CASE is a novel agentic AI system that proactively interviews scam victims using LLMs to collect detailed intelligence, which is then structured for use in scam prevention, resulting in a 21% increase in enforcements on Google Pay India.
The challenges of evaluating LLM appli- cations: An analysis of automated, human, and LLM-based approaches,
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
A semi-structured thematic synthesis identifies core challenges in FM selection, alignment, prompting, orchestration, testing, deployment, and cross-cutting concerns like observability for production-ready FMware.
citing papers explorer
-
CASE: An Agentic AI Framework for Enhancing Scam Intelligence in Digital Payments
CASE is a novel agentic AI system that proactively interviews scam victims using LLMs to collect detailed intelligence, which is then structured for use in scam prevention, resulting in a 21% increase in enforcements on Google Pay India.
-
From Cool Demos to Production-Ready FMware: Core Challenges and a Technology Roadmap
A semi-structured thematic synthesis identifies core challenges in FM selection, alignment, prompting, orchestration, testing, deployment, and cross-cutting concerns like observability for production-ready FMware.