activity
20222026
most citedAugmenting Scientific Creativity with Retrieval across Knowledge Domains

7 citations · 12 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CV2026

HASSL: Hierarchy-Aware Self-Supervised Learning Framework for Single Cell Microscopy

Julius Riel, Vishwa Mohan Singh, Sai Anirudh Aryasomayajula +10

Hierarchical structure is common in image data, where fine-grained clusters often merge into larger, coarser semantic groups. In biological cell images, current self-supervised lea…

cs.CE2025

A Synthesizability-Guided Pipeline for Materials Discovery

Thorben Prein, Willis O'Leary, Aikaterini Flessa Savvidou +2

Computational materials discovery relies on the generation of plausible crystal structures. The plausibility is typically judged through density functional theory methods which, wh…

cond-mat.mtrl-sci2025★ 2 cited

DiffSyn: A Generative Diffusion Approach to Materials Synthesis Planning

Elton Pan, Soonhyoung Kwon, Sulin Liu +9

The synthesis of crystalline materials, such as zeolites, remains a significant challenge due to a high-dimensional synthesis space, intricate structure-synthesis relationships and…

cond-mat.mtrl-sci2025

Language Models Enable Data-Augmented Synthesis Planning for Inorganic Materials

Thorben Prein, Elton Pan, Janik Jehkul +3

Inorganic synthesis planning currently relies primarily on heuristic approaches or machine-learning models trained on limited datasets, which constrains its generality. We demonstr…

physics.chem-ph2025★ 2 cited

Retro-Rank-In: A Ranking-Based Approach for Inorganic Materials Synthesis Planning

Thorben Prein, Elton Pan, Sami Haddouti +8

Retrosynthesis strategically plans the synthesis of a chemical target compound from simpler, readily available precursor compounds. This process is critical for synthesizing novel…

cs.CL2024★ 1 cited

Regress, Don't Guess -- A Regression-like Loss on Number Tokens for Language Models

Jonas Zausinger, Lars Pennig, Anamarija Kozina +13

While language models have exceptional capabilities at text generation, they lack a natural inductive bias for emitting numbers and thus struggle in tasks involving quantitative re…

cs.IR2022★ 7 cited

Augmenting Scientific Creativity with Retrieval across Knowledge Domains

Hyeonsu B. Kang, Sheshera Mysore, Kevin Huang +5

Exposure to ideas in domains outside a scientist's own may benefit her in reformulating existing research problems in novel ways and discovering new application domains for existin…