diff --git a/_bibliography/papers.bib b/_bibliography/papers.bib
index 021530acda04..78d2b462f08c 100644
--- a/_bibliography/papers.bib
+++ b/_bibliography/papers.bib
@@ -3,6 +3,23 @@
 
 @string{aps = {American Physical Society,}}
 
+@techreport{liu_cone_2023,
+	type = {preprint},
+	title = {{CONE}: {COntext}-specific {Network} {Embedding} via {Contextualized} {Graph} {Attention}},
+	shorttitle = {{CONE}},
+	url = {http://biorxiv.org/lookup/doi/10.1101/2023.10.21.563390},
+	abstract = {Human gene interaction networks, commonly known as interactomes, encode genes’ functional relationships, which are invaluable knowledge for translational medical research and the mechanistic understanding of complex human diseases. Meanwhile, the advancement of network embedding techniques has inspired recent efforts to identify novel human disease-associated genes using canonical interactome embeddings. However, one pivotal challenge that persists stems from the fact that many complex diseases manifest in specific biological contexts, such as tissues or cell types, and many existing interactomes do not encapsulate such information. Here, we propose CONE3, a versatile approach to generate contextspecific embeddings from a context-free interactome. The core component of CONE consists of a graph attention network with contextual conditioning, and it is trained in a noise contrastive fashion using contextualized interactome random walks localized around contextual genes. We demonstrate the strong performance of CONE embeddings in identifying disease-associated genes when using known associated biological contexts to the diseases. Furthermore, our approach offers insights into understanding the biological contexts associated with human diseases.},
+	language = {en},
+	urldate = {2023-12-13},
+	institution = {Bioinformatics},
+	author = {Liu, Renming and Yuan, Hao and Johnson, Kayla A and Krishnan, Arjun},
+	month = oct,
+	year = {2023},
+	doi = {10.1101/2023.10.21.563390},
+	file = {Liu et al. - 2023 - CONE COntext-specific Network Embedding via Conte.pdf:/Users/haoyuan/Zotero/storage/LJGCKE76/Liu et al. - 2023 - CONE COntext-specific Network Embedding via Conte.pdf:application/pdf},
+}
+
+
 @article{atta_exon-capture_2022,
   abbr = {MPE},
 	title = {Exon-capture data and locus screening provide new insights into the phylogeny of flatfishes ({Pleuronectoidei})},