Discrete flow matching
Despite Flow Matching and diffusion models having emerged as powerful generative
paradigms for continuous variables such as images and videos, their application to high …
paradigms for continuous variables such as images and videos, their application to high …
[HTML][HTML] Quo Vadis ChatGPT? From Large Language Models to Large Knowledge Models
V Venkatasubramanian, A Chakraborty - Computers & Chemical …, 2025 - Elsevier
The startling success of ChatGPT and other large language models (LLMs) using
transformer-based generative neural network architecture in applications such as natural …
transformer-based generative neural network architecture in applications such as natural …
Benchmarking large language models for molecule prediction tasks
Large Language Models (LLMs) stand at the forefront of a number of Natural Language
Processing (NLP) tasks. Despite the widespread adoption of LLMs in NLP, much of their …
Processing (NLP) tasks. Despite the widespread adoption of LLMs in NLP, much of their …
Towards building specialized generalist ai with system 1 and system 2 fusion
In this perspective paper, we introduce the concept of Specialized Generalist Artificial
Intelligence (SGAI or simply SGI) as a crucial milestone toward Artificial General Intelligence …
Intelligence (SGAI or simply SGI) as a crucial milestone toward Artificial General Intelligence …
A Comprehensive Survey of Scientific Large Language Models and Their Applications in Scientific Discovery
In many scientific fields, large language models (LLMs) have revolutionized the way with
which text and other modalities of data (eg, molecules and proteins) are dealt, achieving …
which text and other modalities of data (eg, molecules and proteins) are dealt, achieving …
Geometry Informed Tokenization of Molecules for Language Model Generation
We consider molecule generation in 3D space using language models (LMs), which
requires discrete tokenization of 3D molecular geometries. Although tokenization of …
requires discrete tokenization of 3D molecular geometries. Although tokenization of …
Crystalline material discovery in the era of artificial intelligence
Crystalline materials, with their symmetrical and periodic structures, possess a diverse array
of properties and have been widely used in various fields, ranging from electronic devices to …
of properties and have been widely used in various fields, ranging from electronic devices to …
Empowering Cognitive Digital Twins with Generative Foundation Models: Developing a Low-Carbon Integrated Freight Transportation System
Effective monitoring of freight transportation is essential for advancing sustainable, low-
carbon economies. Traditional methods relying on single-modal data and discrete …
carbon economies. Traditional methods relying on single-modal data and discrete …
[HTML][HTML] Advancing Life Cycle Assessment of Sustainable Green Hydrogen Production Using Domain-Specific Fine-Tuning by Large Language Models Augmentation
Y Chen, U Liebau, SM Guruprasad… - Machine Learning and …, 2024 - mdpi.com
Assessing the sustainable development of green hydrogen and assessing its potential
environmental impacts using the Life Cycle Assessment is crucial. Challenges in LCA, like …
environmental impacts using the Life Cycle Assessment is crucial. Challenges in LCA, like …
Amyloid-β Deposition Prediction with Large Language Model Driven and Task Oriented Learning of Brain Functional Networks
Amyloid-β positron emission tomography can reflect the Amyloid-β protein deposition in the
brain and thus serves as one of the golden standards for Alzheimer's disease (AD) …
brain and thus serves as one of the golden standards for Alzheimer's disease (AD) …