2.4k citations · 3k across the 56 of their papers we have counts for
5 papers · 1 filter
Continual Learning for Instruction Following from Realtime Feedback
Alane Suhr, Yoav Artzi
We propose and deploy an approach to continually train an instruction-following agent from feedback provided by users during collaborative interactions. During interaction, human u…
Abstract Visual Reasoning with Tangram Shapes
Anya Ji, Noriyuki Kojima, Noah Rush +4
We introduce KiloGram, a resource for studying abstract visual reasoning in humans and machines. Drawing on the history of tangram puzzles as stimuli in cognitive science, we build…
lilGym: Natural Language Visual Reasoning with Reinforcement Learning
Anne Wu, Kianté Brantley, Noriyuki Kojima +1
We present lilGym, a new benchmark for language-conditioned reinforcement learning in visual environments. lilGym is based on 2,661 highly-compositional human-written natural langu…
Wav2Seq: Pre-training Speech-to-Text Encoder-Decoder Models Using Pseudo Languages
Felix Wu, Kwangyoun Kim, Shinji Watanabe +4
We introduce Wav2Seq, the first self-supervised approach to pre-train both parts of encoder-decoder models for speech data. We induce a pseudo language as a compact discrete repres…
Simulating Bandit Learning from User Feedback for Extractive Question Answering
Ge Gao, Eunsol Choi, Yoav Artzi
We study learning from user feedback for extractive question answering by simulating feedback using supervised data. We cast the problem as contextual bandit learning, and analyze…