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Found 14 papers, 2 papers with code
Evaluating Chatbots to Promote Users' Trust -- Practices and Open Problems
Chatbots, the common moniker for collaborative assistants, are Artificial Intelligence (AI) software that enables people to naturally interact with them to get tasks done.
A Planning Ontology to Represent and Exploit Planning Knowledge for Performance Efficiency
Ontologies are known for their ability to organize rich metadata, support the identification of novel insights via semantic queries, and promote reuse.
IERL: Interpretable Ensemble Representation Learning -- Combining CrowdSourced Knowledge and Distributed Semantic Representations
Crowdsourced and expert-curated knowledge graphs such as ConceptNet are designed to capture the meaning of words from a compact set of well-defined contexts.
Knowledge-Infused Self Attention Transformers
However, the ad-hoc nature of existing methods makes it difficult to properly analyze the effects of knowledge infusion on the many moving parts or components of a transformer.
Process Knowledge-infused Learning for Clinician-friendly Explanations
In this study, we introduce Process Knowledge-infused Learning (PK-iL), a new learning paradigm that layers clinical process knowledge structures on language model outputs, enabling clinician-friendly explanations of the underlying language model predictions.
Explainable Artificial Intelligence (XAI)
Language Modelling
Cook-Gen: Robust Generative Modeling of Cooking Actions from Recipes
In this study, we explore the use of generative AI methods to extend current food computation models, primarily involving the analysis of nutrition and ingredients, to also incorporate cooking actions (e. g., add salt, fry the meat, boil the vegetables, etc.).
Knowledge Graph Guided Semantic Evaluation of Language Models For User Trust
However, they do not ascribe object and concept-level meaning and semantics to the learned stochastic patterns such as those described in knowledge graphs.
On Safe and Usable Chatbots for Promoting Voter Participation
Chatbots, or bots for short, are multi-modal collaborative assistants that can help people complete useful tasks.
KSAT: Knowledge-infused Self Attention Transformer -- Integrating Multiple Domain-Specific Contexts
Domain-specific language understanding requires integrating multiple pieces of relevant contextual information.
Learning to Automate Follow-up Question Generation using Process Knowledge for Depression Triage on Reddit Posts
We demonstrate the challenge of using existing datasets to train a DLM for generating FQs that adhere to clinical process knowledge.
Interpretable Design of Reservoir Computing Networks using Realization Theory
The reservoir computing networks (RCNs) have been successfully employed as a tool in learning and complex decision-making tasks.
Learning to Control using Image Feedback
Learning to control complex systems using non-traditional feedback, e. g., in the form of snapshot images, is an important task encountered in diverse domains such as robotics, neuroscience, and biology (cellular systems).
Cooperative Deep $Q$-learning Framework for Environments Providing Image Feedback
In this paper, we address two key challenges in deep reinforcement learning setting, sample inefficiency and slow learning, with a dual NN-driven learning approach.
Plan or not: Remote Human-robot Teaming with Incomplete Task Information
While information asymmetry can be desirable sometimes, it may also lead to the robot choosing improper actions that negatively influence the teaming performance.
