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Found 9 papers, 1 papers with code
The MeMAD Submission to the WMT18 Multimodal Translation Task
Our experiments show that the effect of the visual features in our system is small.
#MeToo on Campus: Studying College Sexual Assault at Scale Using Data Reported on Social Media
Recently, the emergence of the #MeToo trend on social media has empowered thousands of people to share their own sexual harassment experiences.
The Ivory Tower Lost: How College Students Respond Differently than the General Public to the COVID-19 Pandemic
Recently, the pandemic of the novel Coronavirus Disease-2019 (COVID-19) has presented governments with ultimate challenges.
RAIST: Learning Risk Aware Traffic Interactions via Spatio-Temporal Graph Convolutional Networks
A key aspect of driving a road vehicle is to interact with other road users, assess their intentions and make risk-aware tactical decisions.
SeekNet: Improved Human Instance Segmentation and Tracking via Reinforcement Learning Based Optimized Robot Relocation
Amodal recognition is the ability of the system to detect occluded objects.
DroNeRF: Real-time Multi-agent Drone Pose Optimization for Computing Neural Radiance Fields
Using drones in conjunction with NeRF provides a unique and dynamic way to generate novel views of a scene, especially with limited scene capabilities of restricted movements.
Optimizing Crowd-Aware Multi-Agent Path Finding through Local Broadcasting with Graph Neural Networks
Multi-Agent Path Finding (MAPF) in crowded environments presents a challenging problem in motion planning, aiming to find collision-free paths for all agents in the system.
DREAM: Decentralized Reinforcement Learning for Exploration and Efficient Energy Management in Multi-Robot Systems
This paper introduces DREAM - Decentralized Reinforcement Learning for Exploration and Efficient Energy Management in Multi-Robot Systems, a comprehensive framework that optimizes the allocation of resources for efficient exploration.
RL Dreams: Policy Gradient Optimization for Score Distillation based 3D Generation
Further, the recent work of Denoising Diffusion Policy Optimization (DDPO) demonstrates that the diffusion process is compatible with policy gradient methods and has been demonstrated to improve the 2D diffusion models using an aesthetic scoring function.
