2 citations · 2 across the 5 of their papers we have counts for
8 papers
Physics of Agents: Statistical Mechanics Predicts Collective Behavior of AI Agents
Batu El, Jinhee Paeng, Fatih Dinc +7
AI agents increasingly operate as part of interacting systems rather than in isolation. As agents exchange information and jointly make decisions, their interactions can improve co…
Score Broadcast and Decorrelation: A General Framework for Broadcast-Based Credit Assignment
Mustafa Uzun, Mete Erdogan, Cengiz Pehlevan +1
We introduce Score Broadcast and Decorrelation (SBD), a principled framework for broadcast-based credit assignment for general families of differentiable losses. Error broadcast is…
Tangent Space Fine-Tuning for Directional Preference Alignment in Large Language Models
Mete Erdogan
Our goal is to enable large language models (LLMs) to balance multiple human preference dimensions; such as helpfulness, safety, and verbosity, through principled and controllable…
An Information-Theoretic Perspective on LLM Tokenizers
Mete Erdogan, Abhiram Gorle, Shubham Chandak +2
Large language model (LLM) tokenizers act as structured compressors: by mapping text to discrete token sequences, they determine token count (and thus compute and context usage) an…
Generalized Gradient Norm Clipping & Non-Euclidean -Smoothness
Thomas Pethick, Wanyun Xie, Mete Erdogan +3
This work introduces a hybrid non-Euclidean optimization method which generalizes gradient norm clipping by combining steepest descent and conditional gradient approaches. The meth…
Efficient Large Language Model Inference with Neural Block Linearization
Mete Erdogan, Francesco Tonin, Volkan Cevher
The high inference demands of transformer-based Large Language Models (LLMs) pose substantial challenges in their deployment. To this end, we introduce Neural Block Linearization (…
Error Broadcast and Decorrelation as a Potential Artificial and Natural Learning Mechanism
Mete Erdogan, Cengiz Pehlevan, Alper T. Erdogan
We introduce Error Broadcast and Decorrelation (EBD), a novel learning framework for neural networks that addresses credit assignment by directly broadcasting output errors to indi…
Bridging the Bosphorus: Advancing Turkish Large Language Models through Strategies for Low-Resource Language Adaptation and Benchmarking
Emre Can Acikgoz, Mete Erdogan, Deniz Yuret
Large Language Models (LLMs) are becoming crucial across various fields, emphasizing the urgency for high-quality models in underrepresented languages. This study explores the uniq…