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Found 8 papers, 3 papers with code
Chat, Shift and Perform: Bridging the Gap between Task-oriented and Non-task-oriented Dialog Systems
We propose CASPER (ChAt, Shift and PERform), a novel dialog system consisting of three types of dialog models: chatter, shifter, and performer.
LatteGAN: Visually Guided Language Attention for Multi-Turn Text-Conditioned Image Manipulation
Previous models for this task successfully generate images iteratively, given a sequence of instructions and a previously generated image.
Ranked #1 on
Text-to-Image Generation
on GeNeVA (CoDraw)
d3rlpy: An Offline Deep Reinforcement Learning Library
In this paper, we introduce d3rlpy, an open-sourced offline deep reinforcement learning (RL) library for Python.
Unified Questioner Transformer for Descriptive Question Generation in Goal-Oriented Visual Dialogue
In addition, we build a goal-oriented visual dialogue task called CLEVR Ask.
SLAM-Inspired Simultaneous Contextualization and Interpreting for Incremental Conversation Sentences
In many methods, however, only one meaning is considered for one label of a word, and multiple meanings of polysemous words depending on the context are rarely handled.
Temporal Difference Weighted Ensemble For Reinforcement Learning
Combining multiple function approximators in machine learning models typically leads to better performance and robustness compared with a single function.
Autonomous Self-Explanation of Behavior for Interactive Reinforcement Learning Agents
In cooperation, the workers must know how co-workers behave.
Bayesian Inference of Self-intention Attributed by Observer
Most of agents that learn policy for tasks with reinforcement learning (RL) lack the ability to communicate with people, which makes human-agent collaboration challenging.
