96 citations · 229 across the 49 of their papers we have counts for
15 papers · 1 filter
Domain Invariant Learning for Gaussian Processes and Bayesian Exploration
Xilong Zhao, Siyuan Bian, Yaoyun Zhang +5
Out-of-distribution (OOD) generalization has long been a challenging problem that remains largely unsolved. Gaussian processes (GP), as popular probabilistic model classes, especia…
Towards Controlled Table-to-Text Generation with Scientific Reasoning
Zhixin Guo, Jianping Zhou, Jiexing Qi +6
The sheer volume of scientific experimental results and complex technical statements, often presented in tabular formats, presents a formidable barrier to individuals acquiring pre…
HuRef: HUman-REadable Fingerprint for Large Language Models
Boyi Zeng, Lizheng Wang, Yuncong Hu +5
Protecting the copyright of large language models (LLMs) has become crucial due to their resource-intensive training and accompanying carefully designed licenses. However, identify…
Enhancing Uncertainty-Based Hallucination Detection with Stronger Focus
Tianhang Zhang, Lin Qiu, Qipeng Guo +6
Large Language Models (LLMs) have gained significant popularity for their impressive performance across diverse fields. However, LLMs are prone to hallucinate untruthful or nonsens…
Exploring the Limits of Historical Information for Temporal Knowledge Graph Extrapolation
Yi Xu, Junjie Ou, Hui Xu +4
Temporal knowledge graphs, representing the dynamic relationships and interactions between entities over time, have been identified as a promising approach for event forecasting. H…
Graph Out-of-Distribution Generalization with Controllable Data Augmentation
Bin Lu, Xiaoying Gan, Ze Zhao +4
Graph Neural Network (GNN) has demonstrated extraordinary performance in classifying graph properties. However, due to the selection bias of training and testing data (e.g., traini…
Exploring and Verbalizing Academic Ideas by Concept Co-occurrence
Yi Xu, Shuqian Sheng, Bo Xue +3
Researchers usually come up with new ideas only after thoroughly comprehending vast quantities of literature. The difficulty of this procedure is exacerbated by the fact that the n…
K2: A Foundation Language Model for Geoscience Knowledge Understanding and Utilization
Cheng Deng, Tianhang Zhang, Zhongmou He +9
Large language models (LLMs) have achieved great success in general domains of natural language processing. In this paper, we bring LLMs to the realm of geoscience with the objecti…
Towards Tracing Code Provenance with Code Watermarking
Wei Li, Borui Yang, Yujie Sun +5
Recent advances in large language models have raised wide concern in generating abundant plausible source code without scrutiny, and thus tracing the provenance of code emerges as…
Prediction with Incomplete Data under Agnostic Mask Distribution Shift
Yichen Zhu, Jian Yuan, Bo Jiang +4
Data with missing values is ubiquitous in many applications. Recent years have witnessed increasing attention on prediction with only incomplete data consisting of observed feature…
ONCache: A Cache-Based Low-Overhead Container Overlay Network
Shengkai Lin, Shizhen Zhao, Peirui Cao +6
Recent years have witnessed a widespread adoption of containers. While containers simplify and accelerate application development, existing container network technologies either in…
Revisiting Network Value: Sublinear Knowledge Law
Xinbing Wang, Luoyi Fu, Huquan Kang +3
Three influential laws, namely Sarnoff's Law, Metcalfe's Law, and Reed's Law, have been established to describe network value in terms of the number of neighbors, edges, and subgra…
Covidia: COVID-19 Interdisciplinary Academic Knowledge Graph
Cheng Deng, Jiaxin Ding, Luoyi Fu +3
The pandemic of COVID-19 has inspired extensive works across different research fields. Existing literature and knowledge platforms on COVID-19 only focus on collecting papers on b…
Text Classification in the Wild: a Large-scale Long-tailed Name Normalization Dataset
Jiexing Qi, Shuhao Li, Zhixin Guo +5
Real-world data usually exhibits a long-tailed distribution,with a few frequent labels and a lot of few-shot labels. The study of institution name normalization is a perfect applic…
Ordered GNN: Ordering Message Passing to Deal with Heterophily and Over-smoothing
Yunchong Song, Chenghu Zhou, Xinbing Wang +1
Most graph neural networks follow the message passing mechanism. However, it faces the over-smoothing problem when multiple times of message passing is applied to a graph, causing…