37 citations · 37 across the 7 of their papers we have counts for
7 papers
Toward Auto-Research: Mining Falsifiable Research Ideas from Paper Knowledge Graphs with Categorical Structure
Yuchen Wang, Zhongzhi Luan
Automated research-idea generation systems built on large language models (LLMs) share a structural weakness: they reduce ideation to free-text recombination, random paper pairing,…
Closed-Loop Control with Rule-Aligned Small Language Models and Multi-Agent Self-Correction
Yuchen Wang, Javal Vyas, Tong Liu +1
A key step toward autonomous industrial operation is the ability to create and reconfigure control policies from natural-language requirement specifications, with minimal or no man…
PARNESS: A Paper Harness for End-to-End Automated Scientific Research with Dynamic Workflows, Full-Text Indexing, and Cross-Run Knowledge Accumulation
Yuchen Wang, Zhongzhi Luan
Recent autonomous research systems -- AI-Scientist, PaperOrchestra, AutoSOTA, DeepResearch, InternAgent, ResearchAgent and others -- show LLM agents can ideate, run experiments and…
Nemobot Games: Crafting Strategic AI Gaming Agents for Interactive Learning with Large Language Models
Chee Wei Tan, Yuchen Wang, Shangxin Guo
This paper introduces a new paradigm for AI game programming, leveraging large language models (LLMs) to extend and operationalize Claude Shannon's taxonomy of game-playing machine…
Future-Proofing Programmers: Optimal Knowledge Tracing for AI-Assisted Personalized Education
Yuchen Wang, Pei-Duo Yu, Chee Wei Tan
Learning to learn is becoming a science, driven by the convergence of knowledge tracing, signal processing, and generative AI to model student learning states and optimize educatio…
From Code Generation to Software Testing: AI Copilot with Context-Based RAG
Yuchen Wang, Shangxin Guo, Chee Wei Tan
The rapid pace of large-scale software development places increasing demands on traditional testing methodologies, often leading to bottlenecks in efficiency, accuracy, and coverag…
Contextual Augmented Multi-Model Programming (CAMP): A Hybrid Local-Cloud Copilot Framework
Yuchen Wang, Shangxin Guo, Chee Wei Tan
The advancements in cloud-based Large Languages Models (LLMs) have revolutionized AI-assisted programming. However, their integration into certain local development environments li…