamer Ali Yuksel, Gokhan Tur +2
A central obstacle to self-improving agents is the absence of a reliable fitness signal for realistic stateful tasks. We introduce \textsc{VeriEvolve}, an evaluator-first evolution…
ARCHead: Activation-Metric Residual Correction for Large Language Model Output Heads
Şuayp Talha Kocabay, Talha Rüzgar Akkuş, Kamer Ali Yuksel
Weight-only quantization substantially reduces the storage of large language model (LLM) transformer blocks, but practical backends often retain the final language-modeling head (L…
Selectivity and Shape in the Design of Forward-Forward Goodness Functions
Talha Ruzgar Akkus, Suayp Talha Kocabay, Kamer Ali Yuksel +1
The Forward-Forward (FF) algorithm trains networks layer-by-layer using a local "goodness function," yet sum-of-squares (SoS) has remained the only choice studied. We systematicall…
EvoForest: A Novel Machine-Learning Paradigm via Open-Ended Evolution of Computational Graphs
Kamer Ali Yuksel, Hassan Sawaf
Modern machine learning is still largely organized around a single recipe: choose a parameterized model family and optimize its weights. Although highly successful, this paradigm i…
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…
PAACE: A Plan-Aware Automated Agent Context Engineering Framework
Kamer Ali Yuksel
Large Language Model (LLM) agents are increasingly deployed in complex, multi-step workflows involving planning, tool use, reflection, and interaction with external knowledge syste…
EvoLattice: Persistent Internal-Population Evolution through Multi-Alternative Quality-Diversity Graph Representations for LLM-Guided Program Discovery
Kamer Ali Yuksel
Large language models (LLMs) are increasingly used to evolve programs and multi-agent systems, yet most existing approaches rely on overwrite-based mutations that maintain only a s…
AI Co-Artist: A LLM-Powered Framework for Interactive GLSL Shader Animation Evolution
Kamer Ali Yuksel, Hassan Sawaf
Creative coding and real-time shader programming are at the forefront of interactive digital art, enabling artists, designers, and enthusiasts to produce mesmerizing, complex visua…
Efficient Machine Translation Corpus Generation: Integrating Human-in-the-Loop Post-Editing with Large Language Models
Kamer Ali Yuksel, Ahmet Gunduz, Abdul Baseet Anees +1
This paper introduces an advanced methodology for machine translation (MT) corpus generation, integrating semi-automated, human-in-the-loop post-editing with large language models…
MediaMind: Revolutionizing Media Monitoring using Agentification
Ahmet Gunduz, Kamer Ali Yuksel, Hassan Sawaf
In an era of rapid technological advancements, agentification of software tools has emerged as a critical innovation, enabling systems to function autonomously and adaptively. This…
ChameleonLLM: Batch-Aware Dynamic Low-Rank Adaptation via Inference-Time Clusters
Kamer Ali Yuksel, Hassan Sawaf
Recent advances in large language models (LLMs) have shown remarkable performance across diverse tasks. However, these models are typically deployed with fixed weights, which limit…
AlphaSharpe: LLM-Driven Discovery of Robust Risk-Adjusted Metrics
Kamer Ali Yuksel, Hassan Sawaf
Financial metrics like the Sharpe ratio are pivotal in evaluating investment performance by balancing risk and return. However, traditional metrics often struggle with robustness a…
A Multi-AI Agent System for Autonomous Optimization of Agentic AI Solutions via Iterative Refinement and LLM-Driven Feedback Loops
Kamer Ali Yuksel, Hassan Sawaf
Agentic AI systems use specialized agents to handle tasks within complex workflows, enabling automation and efficiency. However, optimizing these systems often requires labor-inten…
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…
An Automated End-to-End Open-Source Software for High-Quality Text-to-Speech Dataset Generation
Ahmet Gunduz, Kamer Ali Yuksel, Kareem Darwish +4
Data availability is crucial for advancing artificial intelligence applications, including voice-based technologies. As content creation, particularly in social media, experiences…
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…
Generative Meta-Learning Robust Quality-Diversity Portfolio
Kamer Ali Yuksel
This paper proposes a novel meta-learning approach to optimize a robust portfolio ensemble. The method uses a deep generative model to generate diverse and high-quality sub-portfol…
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-…
NoRefER: a Referenceless Quality Metric for Automatic Speech Recognition via Semi-Supervised Language Model Fine-Tuning with Contrastive Learning
Kamer Ali Yuksel, Thiago Ferreira, Golara Javadi +2
This paper introduces NoRefER, a novel referenceless quality metric for automatic speech recognition (ASR) systems. Traditional reference-based metrics for evaluating ASR systems r…
Efficient Machine Translation Corpus Generation
Kamer Ali Yuksel, Ahmet Gunduz, Shreyas Sharma +1
This paper proposes an efficient and semi-automated method for human-in-the-loop post-editing for machine translation (MT) corpus generation. The method is based on online training…
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…
Granular Motor State Monitoring of Free Living Parkinson's Disease Patients via Deep Learning
Kamer A. Yuksel, Jann Goschenhofer, Hridya V. Varma +2
Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide and affects around 1% of the (60+ years old) elderly population in industrial nations. More t…
Wearable-based Parkinson's Disease Severity Monitoring using Deep Learning
Jann Goschenhofer, Franz MJ Pfister, Kamer Ali Yuksel +3
One major challenge in the medication of Parkinson's disease is that the severity of the disease, reflected in the patients' motor state, cannot be measured using accessible biomar…