Abstract: Modern language models (LMs) increasingly require two critical resources: computational resources and data resources. Data selection techniques can effectively reduce the amount of training ...

The development of accurate predictive models for SFT would allow the optimization of compound design, which is a key factor for improving the performance of any process involving fluid systems, ...

Abstract: To design the “Kansei value” aspect of a product, it is useful to design multilayered relationships of perceptual and affective responses via the physical or psychophysical properties of the ...

We introduce VeriStruct, a novel framework that extends AI-assisted automated verification from single functions to more complex data structure modules in Verus. VeriStruct employs a planner module to ...

This project investigates token quality from a noisy-label perspective and propose a generic token cleaning pipeline for SFT tasks. Our method filters out uninformative tokens while preserving those ...