NILLI
Novel Ideas in Learning-to-Learn through Interaction

Workshop @ EMNLP 2023

Collaborative dialogues [1, 2, 3] with automated systems through language interactions have become ubiquitous, wherein it is becoming common from setting an alarm to planning one’s day through language interactions. With recent advances in dialogue research [1, 2, 3], embodied learning [4, 5, 6] and using language as a mode of instruction for learning agents [4, 7, 8] there is, now, a scope for realizing domains that can assume agents with primitive task knowledge and a continual interact-and-learn procedure to systematically acquire knowledge through verbal/non-verbal interactions [9, 10, 11, 12]. The research direction of building interactive learning agents [4, 7, 8, 13] facilitates the possibility of agents to have advanced interactions like taking instructions by being a pragmatic listener, asking for more samples, generating rationales for predictions, interactions to interpret learning dynamics, or even identifying or modifying a new task that can be used towards building effective learning-to-learn mechanisms. In a way, with verbal/non-verbal interactive medium this interdisciplinary field unifies research paradigms of lifelong learning, natural language processing, embodied learning, reinforcement learning, robot learning and multi-modal learning towards building interactive and interpretable AI.

Speakers

Stefanie Tellex Assistant Professor, Brown University	Justin Johnson Assisstant Professor, University of Michigan Research Scientist, Deepmind	Daniel Fried Assistant Professor, Carnegie Mellon University

Katerina Fragkiadaki Assistant Professor, Carnegie Mellon University	Yoav Artzi Associate Professor, Cornell University	Shelia McIlraith Assistant Professor, University of Toronto

Call For Papers

We call for novel, unpublished or in-review works on topics listed in the groups below:

• Language at Fore
  • Novel environments for language understanding through interaction.
  • Language based Reinforcement Learning.
  • Learning representations in grounded language.
  • Language based interaction methods in interdisciplinary research.
• Machine Learning with Interaction
  • Modeling multi-modal and language interactions to aid continual learning.
  • Interactive training for embodied agents.
  • Early and negative results on learning to solve tasks through interaction.
  • Non-verbal/Verbal interactive frameworks.
• Community Impact of Interactive Agents
  • Frontiers in building interactive agents (data, frameworks, open problems).
  • Applications of interactive learning in interdisciplinary research.
  • Security and ethical challenges in interaction based learning.

Important Dates

To be announced

Submission Instructions

To be announced

Schedule

To be announced

Papers Accepted (Poster and Oral)

To be announced

Organizing Committee

Prasanna Parthasarathi Senior Researcher, Huawei Noah's Ark Lab	Koustuv Sinha Research Scientist FAIR	Khyathi Raghavi Chandu NLP Researcher	Chinnadhurai Sankar Research Scientist, FAIR

Adina Williams Research Scientist, FAIR	Sarath Chandar Assistant Professor, École polytechnique de Montréal	Marc-Alexandre Côté Senior researcher, Microsoft Research	Joelle Pineau Associate Professor, McGill University

Program Committee

• Nikita Moghe, University of Edinburgh
• Yuanzhe Pang, New York University
• Saujas Vaduguru, Carnegie Mellon University
• Eric Yuan, MSR Montreal
• Bishal Santra, IIT Kharagpur
• Thao Nguyen, Brown University
• Yu-Siang Wang, University of Toronto
• Darshan Patil, University of Montreal