5 citations · 9 across the 12 of their papers we have counts for
12 papers
Before the Action: Benchmarking LLMs on Prospective Hypothesis Discovery
Tianyun Zhong, Wangyi Jiang, Wei Wang +15
Large language models (LLMs) excel at answering pre-specified questions, yet their ability to navigate the open-ended, pre-conclusion stage of discovery remains largely unmeasured.…
DLawBench: Evaluating LLMs Through Multi-Turn Legal Consultation
Li Zhang, Yuzhen Shi, Yiran Hu +15
Lawyer-client consultation is a critical starting point for legal services. Effective legal assistance hinges on eliciting sufficient and truthful information from clients in order…
PLawBench: A Rubric-Based Benchmark for Evaluating LLMs in Real-World Legal Practice
Yuzhen Shi, Huanghai Liu, Yiran Hu +27
As large language models (LLMs) are increasingly applied to legal domain-specific tasks, evaluating their ability to perform legal work in real-world settings has become essential.…
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…
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…
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…
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…
Constraint representation towards precise data-driven storytelling
Yu-Zhe Shi, Haotian Li, Lecheng Ruan +1
Data-driven storytelling serves as a crucial bridge for communicating ideas in a persuasive way. However, the manual creation of data stories is a multifaceted, labor-intensive, an…
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…
AutoDSL: Automated domain-specific language design for structural representation of procedures with constraints
Yu-Zhe Shi, Haofei Hou, Zhangqian Bi +4
Accurate representation of procedures in restricted scenarios, such as non-standardized scientific experiments, requires precise depiction of constraints. Unfortunately, Domain-spe…
To think inside the box, or to think out of the box? Scientific discovery via the reciprocation of insights and concepts
Yu-Zhe Shi, Manjie Xu, Wenjuan Han +1
If scientific discovery is one of the main driving forces of human progress, insight is the fuel for the engine, which has long attracted behavior-level research to understand and…
On the Complexity of Bayesian Generalization
Yu-Zhe Shi, Manjie Xu, John E. Hopcroft +6
We consider concept generalization at a large scale in the diverse and natural visual spectrum. Established computational modes (i.e., rule-based or similarity-based) are primarily…