3 citations · 6 across the 6 of their papers we have counts for
6 papers
Harnessing AtomisticSkills for Agentic Atomistic Research
Bowen Deng, Bohan Li, Matthew Cox +20
Computational materials science and chemistry span vast knowledge domains and fractured software ecosystems. Although large language models (LLMs) have demonstrated research capabi…
D-PACE: Dynamic Position-Aware Cross-Entropy for Parallel Speculative Drafting
Tianyu Wu, Yu Yao, Zhenting Qi +7
Speculative decoding accelerates LLM inference by having a small drafter propose tokens that a larger target model verifies in parallel. Recent diffusion-based parallel drafters su…
Multi-Persona Debate System for Automated Scientific Hypothesis Generation
Jaeha Oh, Byungchan Kim, Ju Li +2
Modern scientific discovery is bottlenecked not by data scarcity, but by the inability to synthesize fragmented knowledge into actionable hypotheses. This challenge is especially a…
Leveraging neural network interatomic potentials for a foundation model of chemistry
So Yeon Kim, Yang Jeong Park, Ju Li
Large-scale foundation models, including neural network interatomic potentials (NIPs) in computational materials science, have demonstrated significant potential. However, despite…
Frankenstein Optimizer: Harnessing the Potential by Revisiting Optimization Tricks
Chia-Wei Hsu, Nien-Ti Tsou, Yu-Cheng Chen +2
Gradient-based optimization drives the unprecedented performance of modern deep neural network models across diverse applications. Adaptive algorithms have accelerated neural netwo…
Contrastive Learning of English Language and Crystal Graphs for Multimodal Representation of Materials Knowledge
Yang Jeong Park, Mayank Kumaran, Chia-Wei Hsu +2
Artificial intelligence (AI) is increasingly used for the inverse design of materials, such as crystals and molecules. Existing AI research on molecules has integrated chemical str…