🤝 New advances in decentralized learning! "Topology-Aware Knowledge Propagation in Decentralized Learning" proposes a novel way to improve how information flows in distributed machine learning systems. Let’s break it down! 🧵 (1/6) (arxiv.org/abs/2505.11760)

@mansisakarvadia.bsky.social, Aswathy (PhD students), and @nathaniel-hudson.bsky.social (postdoc) presented their work on identifying and ablating memorization in #LLMs at the 2024 MSLD workshop! 🎉 Their research is also accepted to ICLR 2025 — check it out: mansisak.com/memorization/

1/🧵ICLR 2025 Spotlight Research on LM & Memorization!
Language models (LMs) often "memorize" data, leading to privacy risks. This paper explores ways to reduce that!
Paper: arxiv.org/pdf/2410.02159
Code: github.com/msakarvadia/...
Blog: mansisak.com/memorization/

Congratulations to @mansisakarvadia.bsky.social and team on their "Mitigating Memorization in Language Models" paper being selected as a Spotlight paper at ICLR '25! Check out the pre-print here: arxiv.org/abs/2410.02159

How can we stop LLMs from memorizing information? @mansisakarvadia.bsky.social's paper, which develops new methods for unlearning memorized information and introduces a suite of small LMs for testing these methods, was just accepted to ICLR '25!
arxiv.org/pdf/2410.02159

Reflecting on my 2024 PhD journey: passed my qualifying exam, spent the summer at Berkeley, mentored undergrad students, and tackled the fast pace of AI/ML research. It’s been a year of milestones and growth! Read more here: mansisak.com/blog/2025/ye... #PhDJourney #AIResearch