Explore Franklin AI
Understand new AI research with readable explanations and links to the original papers.
Rethinking AI Alignment Current AI alignment research typically views self-preservation as a problem to be managed through external constraints.
A Lightweight Multi-Agent Framework for Automated Concrete Barrier Design Designing reinforced concrete highway barriers is a complex, safety-critical task t...
IntElicit: Eliciting and Assessing Contextualized Creativity via Dialogue Policy Optimization This paper introduces IntElicit, an AI-driven framework designe...
A Five-Plane Reference Architecture for Runtime Governance of Production AI Agents addresses the critical security gap created by AI agents in enterprise env...
PROJECTMEM: A Local-First, Event-Sourced Memory and Judgment Layer for AI Coding Agents AI coding assistants are highly effective during a single session, bu...
Automating compliance checking for complex building regulations is a major challenge in the Architecture, Engineering, and Construction (AEC) industry.
Towards Responsibly Non-Compliant Machines This paper explores the challenge of engineering autonomous intelligent agents that can "responsibly" refuse user...
The Impossibility of Eliciting Latent Knowledge This paper investigates the challenge of Eliciting Latent Knowledge (ELK), which is the problem of training a...
Nonslop: A Gamified Experiment in Human-AI Collaborative Writing explores how people interact with AI writing assistants when those assistants are framed as...
Superficial Beliefs in LLM Decision-Making This research investigates whether Large Language Models (LLMs) possess a genuine, structured internal logic when...
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.
