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Found 27 papers, 4 papers with code
Fast and Slow Planning
The concept of Artificial Intelligence has gained a lot of attention over the last decade.
Advances in Automatically Rating the Trustworthiness of Text Processing Services
Then, we will outline challenges and vision for a principled, multi-modal, causality-based rating methodologies and its implication for decision-support in real-world scenarios like health and food recommendation.
Rating Sentiment Analysis Systems for Bias through a Causal Lens
Sentiment Analysis Systems (SASs) are data-driven Artificial Intelligence (AI) systems that, given a piece of text, assign one or more numbers conveying the polarity and emotional intensity expressed in the input.
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.
Plansformer: Generating Symbolic Plans using Transformers
Large Language Models (LLMs) have been the subject of active research, significantly advancing the field of Natural Language Processing (NLP).
A Dataset and Baseline Approach for Identifying Usage States from Non-Intrusive Power Sensing With MiDAS IoT-based Sensors
The state identification problem seeks to identify power usage patterns of any system, like buildings or factories, of interest.
A Rich Recipe Representation as Plan to Support Expressive Multi Modal Queries on Recipe Content and Preparation Process
This demands a need for better representation of the recipes, overcoming the ambiguity and sparseness that exists in the current textual documents.
Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environments
Current AI systems lack several important human capabilities, such as adaptability, generalizability, self-control, consistency, common sense, and causal reasoning.
ULTRA: A Data-driven Approach for Recommending Team Formation in Response to Proposal Calls
We introduce an emerging AI-based approach and prototype system for assisting team formation when researchers respond to calls for proposals from funding agencies.
Thinking Fast and Slow in AI: the Role of Metacognition
AI systems have seen dramatic advancement in recent years, bringing many applications that pervade our everyday life.
E-PDDL: A Standardized Way of Defining Epistemic Planning Problems
Epistemic Planning (EP) refers to an automated planning setting where the agent reasons in the space of knowledge states and tries to find a plan to reach a desirable state from the current state.
"Who can help me?": Knowledge Infused Matching of Support Seekers and Support Providers during COVID-19 on Reddit
During the ongoing COVID-19 crisis, subreddits on Reddit, such as r/Coronavirus saw a rapid growth in user's requests for help (support seekers - SSs) including individuals with varying professions and experiences with diverse perspectives on care (support providers - SPs).
Did Chatbots Miss Their 'Apollo Moment'? A Survey of the Potential, Gaps and Lessons from Using Collaboration Assistants During COVID-19
Artificial Intelligence (AI) technologies have long been positioned as a tool to provide crucial data-driven decision support to people.
Thinking Fast and Slow in AI
This paper proposes a research direction to advance AI which draws inspiration from cognitive theories of human decision making.
SWOW-8500: Word Association task for Intrinsic Evaluation of Word Embeddings
Downstream evaluation of pretrained word embeddings is expensive, more so for tasks where current state of the art models are very large architectures.
Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering
While machine learning (ML) models are being increasingly trusted to make decisions in different and varying areas, the safety of systems using such models has become an increasing concern.
Tentacular Artificial Intelligence, and the Architecture Thereof, Introduced
We briefly introduce herein a new form of distributed, multi-agent artificial intelligence, which we refer to as "tentacular."
A Train Status Assistant for Indian Railways
Trains are part-and-parcel of every day lives in countries with large, diverse, multi-lingual population like India.
Trusted Multi-Party Computation and Verifiable Simulations: A Scalable Blockchain Approach
Large-scale computational experiments, often running over weeks and over large datasets, are used extensively in fields such as epidemiology, meteorology, computational biology, and healthcare to understand phenomena, and design high-stakes policies affecting everyday health and economy.
Decision-support for the Masses by Enabling Conversations with Open Data
Open data refers to data that is freely available for reuse.
Towards Composable Bias Rating of AI Services
The possibly biased behavior of a service is hard to detect and handle if the AI service is merely being used and not developed from scratch, since the training data set is not available.
Estimating Train Delays in a Large Rail Network Using a Zero Shot Markov Model
India runs the fourth largest railway transport network size carrying over 8 billion passengers per year.
On Chatbots Exhibiting Goal-Directed Autonomy in Dynamic Environments
Conversation interfaces (CIs), or chatbots, are a popular form of intelligent agents that engage humans in task-oriented or informal conversation.
Toward Cognitive and Immersive Systems: Experiments in a Cognitive Microworld
These \textit{cognitive and immersive systems} (CAISs) fall squarely into the intersection of AI with HCI/HRI: such systems interact with and assist the human agents that enter them, in no small part because such systems are infused with AI able to understand and reason about these humans and their knowledge, beliefs, goals, communications, plans, etc.
Workflow Complexity for Collaborative Interactions: Where are the Metrics? -- A Challenge
In this paper, we introduce the problem of denoting and deriving the complexity of workflows (plans, schedules) in collaborative, planner-assisted settings where humans and agents are trying to jointly solve a task.
Visualizations for an Explainable Planning Agent
In this paper, we report on the visualization capabilities of an Explainable AI Planning (XAIP) agent that can support human in the loop decision making.
A Measure for Dialog Complexity and its Application in Streamlining Service Operations
Dialog is a natural modality for interaction between customers and businesses in the service industry.
