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: Efficient End-to-end Fragmentation-based Generative Model with Agentic Tuning for Drug Lead Optimization in Small Data Regime
Yuto Suzuki, Paul Awolade, Daniel V. LaBarbera +1
Molecule generation from extremely limited training data is a key challenge in drug discovery. Existing fragment-based methods are more suitable than atom-based approaches in this…
cs.AI2025
Universe of Thoughts: A Computational Framework for Creative Reasoning in Large Language Models
Yuto Suzuki, Farnoush Banaei-Kashani
Recent advances in Large Language Model (LLM) reasoning have improved conventional problem solving, but creative reasoning remains comparatively underexplored. Inspired by cognitiv…