activity
20162025
most citedLoss is its own Reward: Self-Supervision for Reinforcement Learning

91 citations · 115 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CY2025

Evaluating Gemini in an arena for learning

LearnLM Team, Abhinit Modi, Aditya Srikanth Veerubhotla +34

Artificial intelligence (AI) is poised to transform education, but the research community lacks a robust, general benchmark to evaluate AI models for learning. To assess state-of-t…

cs.CY2024★ 4 cited

LearnLM: Improving Gemini for Learning

LearnLM Team, Abhinit Modi, Aditya Srikanth Veerubhotla +43

Today's generative AI systems are tuned to present information by default, rather than engage users in service of learning as a human tutor would. To address the wide range of pote…

cs.CY2024★ 20 cited

Towards Responsible Development of Generative AI for Education: An Evaluation-Driven Approach

Irina Jurenka, Markus Kunesch, Kevin R. McKee +71

A major challenge facing the world is the provision of equitable and universal access to quality education. Recent advances in generative AI (gen AI) have created excitement about…

cs.LG2018

Zero-Shot Visual Imitation

Deepak Pathak, Parsa Mahmoudieh, Guanghao Luo +7

The current dominant paradigm for imitation learning relies on strong supervision of expert actions to learn both 'what' and 'how' to imitate. We pursue an alternative paradigm whe…

cs.LG2016★ 91 cited

Loss is its own Reward: Self-Supervision for Reinforcement Learning

Evan Shelhamer, Parsa Mahmoudieh, Max Argus +1

Reinforcement learning optimizes policies for expected cumulative reward. Need the supervision be so narrow? Reward is delayed and sparse for many tasks, making it a difficult and…