The rapid expansion of astronomical literature has created significant challenges for researchers aiming to increase the visibility and impact of their work. To address this challenge, we developed Stellar Forge, an AI-powered platform that optimizes the research publication workflow by integrating the NASA Astrophysics Data System (ADS) and the Unified Astronomy Thesaurus (UAT).

Stellar Forge provides several key services. First, it includes a concept tagger that uses a large language model with a retrieval pipeline built upon a novel hierarchical representation of UAT to automatically tag papers with relevant UAT concepts, improving discoverability across platforms and reducing human-induced errors. The tool also provides proper justifications, hierarchies, and concept positions within a branch, and it also suggests new concepts with branch positions if they emerge, ensuring that research remains accessible and up-to-date. The platform also includes a performance prediction tool that estimates the potential readership of papers within the ADS platform. This feature analyses abstract content and previous trends of similar publications to probabilistically forecast readership for the upcoming months, helping researchers anticipate the impact of their work. In addition, Stellar Forge supports content creation with title and abstract optimization tools that improve the visibility of research, allowing researchers to cater their writing for specific audiences and purposes with precise controls. These tools use task-specific fine-tuned large language models and dynamic one-shot prompting to craft clear, effective titles and abstracts.

Built on a modular architecture, Stellar Forge integrates with existing research systems to provide continuous support and improvements to researchers, from content creation to maximizing research visibility. By bridging AI with astronomical resources and researcher needs, Stellar Forge opens the door to more efficient and impactful advancements in astronomical research.