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Karthik Valmeekam
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Large Language Models Still Can't Plan (A Benchmark for LLMs on Planning and Reasoning about Change)
K Valmeekam, A Olmo, S Sreedharan, S Kambhampati
arXiv preprint arXiv:2206.10498, 2022
2132022
On the Planning Abilities of Large Language Models--A Critical Investigation
K Valmeekam, M Marquez, S Sreedharan, S Kambhampati
Thirty-seventh Conference on Neural Information Processing Systems, 2023
1052023
Leveraging Pre-trained Large Language Models to Construct and Utilize World Models for Model-based Task Planning
L Guan, K Valmeekam, S Sreedharan, S Kambhampati
Thirty-seventh Conference on Neural Information Processing Systems, 2023
462023
PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change
K Valmeekam, M Marquez, A Olmo, S Sreedharan, S Kambhampati
Thirty-seventh Conference on Neural Information Processing Systems Datasets …, 2023
442023
Can Large Language Models Really Improve by Self-critiquing Their Own Plans?
K Valmeekam, M Marquez, S Kambhampati
arXiv preprint arXiv:2310.08118, 2023
352023
Opinion Mining on Emojis using Deep Learning Techniques
V Karthik, D Nair, J Anuradha
Procedia Computer Science 132, 167-173, 2018
192018
RADAR-X: An Interactive Mixed Initiative Planning Interface Pairing Contrastive Explanations and Revised Plan Suggestions
K Valmeekam, S Sreedharan, S Sengupta, S Kambhampati
Proceedings of the International Conference on Automated Planning and …, 2022
142022
LLMs Can't Plan, But Can Help Planning in LLM-Modulo Frameworks
S Kambhampati, K Valmeekam, L Guan, K Stechly, M Verma, S Bhambri, ...
arXiv preprint arXiv:2402.01817, 2024
132024
On the Self-Verification Limitations of Large Language Models on Reasoning and Planning Tasks
K Stechly, K Valmeekam, S Kambhampati
arXiv preprint arXiv:2402.08115, 2024
92024
Relative Behavioral Attributes: Filling the Gap between Symbolic Goal Specification and Reward Learning from Human Preferences
L Guan, K Valmeekam, S Kambhampati
The Eleventh International Conference on Learning Representations, 2022
62022
RADAR-X: An interactive interface pairing contrastive explanations with revised plan suggestions
V Karthik, S Sreedharan, S Sengupta, S Kambhampati
Proceedings of the AAAI Conference on Artificial Intelligence 35 (18), 16051 …, 2021
62021
On the role of large language models in planning, July 2023. Tutorial presented at the International Conference on Automated Planning and Scheduling (ICAPS), Prague
S Kambhampati, K Valmeekam, M Marquez, L Guan
32023
Chain of Thoughtlessness: An Analysis of CoT in Planning
K Stechly, K Valmeekam, S Kambhampati
arXiv preprint arXiv:2405.04776, 2024
22024
Robust Planning with LLM-Modulo Framework: Case Study in Travel Planning
A Gundawar, M Verma, L Guan, K Valmeekam, S Bhambri, ...
arXiv preprint arXiv:2405.20625, 2024
12024
A Study of Explainable Decision Support for Longitudinal Sequential Decision Making
K Valmeekam
Arizona State University, 2021
2021
Position: LLMs Can’t Plan, But Can Help Planning in LLM-Modulo Frameworks
S Kambhampati, K Valmeekam, L Guan, M Verma, K Stechly, S Bhambri, ...
Forty-first International Conference on Machine Learning, 0
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