Join us at @emnlpmeeting for:
"Tailoring AI: Exploring Active and Passive LLM Personalization" 🎯🧠
To answer, when should LLMs personalize? What role do users play in LLM-personalization?
📅 Deadline Aug. 1
📝 Details in thread 🧵👇
#EMNLP2025#LLM#AI#personalization
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Looking for an alternative to RAG for personalization?
With PLUM, a pipeline for teaching LLMs to remember prior user conversations, we aim to enable your future personalization research. Joint work with @maartjeterhoeve@RinMetcalfSusa@YizheZhangNLP from my internship @Apple
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3/🧵PEFT: We use these QA pairs to finetune a LoRA adapter conversation by conversation. We find that weighting the loss on the QA tokens focuses the model on relevant content, rather than structure. Iterating on each conversation for 10 epochs gives the best results.
Stop discarding your old gradients! Introducing AdEMAMix, a novel (first-order) optimizer capable of outperforming Adam. Let’s have a thread on momentum and the surprising relevance of very old gradients. A joint work with @GrangierDavid and @PierreAblin#ml#optimization
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