most citedLearning Cooperative Visual Dialog Agents with Deep Reinforcement Learning

91 citations · 136 across the 4 of their papers we have counts for

collaborators

5 papers

cs.CV20172 cited

Embodied Question Answering

Abhishek Das, Samyak Datta, Georgia Gkioxari +3

We present a new AI task -- Embodied Question Answering (EmbodiedQA) -- where an agent is spawned at a random location in a 3D environment and asked a question ("What color is the…

cs.HC201738 cited

Evaluating Visual Conversational Agents via Cooperative Human-AI Games

Prithvijit Chattopadhyay, Deshraj Yadav, Viraj Prabhu +5

As AI continues to advance, human-AI teams are inevitable. However, progress in AI is routinely measured in isolation, without a human in the loop. It is crucial to benchmark progr…

cs.CL2017

Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog

Satwik Kottur, José M. F. Moura, Stefan Lee +1

A number of recent works have proposed techniques for end-to-end learning of communication protocols among cooperative multi-agent populations, and have simultaneously found the em…

cs.CV20175 cited

Bidirectional Beam Search: Forward-Backward Inference in Neural Sequence Models for Fill-in-the-Blank Image Captioning

Qing Sun, Stefan Lee, Dhruv Batra

We develop the first approximate inference algorithm for 1-Best (and M-Best) decoding in bidirectional neural sequence models by extending Beam Search (BS) to reason about both for…

cs.CV201791 cited

Learning Cooperative Visual Dialog Agents with Deep Reinforcement Learning

Abhishek Das, Satwik Kottur, José M. F. Moura +2

We introduce the first goal-driven training for visual question answering and dialog agents. Specifically, we pose a cooperative 'image guessing' game between two agents -- Qbot an…