4 papers · 1 filter
Abstract Reward Processes: Leveraging State Abstraction for Consistent Off-Policy Evaluation
Shreyas Chaudhari, Ameet Deshpande, Bruno Castro da Silva +1
Evaluating policies using off-policy data is crucial for applying reinforcement learning to real-world problems such as healthcare and autonomous driving. Previous methods for off-…
GEO: Generative Engine Optimization
Pranjal Aggarwal, Vishvak Murahari, Tanmay Rajpurohit +3
The advent of large language models (LLMs) has ushered in a new paradigm of search engines that use generative models to gather and summarize information to answer user queries. Th…
QualEval: Qualitative Evaluation for Model Improvement
Vishvak Murahari, Ameet Deshpande, Peter Clark +4
Quantitative evaluation metrics have traditionally been pivotal in gauging the advancements of artificial intelligence systems, including large language models (LLMs). However, the…
RLHF Deciphered: A Critical Analysis of Reinforcement Learning from Human Feedback for LLMs
Shreyas Chaudhari, Pranjal Aggarwal, Vishvak Murahari +5
State-of-the-art large language models (LLMs) have become indispensable tools for various tasks. However, training LLMs to serve as effective assistants for humans requires careful…