354 citations · 1.3k across the 59 of their papers we have counts for
64 papers
Aligned Data Can Induce Misalignment via Context Confusion
Yavuz Bakman, Duygu Nur Yaldiz, Baris Askin +4
Large language models (LLMs) are frequently updated for various use cases, where filtering out misaligned training samples is a common practice for preventing post-update misalignm…
ASPIRE: Asynchronous Batched Self-Speculative Decoding for Long-Context LLM Inference
Amir Ziashahabi, Hossein Entezari Zarch, Lei Gao +2
Long-context LLM inference is bottlenecked by attention, whose repeated KV-cache reads make decoding memory-bound. Self-speculative decoding alleviates this by drafting tokens with…
Decoding Extrahepatic Targeting of Lipid Nanoparticles with Interpretable Machine Learning
Asal Mehradfar, Mohammad Shahab Sepehri, Owen Antholine +4
Lipid nanoparticles (LNPs) have transformed RNA medicine, yet their clinical utility remains constrained by predominant hepatic accumulation after systemic administration. Redirect…
Spend Bits Where Queries Look: KV Cache Vector Quantization with Attention-Preserving Transforms
Samuel Fernández-Menduiña, Amir Ziashahabi, Eduardo Pavez +2
Long-context LLM decoding reads the key-value (KV) cache at every step. Loading it takes longer than computing attention over it, so throughput is bandwidth-bound. Hence, reducing…
Hair-Trigger Alignment: Black-Box Evaluation Cannot Guarantee Post-Update Alignment
Yavuz Bakman, Duygu Nur Yaldiz, Eleni Triantafillou +3
Large Language Models (LLMs) are rarely static and are frequently updated in practice. A growing body of alignment research has shown that models initially deemed ``aligned'' can e…
A Machine Learning Benchmarking Framework for Lipid Nanoparticle Transfection Efficiency Prediction
Asal Mehradfar, Mohammad Shahab Sepehri, Jose Miguel Hernandez-Lobato +4
The discovery of new ionizable lipids for efficient lipid nanoparticle (LNP)-mediated RNA delivery remains a major bottleneck in RNA therapeutics development. Recent advances demon…