6 papers
Multi-scale Graph Autoregressive Modeling: Molecular Property Prediction via Next Token Prediction
Zhuoyang Jiang, Yaosen Min, Peiran Jin +1
We present Connection-Aware Motif Sequencing (CamS), a graph-to-sequence representation that enables decoder-only Transformers to learn molecular graphs via standard next-token pre…
Panning for Gold: Expanding Domain-Specific Knowledge Graphs with General Knowledge
Runhao Zhao, Weixin Zeng, Wentao Zhang +4
Domain-specific knowledge graphs (DKGs) are critical yet often suffer from limited coverage compared to General Knowledge Graphs (GKGs). Existing tasks to enrich DKGs rely primaril…
Self-Guided Process Reward Optimization with Redefined Step-wise Advantage for Process Reinforcement Learning
Wu Fei, Shuxian Liang, Yibo Yang +5
Process Reinforcement Learning~(PRL) has demonstrated considerable potential in enhancing the reasoning capabilities of Large Language Models~(LLMs). However, introducing additiona…
Confidence interval estimation of mixed oil length with conditional diffusion model
Yanfeng Yang, Lihong Zhang, Ziqi Chen +2
Accurately estimating the mixed oil length plays a big role in the economic benefit for oil pipeline network. While various proposed methods have tried to predict the mixed oil len…
An AI-enabled Agent-Based Model and Its Application in Measles Outbreak Simulation for New Zealand
Sijin Zhang, Alvaro Orsi, Lei Chen
Agent Based Models (ABMs) have emerged as a powerful tool for investigating complex social interactions, particularly in the context of public health and infectious disease investi…
EntailE: Introducing Textual Entailment in Commonsense Knowledge Graph Completion
Ying Su, Tianqing Fang, Huiru Xiao +4
Commonsense knowledge graph completion is a new challenge for commonsense knowledge graph construction and application. In contrast to factual knowledge graphs such as Freebase and…