Bharath Muppasani

Orcid: 0000-0003-3782-8672

According to our database1, Bharath Muppasani authored at least 12 papers between 2022 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
On the Prospects of Incorporating Large Language Models (LLMs) in Automated Planning and Scheduling (APS).
Proceedings of the Thirty-Fourth International Conference on Automated Planning and Scheduling, 2024

Expressive and Flexible Simulation of Information Spread Strategies in Social Networks Using Planning.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
On safe and usable chatbots for promoting voter participation.
AI Mag., September, 2023

On Solving the Rubik's Cube with Domain-Independent Planners Using Standard Representations.
CoRR, 2023

A Planning Ontology to Represent and Exploit Planning Knowledge for Performance Efficiency.
CoRR, 2023

Can LLMs be Good Financial Advisors?: An Initial Study in Personal Decision Making for Optimized Outcomes.
CoRR, 2023

Understanding the Capabilities of Large Language Models for Automated Planning.
CoRR, 2023

Building and Using a Planning Ontology from Past Data for Performance Efficiency.
Proceedings of the 1st International Planning and Ontology Workshop co-located with The 33rd International Conference on Automated Planning and Scheduling (ICAPS 2023), 2023

Plansformer Tool: Demonstrating Generation of Symbolic Plans Using Transformers.
Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

LLMs for Financial Advisement: A Fairness and Efficacy Study in Personal Decision Making.
Proceedings of the 4th ACM International Conference on AI in Finance, 2023

A Dataset and Baseline Approach for Identifying Usage States from Non-intrusive Power Sensing with MiDAS IoT-Based Sensors.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Plansformer: Generating Symbolic Plans using Transformers.
CoRR, 2022


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