1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.IR2026
TCA-SIR: Learning Target-Conditioned Abstractions for Scientific Inspiration Retrieval
Yuto Suzuki, Farnoush Banaei-Kashani
Scientific hypothesis generation for AI for Science typically involves Scientific Inspiration Retrieval (SIR) followed by hypothesis composition. Existing SIR methods rank papers b…
cs.AI2025★ 1 cited
FRAGMENTA: End-to-end Fragmentation-based Generative Model with Agentic Tuning for Drug Lead Optimization
Yuto Suzuki, Paul Awolade, Daniel V. LaBarbera +1
Molecule generation using generative AI is vital for drug discovery, yet class-specific datasets often contain fewer than 100 training examples. While fragment-based models handle…
cs.AI2025
Universe of Thoughts: Enabling Creative Reasoning with Large Language Models
Yuto Suzuki, Farnoush Banaei-Kashani
Reasoning based on Large Language Models (LLMs) has garnered increasing attention due to outstanding performance of these models in mathematical and complex logical tasks. Beginnin…