arXiv AI

Bidirectional Semantic Complementary Tool Retrieval for Remote Sensing Agents

arXiv:2606. 07538v1 Announce Type: cross Abstract: Large language model (LLM)-based agents provide a novel paradigm for the automated processing of remote sensing(RS) data.

arXiv AI
Sep 1

SimCRAFT: Distilling Remote Sensing Agents via Synthetic Trajectories and Contextual Retrieval-Augmented Fine-Tuning

SimCRAFT is a model‑agnostic framework that distills remote sensing orchestration into a compact 7B‑scale model. It creates a large, constraint‑validated workflow planning corpus (SimRS‑14k) using a multi‑agent synthesis engine and a Mock Execution Engine, then fine‑tunes the model with Contextual Retrieval‑Augmented Fine‑Tuning (CRAFT) to reason analogically. Experiments show SimCRAFT‑7B outperforms open‑weight LLMs and rivals advanced closed‑source models, providing a lightweight, efficient baseline for autonomous remote sensing deployment.

By Haoran Wang, Jing Yao, Xu Yang, Zeqing Wang, Yang Zhang, Pedram Ghamisi, Zhengchao Chen
arXiv AI
Aug 13

VAKRA: Evaluating Multi-Hop Reasoning Across APIs and Retrieval Under Tool-Use Policies

arXiv:2608. 12282v1 Announce Type: new Abstract: Agents deployed in enterprise settings must reason across structured APIs and document collections, yet existing benchmarks evaluate these capabilities in isolation.

By Ankita Rajaram Naik, Anupama Murthi, Benjamin Elder, Siyu Huo, Raavi Gupta, Abhinav Jain, Praveen Venkateswaran, Abdulhamid Adebayo, Danish Contractor