{"type":"rich","version":"1.0","provider_name":"Transistor","provider_url":"https://transistor.fm","author_name":"TalkRL: The Reinforcement Learning Podcast","title":"Sharath Chandra Raparthy","html":"<iframe width=\"100%\" height=\"180\" frameborder=\"no\" scrolling=\"no\" seamless src=\"https://share.transistor.fm/e/f4b1c7d2\"></iframe>","width":"100%","height":180,"duration":2441,"description":"Sharath Chandra Raparthy on In-Context Learning for Sequential Decision Tasks, GFlowNets, and more!  \nSharath Chandra Raparthy is an AI Resident at FAIR at Meta, and did his Master's at Mila.  \n\nFeatured Reference \n\nGeneralization to New Sequential Decision Making Tasks with In-Context Learning   \nSharath Chandra Raparthy , Eric Hambro, Robert Kirk , Mikael Henaff, , Roberta Raileanu \nAdditional References  \nSharath Chandra Raparthy Homepage  \nHuman-Timescale Adaptation in an Open-Ended Task Space, Adaptive Agent Team 2023\nData Distributional Properties Drive Emergent In-Context Learning in Transformers, Chan et al 2022  \nDecision Transformer: Reinforcement Learning via Sequence Modeling, Chen et al  2021","thumbnail_url":"https://img.transistorcdn.com/jXB1-VPK-A9v1epzc4aG4pFxqlvo2vbQ_Ytyuar_gPI/rs:fill:0:0:1/w:400/h:400/q:60/mb:500000/aHR0cHM6Ly9pbWct/dXBsb2FkLXByb2R1/Y3Rpb24udHJhbnNp/c3Rvci5mbS9zaG93/LzIwNDcvMTcwNzk1/NDcxMS1hcnR3b3Jr/LmpwZw.webp","thumbnail_width":300,"thumbnail_height":300}