Search Results for author: Biplav Srivastava

Found 42 papers, 4 papers with code

BEACON: Balancing Convenience and Nutrition in Meals With Long-Term Group Recommendations and Reasoning on Multimodal Recipes

no code implementations19 Jun 2024 Vansh Nagpal, Siva Likitha Valluru, Kausik Lakkaraju, Biplav Srivastava

A common, yet regular, decision made by people, whether healthy or with any health condition, is to decide what to have in meals like breakfast, lunch, and dinner, consisting of a combination of foods for appetizer, main course, side dishes, desserts, and beverages.

Multi-Armed Bandits Nutrition

The Case for Developing a Foundation Model for Planning-like Tasks from Scratch

no code implementations6 Apr 2024 Biplav Srivastava, Vishal Pallagani

Foundation Models (FMs) have revolutionized many areas of computing, including Automated Planning and Scheduling (APS).

Scheduling

On Learning with LAD

no code implementations28 Sep 2023 C. A. Jothishwaran, Biplav Srivastava, Jitin Singla, Sugata Gangopadhyay

The logical analysis of data, LAD, is a technique that yields two-class classifiers based on Boolean functions having disjunctive normal form (DNF) representation.

Evaluating Chatbots to Promote Users' Trust -- Practices and Open Problems

no code implementations9 Sep 2023 Biplav Srivastava, Kausik Lakkaraju, Tarmo Koppel, Vignesh Narayanan, Ashish Kundu, Sachindra Joshi

Chatbots, the common moniker for collaborative assistants, are Artificial Intelligence (AI) software that enables people to naturally interact with them to get tasks done.

Chatbot Language Modelling +1

A Planning Ontology to Represent and Exploit Planning Knowledge for Performance Efficiency

no code implementations25 Jul 2023 Bharath Muppasani, Vishal Pallagani, Biplav Srivastava, Raghava Mutharaju, Michael N. Huhns, Vignesh Narayanan

Ontologies are known for their ability to organize rich metadata, support the identification of novel insights via semantic queries, and promote reuse.

On Solving the Rubik's Cube with Domain-Independent Planners Using Standard Representations

no code implementations25 Jul 2023 Bharath Muppasani, Vishal Pallagani, Biplav Srivastava, Forest Agostinelli

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.

Rubik's Cube

Value-based Fast and Slow AI Nudging

no code implementations14 Jul 2023 Marianna B. Ganapini, Francesco Fabiano, Lior Horesh, Andrea Loreggia, Nicholas Mattei, Keerthiram Murugesan, Vishal Pallagani, Francesca Rossi, Biplav Srivastava, Brent Venable

Values that are relevant to a specific decision scenario are used to decide when and how to use each of these nudging modalities.

Can LLMs be Good Financial Advisors?: An Initial Study in Personal Decision Making for Optimized Outcomes

no code implementations8 Jul 2023 Kausik Lakkaraju, Sai Krishna Revanth Vuruma, Vishal Pallagani, Bharath Muppasani, Biplav Srivastava

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.

Decision Making Language Modelling +1

Towards Explainable and Safe Conversational Agents for Mental Health: A Survey

no code implementations25 Apr 2023 Surjodeep Sarkar, Manas Gaur, L. Chen, Muskan Garg, Biplav Srivastava, Bhaktee Dongaonkar

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.

Rating Sentiment Analysis Systems for Bias through a Causal Lens

no code implementations4 Feb 2023 Kausik Lakkaraju, Biplav Srivastava, Marco Valtorta

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.

Fairness Sentiment Analysis

Advances in Automatically Rating the Trustworthiness of Text Processing Services

no code implementations4 Feb 2023 Biplav Srivastava, Kausik Lakkaraju, Mariana Bernagozzi, Marco Valtorta

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.

Food recommendation

On Safe and Usable Chatbots for Promoting Voter Participation

no code implementations16 Dec 2022 Bharath Muppasani, Vishal Pallagani, Kausik Lakkaraju, Shuge Lei, Biplav Srivastava, Brett Robertson, Andrea Hickerson, Vignesh Narayanan

Chatbots, or bots for short, are multi-modal collaborative assistants that can help people complete useful tasks.

Plansformer: Generating Symbolic Plans using Transformers

no code implementations16 Dec 2022 Vishal Pallagani, Bharath Muppasani, Keerthiram Murugesan, Francesca Rossi, Lior Horesh, Biplav Srivastava, Francesco Fabiano, Andrea Loreggia

Large Language Models (LLMs) have been the subject of active research, significantly advancing the field of Natural Language Processing (NLP).

