Karthik Valmeekam

According to our database, Karthik Valmeekam authored at least 16 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Planning in Strawberry Fields: Evaluating and Improving the Planning and Scheduling Capabilities of LRM o1.

Karthik Valmeekam, Kaya Stechly, Atharva Gundawar, Subbarao Kambhampati

CoRR, 2024

LLMs Still Can't Plan; Can LRMs? A Preliminary Evaluation of OpenAI's o1 on PlanBench.

Karthik Valmeekam, Kaya Stechly, Subbarao Kambhampati

CoRR, 2024

Robust Planning with LLM-Modulo Framework: Case Study in Travel Planning.

Atharva Gundawar, Mudit Verma, Lin Guan, Karthik Valmeekam, Siddhant Bhambri, Subbarao Kambhampati

CoRR, 2024

Chain of Thoughtlessness: An Analysis of CoT in Planning.

Kaya Stechly, Karthik Valmeekam, Subbarao Kambhampati

CoRR, 2024

On the Self-Verification Limitations of Large Language Models on Reasoning and Planning Tasks.

Kaya Stechly, Karthik Valmeekam, Subbarao Kambhampati

CoRR, 2024

LLMs Can't Plan, But Can Help Planning in LLM-Modulo Frameworks.

Subbarao Kambhampati, Karthik Valmeekam, Lin Guan, Kaya Stechly, Mudit Verma, Siddhant Bhambri, Lucas Saldyt, Anil Murthy

CoRR, 2024

Position: LLMs Can't Plan, But Can Help Planning in LLM-Modulo Frameworks.

Subbarao Kambhampati, Karthik Valmeekam, Lin Guan, Mudit Verma, Kaya Stechly, Siddhant Bhambri, Lucas Saldyt, Anil Murthy

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

Can Large Language Models Really Improve by Self-critiquing Their Own Plans?

Karthik Valmeekam, Matthew Marquez, Subbarao Kambhampati

CoRR, 2023

On the Planning Abilities of Large Language Models (A Critical Investigation with a Proposed Benchmark).

Karthik Valmeekam, Sarath Sreedharan, Matthew Marquez, Alberto Olmo Hernandez, Subbarao Kambhampati

CoRR, 2023

On the Planning Abilities of Large Language Models - A Critical Investigation.

Karthik Valmeekam, Matthew Marquez, Sarath Sreedharan, Subbarao Kambhampati

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change.

Karthik Valmeekam, Matthew Marquez, Alberto Olmo Hernandez, Sarath Sreedharan, Subbarao Kambhampati

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning.

Lin Guan, Karthik Valmeekam, Sarath Sreedharan, Subbarao Kambhampati

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Relative Behavioral Attributes: Filling the Gap between Symbolic Goal Specification and Reward Learning from Human Preferences.

Lin Guan, Karthik Valmeekam, Subbarao Kambhampati

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Large Language Models Still Can't Plan (A Benchmark for LLMs on Planning and Reasoning about Change).

Karthik Valmeekam, Alberto Olmo Hernandez, Sarath Sreedharan, Subbarao Kambhampati

CoRR, 2022

RADAR-X: An Interactive Mixed Initiative Planning Interface Pairing Contrastive Explanations and Revised Plan Suggestions.

Karthik Valmeekam, Sarath Sreedharan, Sailik Sengupta, Subbarao Kambhampati

Proceedings of the Thirty-Second International Conference on Automated Planning and Scheduling, 2022

2021

RADAR-X: An Interactive Interface Pairing Contrastive Explanations with Revised Plan Suggestions.

Karthik Valmeekam, Sarath Sreedharan, Sailik Sengupta, Subbarao Kambhampati

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021