Tootfinder

CaliciBoost: Performance-Driven Evaluation of Molecular Representations for Caco-2 Permeability Prediction
Huong Van Le, Weibin Ren, Junhong Kim, Yukyung Yun, Young Bin Park, Young Jun Kim, Bok Kyung Han, Inho Choi, Jong IL Park, Hwi-Yeol Yun, Jae-Mun Choi
https://arxiv.org/abs/2506.08059

CaliciBoost: Performance-Driven Evaluation of Molecular Representations for Caco-2 Permeability Prediction
Caco-2 permeability serves as a critical in vitro indicator for predicting the oral absorption of drug candidates during early-stage drug discovery. To enhance the accuracy and efficiency of computational predictions, we systematically investigated the impact of eight molecular feature representation types including 2D/3D descriptors, structural fingerprints, and deep learning-based embeddings combined with automated machine learning techniques to predict Caco-2 permeability. Using two datasets…

Towards Efficient Speech-Text Jointly Decoding within One Speech Language Model
Haibin Wu, Yuxuan Hu, Ruchao Fan, Xiaofei Wang, Kenichi Kumatani, Bo Ren, Jianwei Yu, Heng Lu, Lijuan Wang, Yao Qian, Jinyu Li
https://arxiv.org/abs/2506.04518

Towards Efficient Speech-Text Jointly Decoding within One Speech Language Model
Speech language models (Speech LMs) enable end-to-end speech-text modelling within a single model, offering a promising direction for spoken dialogue systems. The choice of speech-text jointly decoding paradigm plays a critical role in performance, efficiency, and alignment quality. In this work, we systematically compare representative joint speech-text decoding strategies-including the interleaved, and parallel generation paradigms-under a controlled experimental setup using the same base lan…

Accurate Chemistry Collection: Coupled cluster atomization energies for broad chemical space
Sebastian Ehlert, Jan Hermann, Thijs Vogels, Victor Garcia Satorras, Stephanie Lanius, Marwin Segler, Derk P. Kooi, Kenji Takeda, Chin-Wei Huang, Giulia Luise, Rianne van den Berg, Paola Gori-Giorgi, Amir Karton
https://arxiv.org/abs/250…

Accurate Chemistry Collection: Coupled cluster atomization energies for broad chemical space
Accurate thermochemical data with sub-chemical accuracy (i.e., within $\pm$1 kcal mol$^{-1}$ from sufficiently accurate experimental or theoretical reference data) is essential for the development and improvement of computational chemistry methods. Challenging thermochemical properties such as heats of formation and total atomization energies (TAEs) are of particular interest because they rigorously test the ability of computational chemistry methods to accurately describe complex chemical tran…