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Found 40 papers, 4 papers with code
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.
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.
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.
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.
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.
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.
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.
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.
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.
Decision-support for the Masses by Enabling Conversations with Open Data
Open data refers to data that is freely available for reuse.
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.
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."
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.
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.
"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).
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.
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.
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.
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.
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).
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.
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.
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.
Fast and Slow Planning
The concept of Artificial Intelligence has gained a lot of attention over the last decade.
Towards Explainable and Safe Conversational Agents for Mental Health: A Survey
Virtual Mental Health Assistants (VMHAs) are seeing continual advancements to support the overburdened global healthcare system that gets 60 million primary care visits, and 6 million Emergency Room (ER) visits annually.
Understanding the Capabilities of Large Language Models for Automated Planning
Firstly, we want to understand the extent to which LLMs can be used for plan generation.
Can LLMs be Good Financial Advisors?: An Initial Study in Personal Decision Making for Optimized Outcomes
Increasingly powerful Large Language Model (LLM) based chatbots, like ChatGPT and Bard, are becoming available to users that have the potential to revolutionize the quality of decision-making achieved by the public.
Value-based Fast and Slow AI Nudging
Values that are relevant to a specific decision scenario are used to decide when and how to use each of these nudging modalities.
On Solving the Rubik's Cube with Domain-Independent Planners Using Standard Representations
The fastest solver today for RC is DeepCubeA with a custom representation, and another approach is with Scorpion planner with State-Action-Space+ (SAS+) representation.
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.
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.
Promoting Research Collaboration with Open Data Driven Team Recommendation in Response to Call for Proposals
Building teams and promoting collaboration are two very common business activities.
On Learning with LAD
The logical analysis of data, LAD, is a technique that yields two-class classifiers based on Boolean functions having disjunctive normal form (DNF) representation.
On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS)
Automated Planning and Scheduling is among the growing areas in Artificial Intelligence (AI) where mention of LLMs has gained popularity.
Trust and ethical considerations in a multi-modal, explainable AI-driven chatbot tutoring system: The case of collaboratively solving Rubik's Cube
Artificial intelligence (AI) has the potential to transform education with its power of uncovering insights from massive data about student learning patterns.
From Cloud to Edge: Rethinking Generative AI for Low-Resource Design Challenges
Generative Artificial Intelligence (AI) has shown tremendous prospects in all aspects of technology, including design.
The Case for Developing a Foundation Model for Planning-like Tasks from Scratch
Foundation Models (FMs) have revolutionized many areas of computing, including Automated Planning and Scheduling (APS).
