4 papers
Diagnosing Heteroskedasticity and Resolving Multicollinearity Paradoxes in Physicochemical Property Prediction
Malikussaid, Septian Caesar Floresko, Ade Romadhony +3
Lipophilicity (logP) prediction remains central to drug discovery, yet linear regression models for this task frequently violate statistical assumptions in ways that invalidate the…
Bridging the Plausibility-Validity Gap by Fine-Tuning a Reasoning-Enhanced LLM for Chemical Synthesis and Discovery
Malikussaid, Hilal Hudan Nuha, Isman Kurniawan
Large Language Models frequently generate outputs that appear scientifically reasonable yet violate fundamental principles--a phenomenon we characterize as the "plausibility-validi…
VALID-Mol: a Systematic Framework for Validated LLM-Assisted Molecular Design
Malikussaid, Hilal Hudan Nuha, Isman Kurniawan
Large Language Models demonstrate substantial promise for advancing scientific discovery, yet their deployment in disciplines demanding factual precision and specialized domain con…
NAPER: Fault Protection for Real-Time Resource-Constrained Deep Neural Networks
Rian Adam Rajagede, Muhammad Husni Santriaji, Muhammad Arya Fikriansyah +3
Fault tolerance in Deep Neural Networks (DNNs) deployed on resource-constrained systems presents unique challenges for high-accuracy applications with strict timing requirements. M…