arXiv AI
Can Generative AI Automate Data Extraction for Meta-Analysis? A Case Study on Intercropping Research
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arXiv AI
Jun 30
meta-pipe: An LLM-agent pipeline for end-to-end automated systematic review and meta-analysis
arXiv:2606. 28363v1 Announce Type: cross Abstract: Objective: To describe the architecture and design rationale of meta-pipe, an open-source large language model (LLM)-agent pipeline that integrates the complete systematic review and meta-analysis (SR/MA) workflow -- from literature search through statistical analysis, manuscript generation, and quality assurance -- with mandatory human oversight at critical decision points.
arXiv AI
Jul 2
Autonomous Scientific Discovery via Iterative Meta-Reflection
arXiv:2607. 01131v1 Announce Type: cross Abstract: Autonomous scientific discovery systems offer the potential to accelerate research by automating the process of hypothesis generation and validation.
arXiv AI
Jul 2
Agri-SAGE: Simulation-Grounded Multi-Agent LLM for Context-Aware Agricultural Advisory Generation
arXiv:2607. 00454v1 Announce Type: new Abstract: Agricultural advisory systems face a fundamental tension: static agronomic guidelines offer consistent, evidence-based recommendations, yet remain blind to in-season variability and dynamic uncertainties.
arXiv Computation and Language
Oct 22
Computer Vision and Knowledge-Grounded Language Models for Intelligent Beekeeper Assistance
The paper introduces an edge‑deployable system that transforms photographs of bee hive frames into actionable inspection reports. It uses an object detector to identify comb‑cell classes, converts detections into a structured fact schema, and then generates constrained factual text that triggers a knowledge‑base for interpretation and recommendations. The authors also release the FAIRHiveText‑1K dataset, pairing images with facts and text, to support future LLM research in this domain.
arXiv Machine Learning
Jun 30
KrishokChat: A Citation-Grounded Dataset and Benchmark for Bengali Agricultural Advisory
arXiv:2606. 29243v1 Announce Type: new Abstract: We present KrishokChat, the first citation-grounded Bengali agricultural instruction-tuning dataset for crop advisory in low-resource settings.
arXiv AI
Sep 23
Agentic Explainable Artificial Intelligence (Agentic XAI) Approach To Explore Better Explanation: A Case Study in Decision Support for Rice Cultivation in Japan
arXiv:2512. 21066v4 Announce Type: replace Abstract: Explainable artificial intelligence (XAI) reveals how explanatory variables relate to a response variable, yet communicating XAI outputs to laypersons remains difficult, limiting trust in AI-based predictions.