Papers by Nagarajan Natarajan
Task Facet Learning: A Structured Approach To Prompt Optimization (2025.findings-acl)
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| Challenge: | Existing approaches to prompt optimization are limited to learning multiple facets of a task from training examples. |
| Approach: | They propose to optimize a text prompt by considering different facets of a task and including them in the prompt. |
| Outcome: | The proposed algorithm can generate long, complex prompts that existing methods are unable to generate. |
Learning Optimal Message Representations for Agentic Communication (2026.findings-acl)
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Shashwat Gupta, Anson Bastos, Mayukh Das, Supriyo Ghosh, Nagarajan Natarajan, Chetan Bansal, Saravan Rajmohan
| Challenge: | Existing approaches lack the intelligence necessary to understand, learn or apply optimal communication representations adaptively. |
| Approach: | They propose to dynamically learn the optimal message representations to enhance agentic performance by using an Expanding Markov Decision Process. |
| Outcome: | The proposed framework improves agentic performance while maintaining efficiency. |