Explore Franklin AI
Understand new AI research with readable explanations and links to the original papers.
Think Thrice Before You Speak: Dual knowledge-enhanced Theory-of-Mind Reasoning for Persuasive Agents explores how AI can become more effective at persuasion...
Claw AI Lab: An Autonomous Multi-Agent Research Team Claw AI Lab is an autonomous research platform designed to transform the process of scientific discovery...
A Subjective Logic-based method for runtime confidence updates in safety arguments This paper introduces a new approach to dynamic quantitative assurance, de...
Deep Reinforcement Learning for Flexible Job Shop Scheduling with Random Job Arrivals This paper addresses the Flexible Job Shop Scheduling Problem (FJSP), w...
Meta-Learning for Rapid Adaptation in Reference Tracking of Uncertain Nonlinear Systems This paper introduces a meta-learning framework designed to help cont...
Forecasting Scientific Progress with Artificial Intelligence This paper investigates whether modern artificial intelligence can accurately predict the trajec...
TerminalWorld: Benchmarking Agents on Real-World Terminal Tasks TerminalWorld is a new data engine designed to evaluate how well autonomous AI agents perform...
Search-E1: Self-Distillation Drives Self-Evolution in Search-Augmented Reasoning Search-E1 is a new method designed to improve how language models perform co...
Large language models (LLMs) are increasingly used as automated judges for tasks like code review, content moderation, and grading.
MOSS: Self-Evolution through Source-Level Rewriting in Autonomous Agent Systems Autonomous agentic systems often become static after deployment, meaning they...
Start with the overview to understand the paper’s main idea, then follow its original paper link for the methods, results and limitations.
Use Submit Research to send the original paper URL and explain why it is useful. An editor reviews the suggestion before publication.
