12 papers
ARCHead: Activation-Metric Residual Correction for Large Language Model Output Heads
Åuayp Talha Kocabay, Şuayp Talha Kocabay, Talha Rüzgar AkkuÅ +2
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…