44 citations · 66 across the 7 of their papers we have counts for
12 papers
StyleM: Stylized Metrics for Image Captioning Built with Contrastive N-grams
Chengxi Li, Brent Harrison
In this paper, we build two automatic evaluation metrics for evaluating the association between a machine-generated caption and a ground truth stylized caption: OnlyStyle and Style…
Using Non-Stationary Bandits for Learning in Repeated Cournot Games with Non-Stationary Demand
Kshitija Taywade, Brent Harrison, Judy Goldsmith
Many past attempts at modeling repeated Cournot games assume that demand is stationary. This does not align with real-world scenarios in which market demands can evolve over a prod…
Training Value-Aligned Reinforcement Learning Agents Using a Normative Prior
Md Sultan Al Nahian, Spencer Frazier, Brent Harrison +1
As more machine learning agents interact with humans, it is increasingly a prospect that an agent trained to perform a task optimally, using only a measure of task performance as f…
Influencing Reinforcement Learning through Natural Language Guidance
Tasmia Tasrin, Md Sultan Al Nahian, Habarakadage Perera +1
Interactive reinforcement learning agents use human feedback or instruction to help them learn in complex environments. Often, this feedback comes in the form of a discrete signal…
3M: Multi-style image caption generation using Multi-modality features under Multi-UPDOWN model
Chengxi Li, Brent Harrison
In this paper, we build a multi-style generative model for stylish image captioning which uses multi-modality image features, ResNeXt features and text features generated by DenseC…
Visual Question Answering Using Semantic Information from Image Descriptions
Tasmia Tasrin, Md Sultan Al Nahian, Brent Harrison
In this work, we propose a deep neural architecture that uses an attention mechanism which utilizes region based image features, the natural language question asked, and semantic k…