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Srimat T. Chakradhar

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#artificial intelligence Preprint Sep 2026

GRASP: Generating, Revising, and Assessing for Strategic Planning with Agentic AI

Empirical evaluations show that GRASP consistently establishes a new state-of-the-art frontier across diverse datasets, yielding substantial accuracy gains over direct LLM planners on Natural Plan Calendar Scheduling, ZebraLogic, and SciBench Math.

Arunabh Srivastava, M. Khojastepour, Srimat T. Chakradhar et al. · 0 citations
Preprint Aug 2026

DamageScope: Vision-Language Retrieval at Scale for Disaster Damage Assessment from Satellite Imagery

DamageScope is a retrieval-augmented framework that combines satellite imagery with Vision-Language Models (VLMs) and Large Language Models (LLMs) to automate property damage analysis and introduces a novel multi-vector embedding-based clustering algorithm that outperforms traditional single-vector embedding approaches...

Ravi K. Rajendran, Biplob Debnath, Murugan Sankaradas et al. · 0 citations

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