collaborators

6 papers

cs.AI2026

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…

cs.SE2026

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…

cs.AI2026

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…

cs.AI2025

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…

cs.SE2025

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…

cs.AI2025

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…