most citedExpert-level protocol translation for self-driving labs

1 citations · 3 across the 4 of their papers we have counts for

collaborators

5 papers

cs.AI20251 cited

Automated Constraint Specification for Job Scheduling by Regulating Generative Model with Domain-Specific Representation

Yu-Zhe Shi, Qiao Xu, Yanjia Li +4

Advanced Planning and Scheduling (APS) systems have become indispensable for modern manufacturing operations, enabling optimized resource allocation and production efficiency in in…

cs.CL2025

Targeted control of fast prototyping through domain-specific interface

Yu-Zhe Shi, Mingchen Liu, Hanlu Ma +5

Industrial designers have long sought a natural and intuitive way to achieve the targeted control of prototype models -- using simple natural language instructions to configure and…

cs.AI20251 cited

Hierarchically Encapsulated Representation for Protocol Design in Self-Driving Labs

Yu-Zhe Shi, Mingchen Liu, Fanxu Meng +5

Self-driving laboratories have begun to replace human experimenters in performing single experimental skills or predetermined experimental protocols. However, as the pace of idea i…

cs.RO20241 cited

Expert-level protocol translation for self-driving labs

Yu-Zhe Shi, Fanxu Meng, Haofei Hou +4

Recent development in Artificial Intelligence (AI) models has propelled their application in scientific discovery, but the validation and exploration of these discoveries require s…

cs.RO2024

Abstract Hardware Grounding towards the Automated Design of Automation Systems

Yu-Zhe Shi, Qiao Xu, Fanxu Meng +2

Crafting automation systems tailored for specific domains requires aligning the space of human experts' semantics with the space of robot executable actions, and scheduling the req…