activity
20162023
most citedCoherent Dialogue with Attention-based Language Models

46 citations · 51 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV20233 cited

NeRFuser: Large-Scale Scene Representation by NeRF Fusion

Jiading Fang, Shengjie Lin, Igor Vasiljevic +5

A practical benefit of implicit visual representations like Neural Radiance Fields (NeRFs) is their memory efficiency: large scenes can be efficiently stored and shared as small ne…

cs.RO20221 cited

N-LIMB: Neural Limb Optimization for Efficient Morphological Design

Charles Schaff, Matthew R. Walter

A robot's ability to complete a task is heavily dependent on its physical design. However, identifying an optimal physical design and its corresponding control policy is inherently…

cs.LG2021

Invariance Through Latent Alignment

Takuma Yoneda, Ge Yang, Matthew R. Walter +1

A robot's deployment environment often involves perceptual changes that differ from what it has experienced during training. Standard practices such as data augmentation attempt to…

cs.CL201646 cited

Coherent Dialogue with Attention-based Language Models

Hongyuan Mei, Mohit Bansal, Matthew R. Walter

We model coherent conversation continuation via RNN-based dialogue models equipped with a dynamic attention mechanism. Our attention-RNN language model dynamically increases the sc…

cs.RO20161 cited

Navigational Instruction Generation as Inverse Reinforcement Learning with Neural Machine Translation

Andrea F. Daniele, Mohit Bansal, Matthew R. Walter

Modern robotics applications that involve human-robot interaction require robots to be able to communicate with humans seamlessly and effectively. Natural language provides a flexi…