5 papers · 1 filter
F-TIS: Harnessing Diverse Models in Collaborative GRPO
Nikolay Blagoev, OÄuzhan Ersoy, Wendelin Boehmer +1
Reinforcement learning methods such as GRPO have seen great popularity in LLM post-training. In GRPO, models produce completions to a set of prompts, which are rewarded, and the po…
Hail to the Thief: Exploring Attacks and Defenses in Decentralised GRPO
Nikolay Blagoev, OÄuzhan Ersoy, Lydia Yiyu Chen
Group Relative Policy Optimization (GRPO) has demonstrated wide adoption in the post-training of Large Language Models (LLMs). In GRPO, prompts are answered by the model and prefer…
Go With The Flow: Churn-Tolerant Decentralized Training of Large Language Models
Nikolay Blagoev, Bart Cox, Jérémie Decouchant +1
Motivated by the emergence of large language models (LLMs) and the importance of democratizing their training, we propose GWTF, the first crash tolerant practical decentralized tra…
NoLoCo: No-all-reduce Low Communication Training Method for Large Models
Jari Kolehmainen, Nikolay Blagoev, John Donaghy +2
Training large language models is generally done via optimization methods on clusters containing tens of thousands of accelerators, communicating over a high-bandwidth interconnect…
SkipPipe: Partial and Reordered Pipelining Framework for Training LLMs in Heterogeneous Networks
Nikolay Blagoev, Lydia Yiyu Chen, OÄuzhan Ersoy
Data and pipeline parallelism are ubiquitous for training of Large Language Models (LLM) on distributed nodes. Driven by the need for cost-effective training, recent work explores…