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Found 17 papers, 1 papers with code
MRF-Chat: Improving Dialogue with Markov Random Fields
Recent state-of-the-art approaches in open-domain dialogue include training end-to-end deep-learning models to learn various conversational features like emotional content of response, symbolic transitions of dialogue contexts in a knowledge graph and persona of the agent and the user, among others.
AI Audit: A Card Game to Reflect on Everyday AI Systems
The game mechanics reward systems that are ethically developed or that take steps to mitigate potential harms.
Modeling Empathic Similarity in Personal Narratives
The most meaningful connections between people are often fostered through expression of shared vulnerability and emotional experiences in personal narratives.
HIINT: Historical, Intra- and Inter- personal Dynamics Modeling with Cross-person Memory Transformer
Accurately modeling affect dynamics, which refers to the changes and fluctuations in emotions and affective displays during human conversations, is crucial for understanding human interactions.
Constructing Dreams using Generative AI
Generative AI tools introduce new and accessible forms of media creation for youth.
Multipar-T: Multiparty-Transformer for Capturing Contingent Behaviors in Group Conversations
As we move closer to real-world AI systems, AI agents must be able to deal with multiparty (group) conversations.
Adversarial Transformer Language Models for Contextual Commonsense Inference
Contextualized or discourse aware commonsense inference is the task of generating coherent commonsense assertions (i. e., facts) from a given story, and a particular sentence from that story.
Joint Engagement Classification using Video Augmentation Techniques for Multi-person Human-robot Interaction
This work serves as the first step toward fully unlocking the potential of end-to-end video understanding models pre-trained on large public datasets and augmented with data augmentation and visualization techniques for affect recognition in the multi-person human-robot interaction in the wild.
Build-a-Bot: Teaching Conversational AI Using a Transformer-Based Intent Recognition and Question Answering Architecture
As such, we propose the development of an open-source tool (Build-a-Bot) for students and teachers to not only create their own transformer-based chatbots based on their own course material, but also learn the fundamentals of AI through the model creation process.
B$^3$RTDP: A Belief Branch and Bound Real-Time Dynamic Programming Approach to Solving POMDPs
Partially Observable Markov Decision Processes (POMDPs) offer a promising world representation for autonomous agents, as they can model both transitional and perceptual uncertainties.
Explainable AI for Suicide Risk Assessment Using Eye Activities and Head Gestures
The prevalence of suicide has been on the rise since the 20th century, causing severe emotional damage to individuals, families, and communities alike.
Introducing Variational Autoencoders to High School Students
Generative Artificial Intelligence (AI) models are a compelling way to introduce K-12 students to AI education using an artistic medium, and hence have drawn attention from K-12 AI educators.
RetroGAN: A Cyclic Post-Specialization System for Improving Out-of-Knowledge and Rare Word Representations
Retrofitting is a technique used to move word vectors closer together or further apart in their space to reflect their relationships in a Knowledge Base (KB).
Combining pre-trained language models and structured knowledge
In recent years, transformer-based language models have achieved state of the art performance in various NLP benchmarks.
Migratable AI : Investigating users' affect on identity and information migration of a conversational AI agent
Conversational AI agents are becoming ubiquitous and provide assistance to us in our everyday activities.
Migratable AI: Personalizing Dialog Conversations with migration context
The migration of conversational AI agents across different embodiments in order to maintain the continuity of the task has been recently explored to further improve user experience.
Dyadic Speech-based Affect Recognition using DAMI-P2C Parent-child Multimodal Interaction Dataset
Automatic speech-based affect recognition of individuals in dyadic conversation is a challenging task, in part because of its heavy reliance on manual pre-processing.
