A Framework for Learning to Request Rich and Contextually Useful Information from Humans

14 October 2021

Papers citing "A Framework for Learning to Request Rich and Contextually Useful Information from Humans"

7 / 7 papers shown

Title
DriVLMe: Enhancing LLM-based Autonomous Driving Agents with Embodied and Social Experiences Yidong Huang Jacob Sansom Ziqiao Ma Felix Gervits Joyce Chai 28 17 0 05 Jun 2024
Evaluating the Faithfulness of Importance Measures in NLP by Recursively Masking Allegedly Important Tokens and Retraining Andreas Madsen Nicholas Meade Vaibhav Adlakha Siva Reddy 93 35 0 15 Oct 2021
TEACh: Task-driven Embodied Agents that Chat Aishwarya Padmakumar Jesse Thomason Ayush Shrivastava P. Lange Anjali Narayan-Chen Spandana Gella Robinson Piramithu Gökhan Tür Dilek Z. Hakkani-Tür LM&Ro 140 179 0 01 Oct 2021
MindCraft: Theory of Mind Modeling for Situated Dialogue in Collaborative Tasks Cristian-Paul Bara Sky CH-Wang J. Chai 59 61 0 13 Sep 2021
Interactive Learning from Activity Description Khanh Nguyen Dipendra Kumar Misra Robert Schapire Miroslav Dudík Patrick Shafto 37 34 0 13 Feb 2021
Help, Anna! Visual Navigation with Natural Multimodal Assistance via Retrospective Curiosity-Encouraging Imitation Learning Khanh Nguyen Hal Daumé LM&Ro EgoV 165 148 0 04 Sep 2019
e-SNLI: Natural Language Inference with Natural Language Explanations Oana-Maria Camburu Tim Rocktaschel Thomas Lukasiewicz Phil Blunsom LRM 249 618 0 04 Dec 2018