From the 1 of 7 linked papers with an AI index.
7 papers
SinAE: A Single-Architecture Flow-Matching Autoencoder for Cross-Domain Atomic Systems
Yuxuan Ren, Fan Yang, Jianhua Yao +1
SinAE is a unified Transformer-based autoencoder that uses flow-matching decoding to reconstruct and generate atomic structures across molecules, crystals, and proteins with near-l…
Graph Unitary Message Passing
Haiquan Qiu, Quanming Yao
Unitarity is a useful principle for stabilizing deep neural networks, but in graph neural networks (GNNs) instability is induced not only by learnable parameters but also by the gr…
Think Consistently, Reason Efficiently: Energy-Based Calibration for Implicit Chain-of-Thought
Zhikang Chen, Sen Cui, Deheng Ye +3
Large Language Models (LLMs) have demonstrated strong reasoning capabilities through \emph{Chain-of-Thought} (CoT) prompting, which enables step-by-step intermediate reasoning. How…
Learning to Learn with Contrastive Meta-Objective
Shiguang Wu, Yaqing Wang, Yatao Bian +1
Meta-learning enables learning systems to adapt quickly to new tasks, similar to humans. Different meta-learning approaches all work under/with the mini-batch episodic training fra…
3D-GSRD: 3D Molecular Graph Auto-Encoder with Selective Re-mask Decoding
Chang Wu, Zhiyuan Liu, Wen Shu +6
Masked graph modeling (MGM) is a promising approach for molecular representation learning (MRL).However, extending the success of re-mask decoding from 2D to 3D MGM is non-trivial,…
UniMoT: Unified Molecule-Text Language Model with Discrete Token Representation
Shuhan Guo, Yatao Bian, Ruibing Wang +3
The remarkable success of Large Language Models (LLMs) across diverse tasks has driven the research community to extend their capabilities to molecular applications. However, most…