Why SymTax is Not Just Another AI, But a New Partner for Researchers
27 Aug 2025
This work presents SymTax, a novel citation recommendation AI. It models human behavior via "symbiosis" and sets a new state-of-the-art.
A Quantitative and Qualitative Analysis of the SymTax Citation Recommendation Model
26 Aug 2025
This deep-dive analysis proves why SymTax works, showing its 'symbiotic' enricher and taxonomy fusion are essential for its state-of-the-art performance.
A Comparative Performance Analysis of SymTax on Five Citation Recommendation Datasets
26 Aug 2025
This paper presents empirical proof that the SymTax model significantly outperforms state-of-the-art AI on all major citation recommendation benchmarks.
A Three-Stage Architecture for Precision Citation Recommendation
26 Aug 2025
SymTax, a new AI for citation recommendation, uses a "symbiotic" model and taxonomy fusion to more accurately predict relevant scientific papers.
The Creation of ArSyTa, a Novel 8.27-Million-Context Dataset for Local Citation Recommendation
26 Aug 2025
This paper details ArSyTa, a new, massive dataset for citation AI. It has 8.27M rich contexts from arXiv papers to improve recommendation models.
How Symbiotic AI Can Find Your Paper's Next Great Citation
26 Aug 2025
SymTax is a novel AI for citation recommendation. It mimics human behavior by using a "symbiotic" model and hyperbolic geometry to improve accuracy.
What is the Best Way to Train AI Models?
1 Mar 2025
Fine-tuning outperforms full-training in Hi-Mapper’s visual hierarchy learning, optimizing feature representation in CNNs and transformer models.
Supplementary Materials for Study on Hyperbolic Visual Hierarchy Mapping
1 Mar 2025
Supplementary details on Hyperbolic Visual Hierarchy Mapping, including network architecture, theoretical baseline, and additional experimental results.
What If AI Understood Images Like We Do? This Model Might
1 Mar 2025
Hi-Mapper enhances AI’s ability to understand visual hierarchies using hyperbolic space learning, improving scene comprehension and deep learning models.