ReallyUnderstandPapers.com: Autonomous AI Research Agent & Pedagogical Paper Coach
“An autonomous, agentic research assistant and pedagogical paper coach built on decoupled React/FastAPI architectures, LangGraph, and MCP with Reflexion-style self-critique loops, literature cross-verification, and sandboxed interactive code execution.”
Project Scope & Details
ReallyUnderstandPapers.com moves beyond conventional RAG chatbots by employing a genuine Reflexion-style self-critique loop, automated literature cross-checking, and interactive sandboxed coding challenges.
It ingests academic papers, autonomously researches context across academic indexes (alphaXiv, Semantic Scholar, Tavily), verifies empirical claims, and coaches users through three distinct engagement tracks: Learn (scaffolded code stubs executing in isolated E2B sandboxes against unit tests), Prototype (generating runnable downscaled implementations), and Twist (verifying user-proposed algorithmic modifications via MCP literature search before coding).
Multi-Agent Research Paper Comprehension
Hierarchical agentic architecture decomposing complex academic manuscripts into mathematical premises and empirical claims.
Sandboxed Dynamic Code Verification
Executes and verifies paper implementation snippets in isolated Linux environments without hallucinated outcomes.
Interactive Socratic Mathematical Coach
Guides researchers through rigorous step-by-step proofs and derivation verification with interactive feedback.
Hallucination-Resistant Citation Grounding
Strictly anchors all explanations to verified PDF page and line coordinates, preventing synthetic fabrications.
ReallyUnderstandPapers Interactive Coach
Scaffolded Paper Coaching: An Agentic Reflexion Framework for Interactive Academic Code Replication
Authors: Chaitanya Anand, Himangshu Sarma
- Chaitanya Anand
- Dr. Himangshu Sarma