Parameter-efficient fine-tuning of large language models using semantic knowledge tuning.

Large Language Models (LLMs) are gaining significant popularity in recent years for specialized tasks using prompts due to their low computational cost. Standard methods like prefix tuning utilize special, modifiable tokens that lack semantic meaning and require extensive training for best performance, often falling short. In this context, we propose a novel method called Semantic Knowledge Tuning (SK-Tuning) for prompt and prefix tuning that employs meaningful words instead of random tokens.

Microbial Evaluation of Plaque on Conventional Stainless Steel Crown and Titanium-coated Stainless Steel Crown on Primary Molars.

Introduction: The extensive plaque formation on dental restoratives may contribute to secondary caries or periodontal inflammation. Therefore, it is important to know how different types of dental restoratives may prevent or promote the accumulation of microorganisms. Hence, this study aims to evaluate the oral hygiene and microbial adhesion on the titanium (Ti)-coated stainless steel crown (Ti-coated SSC) and conventional SSC on a primary molar.

Medication Refill Adherence in Patients with Chronic Inflammatory Eye Disease.

Purpose: To utilize pharmacy dispenses to investigate adherence rates to immunosuppressive therapy (IMT) for the treatment of noninfectious inflammatory eye disease (IED), impact of adherence on disease control, factors associated with nonadherence, and association between adherence in the medical record and pharmacy dispenses.

Method: Retrospective medical chart review was conducted on patients followed for at least 2 years in the uveitis clinic. Appointment and lab attendance, and provider documentation, determined adherence through the medical record.

Search for Soft Unclustered Energy Patterns in Proton-Proton Collisions at 13 TeV.

The first search for soft unclustered energy patterns (SUEPs) is performed using an integrated luminosity of 138  fb^{-1} of proton-proton collision data at sqrt[s]=13  TeV, collected in 2016-2018 by the CMS detector at the LHC. Such SUEPs are predicted by hidden valley models with a new, confining force with a large 't Hooft coupling. In events with boosted topologies, selected by high-threshold hadronic triggers, the multiplicity and sphericity of clustered tracks are used to reject the background from standard model quantum chromodynamics.