works on

From the 1 of 13 linked papers with an AI index.

activity
20242026
most citedA Machine Learning Benchmarking Framework for Lipid Nanoparticle Transfection Efficiency Prediction

1 citations · 2 across the 4 of their papers we have counts for

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13 papers

cs.LG2026

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…

q-bio.QM20261 cited

A Machine Learning Benchmarking Framework for Lipid Nanoparticle Transfection Efficiency Prediction

Asal Mehradfar, Mohammad Shahab Sepehri, Jose Miguel Hernandez-Lobato +4

The paper introduces a standardized machine‑learning benchmarking framework for predicting lipid‑nanoparticle transfection efficiency from ionizable lipid structures, evaluating ma…

cs.LG2026

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…

cs.CR20261 cited

Kick Bad Guys Out! Conditionally Activated Anomaly Detection in Federated Learning with Zero-Knowledge Proof Verification

Shanshan Han, Wenxuan Wu, Baturalp Buyukates +4

Federated Learning (FL) systems are susceptible to adversarial attacks, such as model poisoning attacks and backdoor attacks. Existing defense mechanisms face critical limitations…

cs.LG2026

Enabling Weak Client Participation via On-device Knowledge Distillation in Heterogeneous Federated Learning

Jihyun Lim, Junhyuk Jo, Tuo Zhang +1

Online Knowledge Distillation (KD) is recently highlighted to train large models in Federated Learning (FL) environments. Many existing studies adopt the logit ensemble method to p…

cs.LG2025

FALCON: An ML Framework for Fully Automated Layout-Constrained Analog Circuit Design

Asal Mehradfar, Xuzhe Zhao, Yilun Huang +5

Designing analog circuits from performance specifications is a complex, multi-stage process encompassing topology selection, parameter inference, and layout feasibility. We introdu…