Search Results for author:
Found 7 papers, 4 papers with code
Depth by Poking: Learning to Estimate Depth from Self-Supervised Grasping
Our network predicts, for each pixel in an input image, the z position that a robot's end effector would reach if it attempted to grasp or poke at the corresponding position.
Neural Assistant: Joint Action Prediction, Response Generation, and Latent Knowledge Reasoning
In this paper, we develop Neural Assistant: a single neural network model that takes conversation history and an external knowledge source as input and jointly produces both text response and action to be taken by the system as output.
Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset
A significant barrier to progress in data-driven approaches to building dialog systems is the lack of high quality, goal-oriented conversational data.
Parallel Scheduled Sampling
Experimentally, we find the proposed technique leads to equivalent or better performance on image generation, summarization, dialog generation, and translation compared to teacher-forced training.
Assessing The Factual Accuracy of Generated Text
We propose a model-based metric to estimate the factual accuracy of generated text that is complementary to typical scoring schemes like ROUGE (Recall-Oriented Understudy for Gisting Evaluation) and BLEU (Bilingual Evaluation Understudy).
Generating Wikipedia by Summarizing Long Sequences
We show that generating English Wikipedia articles can be approached as a multi- document summarization of source documents.
Imitation Learning from Visual Data with Multiple Intentions
In this paper we present an LfD approach for learning multiple modes of behavior from visual data.
