3 papers
cs.LG2026
Understanding and Exploiting Weight Update Sparsity for Communication-Efficient Distributed RL
Erfan Miahi, Eugene Belilovsky
Bandwidth-constrained distributed reinforcement learning (RL) post-training of large language models is bottlenecked by two channels: weight synchronization from trainers to infere…
cs.CL2026
Grounded or Guessing? LVLM Confidence Estimation via Blind-Image Contrastive Ranking
Reza Khanmohammadi, Erfan Miahi, Simerjot Kaur +4
Large vision-language models suffer from visual ungroundedness: they can produce a fluent, confident, and even correct response driven entirely by language priors, with the image c…
cs.DC2026
Covenant-72B: Pre-Training a 72B LLM with Trustless Peers Over-the-Internet
Joel Lidin, Amir Sarfi, Erfan Miahi +6
Recently, there has been increased interest in globally distributed training, which has the promise to both reduce training costs and democratize participation in building large-sc…