TL;DR
MEPO-SLM is presented, a framework that reformulates prompt engineering for SLMs as a four-objective Pareto problem over task inaccuracy, and Phi-3-mini and Gemma-2B on English TriviaQA and Arabic medical QA, and TinyLlama-1.1B on TriviaQA only are evaluated.
This survey systematically reviews PEFT methods that update only 0.1–5% of model parameters while achieving good performance across diverse audio tasks, the first survey to comprehensively examine PEFT techniques specifically for audio foundation models.
Results show that mixer design plays a central role in convergence and solution visibility in FALQON combined with transverse-field, XY, and warm start mixers.
The generalized adaptive bridge regression (GABR) framework successfully identifies optimal, off-grid grouping architectures and is evaluated on simulated architectures, demonstrating its dynamic adaptivity to structural sparsity, collinearity, and varying signal-to-noise ratios.
The causal relationship between two random variables is categorized into four categories: two direct-case cases, two cases in which the variables are independent, and a case in which the variables are confounded by unobserved common causes.
A new computational approach reveals how cells communicate to assemble into tissues. This could accelerate stem cell engineering, improve disease models, and inform therapies.
Zero-knowledge proofs can verify computing results without rerunning workloads or exposing sensitive data. Magnetar helps bring them into the mainstream with support for standard programming languages, major speed gains, and quantum-resistant security. The post Proof-based general-purpose computing with Magnetar appeared first on Microsoft Research.
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