1 citations · 1 across the 5 of their papers we have counts for
6 papers
When Can One Neuron Fix Repetition Loops in LLMs?
Aristotelis Lazaridis, Aman Sharma, Dylan Bates +3
The Gemma 4 instruction-tuned models share a reproducible failure: on long factual enumeration prompts, such as TV episodes, the 88 IAU constellations, or the 151 original Pokemon,…
EDGE-OPD: Internalizing Privileged Context with Evidence Guided On-Policy Distillation
Aristotelis Lazaridis, Dylan Bates, Aman Sharma +3
On-Policy Distillation (OPD) has gained wide attraction as an LLM post-training paradigm due to its effectiveness in improving capabilities without introducing model distribution d…
Measuring and Eliminating Refusals in Military Large Language Models
Jack FitzGerald, Dylan Bates, Aristotelis Lazaridis +17
Military Large Language Models (LLMs) must provide accurate information to the warfighter in time-critical and dangerous situations. However, today's LLMs are imbued with safety be…
EdgeRunner 20B: Military Task Parity with GPT-5 while Running on the Edge
Jack FitzGerald, Aristotelis Lazaridis, Dylan Bates +17
We present EdgeRunner 20B, a fine-tuned version of gpt-oss-20b optimized for military tasks. EdgeRunner 20B was trained on 1.6M high-quality records curated from military documenta…
A Hybrid Approach for Reinforcement Learning Using Virtual Policy Gradient for Balancing an Inverted Pendulum
Dylan Bates
Using the policy gradient algorithm, we train a single-hidden-layer neural network to balance a physically accurate simulation of a single inverted pendulum. The trained weights an…
Recommending More Efficient Workflows to Software Developers
Dylan Bates
Existing recommendation systems can help developers improve their software development abilities by recommending new programming tools, such as a refactoring tool or a program navi…