Question Answering Text Generation +2

ULTRA: A Data-driven Approach for Recommending Team Formation in Response to Proposal Calls

no code implementations13 Jan 2022 Biplav Srivastava, Tarmo Koppel, Sai Teja Paladi, Siva Likitha Valluru, Rohit Sharma, Owen Bond

We introduce an emerging AI-based approach and prototype system for assisting team formation when researchers respond to calls for proposals from funding agencies.

E-PDDL: A Standardized Way of Defining Epistemic Planning Problems

no code implementations19 Jul 2021 Francesco Fabiano, Biplav Srivastava, Jonathan Lenchner, Lior Horesh, Francesca Rossi, Marianna Bergamaschi Ganapini

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

no code implementations12 May 2021 Manas Gaur, Kaushik Roy, Aditya Sharma, Biplav Srivastava, Amit Sheth

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).

Natural Language Inference

Did Chatbots Miss Their 'Apollo Moment'? A Survey of the Potential, Gaps and Lessons from Using Collaboration Assistants During COVID-19

no code implementations27 Feb 2021 Biplav Srivastava

Artificial Intelligence (AI) technologies have long been positioned as a tool to provide crucial data-driven decision support to people.

SWOW-8500: Word Association task for Intrinsic Evaluation of Word Embeddings

1 code implementation WS 2019 Avijit Thawani, Biplav Srivastava, Anil Singh

Downstream evaluation of pretrained word embeddings is expensive, more so for tasks where current state of the art models are very large architectures.

General Classification Natural Language Inference +4

Detecting Backdoor Attacks on Deep Neural Networks by Activation Clustering

1 code implementation9 Nov 2018 Bryant Chen, Wilka Carvalho, Nathalie Baracaldo, Heiko Ludwig, Benjamin Edwards, Taesung Lee, Ian Molloy, Biplav Srivastava

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.

Clustering

Tentacular Artificial Intelligence, and the Architecture Thereof, Introduced

no code implementations14 Oct 2018 Selmer Bringsjord, Naveen Sundar Govindarajulu, Atriya Sen, Matthew Peveler, Biplav Srivastava, Kartik Talamadupula

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

no code implementations23 Sep 2018 Himadri Mishra, Ramashish Gaurav, Biplav Srivastava

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

no code implementations22 Sep 2018 Ravi Kiran Raman, Roman Vaculin, Michael Hind, Sekou L. Remy, Eleftheria K. Pissadaki, Nelson Kibichii Bore, Roozbeh Daneshvar, Biplav Srivastava, Kush R. Varshney

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.

Epidemiology

Towards Composable Bias Rating of AI Services

no code implementations31 Jul 2018 Biplav Srivastava, Francesca Rossi

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.

Translation

Estimating Train Delays in a Large Rail Network Using a Zero Shot Markov Model

2 code implementations7 Jun 2018 Ramashish Gaurav, Biplav Srivastava

India runs the fourth largest railway transport network size carrying over 8 billion passengers per year.

regression

On Chatbots Exhibiting Goal-Directed Autonomy in Dynamic Environments

no code implementations26 Mar 2018 Biplav Srivastava

Conversation interfaces (CIs), or chatbots, are a popular form of intelligent agents that engage humans in task-oriented or informal conversation.

Position

Toward Cognitive and Immersive Systems: Experiments in a Cognitive Microworld

no code implementations14 Sep 2017 Matthew Peveler, Naveen Sundar Govindarajulu, Selmer Bringsjord, Biplav Srivastava, Kartik Talamadupula, Hui Su

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.

Visualizations for an Explainable Planning Agent

no code implementations13 Sep 2017 Tathagata Chakraborti, Kshitij P. Fadnis, Kartik Talamadupula, Mishal Dholakia, Biplav Srivastava, Jeffrey O. Kephart, Rachel K. E. Bellamy

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.

Decision Making

Workflow Complexity for Collaborative Interactions: Where are the Metrics? -- A Challenge

no code implementations13 Sep 2017 Kartik Talamadupula, Biplav Srivastava, Jeffrey O. Kephart

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

no code implementations4 Aug 2017 Q. Vera Liao, Biplav Srivastava, Pavan Kapanipathi

Dialog is a natural modality for interaction between customers and businesses in the service industry.

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