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Found 15 papers, 1 papers with code
Dialogue Policies for Confusion Mitigation in Situated HRI
Confusion is a mental state triggered by cognitive disequilibrium that can occur in many types of task-oriented interaction, including Human-Robot Interaction (HRI).
Detecting Interlocutor Confusion in Situated Human-Avatar Dialogue: A Pilot Study
To this end, in this paper, we present our initial research centred on a user-avatar dialogue scenario that we have developed to study the manifestation of confusion and in the long term its mitigation.
Transferring Studies Across Embodiments: A Case Study in Confusion Detection
Human-robot studies are expensive to conduct and difficult to control, and as such researchers sometimes turn to human-avatar interaction in the hope of faster and cheaper data collection that can be transferred to the robot domain.
Self-Supervised Learning for Invariant Representations from Multi-Spectral and SAR Images
This work proposes RSDnet, which applies the distillation network (BYOL) in the remote sensing (RS) domain where data is non-trivially different from natural RGB images.
Data-Driven Reinforcement Learning for Virtual Character Animation Control
Also, compared to existing supervised learning-based animation agents, RLAnimate needs a limited dataset of motion clips to generate representations of valid behaviours during training.
Energy-Based Modelling for Dialogue State Tracking
The uncertainties of language and the complexity of dialogue contexts make accurate dialogue state tracking one of the more challenging aspects of dialogue processing.
Beef Cattle Instance Segmentation Using Fully Convolutional Neural Network
We present an instance segmentation algorithm trained and applied to a CCTV recording of beef cattle during a winter finishing period.
Attentive Language Models
In this paper, we extend Recurrent Neural Network Language Models (RNN-LMs) with an attention mechanism.
Idiom Type Identification with Smoothed Lexical Features and a Maximum Margin Classifier
In our work we address limitations in the state-of-the-art in idiom type identification.
Bootstrapping Labelled Dataset Construction for Cow Tracking and Behavior Analysis
This paper introduces a new approach to the long-term tracking of an object in a challenging environment.
