1 citations · 1 across the 4 of their papers we have counts for
4 papers
Meta Flow Maps enable scalable reward alignment
Peter Potaptchik, Adhi Saravanan, Abbas Mammadov +3
Controlling generative models is computationally expensive. This is because optimal alignment with a reward function--whether via inference-time steering or fine-tuning--requires e…
Beyond Prototyping: Autonomous, Enterprise-Grade Frontend Development from Pixel to Production via a Specialized Multi-Agent Framework
Ramprasath Ganesaraja, Swathika N, Saravanan AP +19
We present AI4UI, a framework of autonomous front-end development agents purpose-built to meet the rigorous requirements of enterprise-grade application delivery. Unlike general-pu…
Locking Machine Learning Models into Hardware
Eleanor Clifford, Adhithya Saravanan, Harry Langford +5
Modern machine learning (ML) models are expensive IP and business competitiveness often depends on keeping this IP confidential. This in turn restricts how these models are deploye…
RFBTD: RFB Text Detector
Christen M, AB Saravanan
Text detection plays a critical role in the whole procedure of textual information extraction and understanding. On a high note, recent years have seen a surge in the high recall t…