From 3d469d2de25600036dc2ef0855956b83433e439f Mon Sep 17 00:00:00 2001 From: Luo Siqiang Date: Tue, 30 Jun 2026 09:41:53 +0800 Subject: [PATCH 1/2] update paper description --- src/components/Publication/pub_data.json | 26 ++++++++++++------------ 1 file changed, 13 insertions(+), 13 deletions(-) diff --git a/src/components/Publication/pub_data.json b/src/components/Publication/pub_data.json index c5f8282..0e8acba 100644 --- a/src/components/Publication/pub_data.json +++ b/src/components/Publication/pub_data.json @@ -1940,7 +1940,7 @@ "year": 2025, "video": "", "href": "https://openreview.net/pdf?id=INg866tEaT", - "description": "", + "description": "For graph neural networks, simple edge pruning can be powerful.", "imgSrc": "", "keywords": [ "Graph Algorithms" @@ -1969,7 +1969,7 @@ "year": 2026, "video": "", "href": "https://arxiv.org/pdf/2406.09675", - "description": "", + "description": "Most Graph Neural Network models can be put in the form of Spectral GNNs. This study unifies many GNN models in the same framework and give a comprehensive comparison.", "imgSrc": "", "keywords": [ "Graph Algorithms" @@ -2055,7 +2055,7 @@ "year": 2026, "video": "", "href": "https://dl.acm.org/doi/pdf/10.1145/3770854.3780219", - "description": "", + "description": "Can graph models help with AI video analysis? Here is an answer.", "imgSrc": "", "keywords": [ "Graph Algorithms" @@ -2082,7 +2082,7 @@ "year": 2026, "video": "", "href": "https://www.vldb.org/pvldb/vol19/p958-liu.pdf", - "description": "", + "description": "Autonomous key-value store for fully dynamic online workload has been achieved!", "imgSrc": "", "keywords": [ "Data Systems" @@ -2109,7 +2109,7 @@ "year": 2026, "video": "", "href": "https://dl.acm.org/doi/pdf/10.1145/3786686", - "description": "", + "description": "A graph storage system designed for intensive graph updates.", "imgSrc": "", "keywords": [ "Data Systems" @@ -2139,7 +2139,7 @@ "year": 2026, "video": "", "href": "https://dl.acm.org/doi/epdf/10.1145/3795880", - "description": "", + "description": "This survey introduces most topics lying in the intersection between graphs and RAG.", "imgSrc": "", "keywords": [ "Graph Algorithms" @@ -2167,7 +2167,7 @@ "year": 2026, "video": "", "href": "https://arxiv.org/pdf/2507.14462", - "description": "", + "description": "PPR has been improving over 2 decades; for the first time, we largely close the gap between upper bound and lower bound.", "imgSrc": "", "keywords": [ "Graph Algorithms" @@ -2194,7 +2194,7 @@ "year": 2026, "video": "", "href": "https://dl.acm.org/doi/pdf/10.1145/3802014", - "description": "", + "description": "Learning for Database often assumes the testing workload has the same distribution with the training workload. Is the assumption reliable? This study answers the question.", "imgSrc": "", "keywords": [ "Data Systems" @@ -2223,7 +2223,7 @@ "year": 2026, "video": "", "href": "", - "description": "", + "description": "Diffusion model is not only effective in computer vision, it can do community search well.", "imgSrc": "", "keywords": [ "Graph Algorithms" @@ -2249,7 +2249,7 @@ "year": 2026, "video": "", "href": "https://arxiv.org/pdf/2603.13434", - "description": "", + "description": "When you even do not have text in your graph, can you still effectively do domain alignment for graph models? This paper provides an approach.", "imgSrc": "", "keywords": [ "Graph Algorithms" @@ -2275,7 +2275,7 @@ "year": 2026, "video": "", "href": "", - "description": "", + "description": "Learning over relation database often model the DB as a graph, based on DB schema. This is not correct.", "imgSrc": "", "keywords": [ "Graph Algorithms" @@ -2334,7 +2334,7 @@ "year": 2026, "video": "", "href": "https://www.openproceedings.org/2026/conf/edbt/paper-111.pdf", - "description": "", + "description": "Is learned index really effective in LSM-tree systems? This study answers this question.", "imgSrc": "", "keywords": [ "Data Systems" @@ -2361,7 +2361,7 @@ "year": 2026, "video": "", "href": "https://www.openproceedings.org/2026/conf/edbt/paper-89.pdf", - "description": "", + "description": "Cache management is a core issue in RocksDB; this paper provides a machine learning approach to address the issue.", "imgSrc": "", "keywords": [ "Data Systems" From 9a7899979d57ccb7fd60a4bc74b58536459e40fe Mon Sep 17 00:00:00 2001 From: Luo Siqiang Date: Tue, 30 Jun 2026 09:49:53 +0800 Subject: [PATCH 2/2] update paper --- src/components/Publication/pub_data.json | 14 +++++++------- 1 file changed, 7 insertions(+), 7 deletions(-) diff --git a/src/components/Publication/pub_data.json b/src/components/Publication/pub_data.json index 0e8acba..65b3e0d 100644 --- a/src/components/Publication/pub_data.json +++ b/src/components/Publication/pub_data.json @@ -1824,7 +1824,7 @@ "year": 2025, "video": "", "href": "https://dl.acm.org/doi/pdf/10.1145/3725310", - "description": "", + "description": "How to Grow an LSM-tree? A serious revisit of LSM-tree data ingestion to bridge the gap between theory and systems.", "imgSrc": "", "keywords": [ "Data Systems" @@ -1969,7 +1969,7 @@ "year": 2026, "video": "", "href": "https://arxiv.org/pdf/2406.09675", - "description": "Most Graph Neural Network models can be put in the form of Spectral GNNs. This study unifies many GNN models in the same framework and give a comprehensive comparison.", + "description": "Most Graph Neural Network models can be put in the form of Spectral GNNs. This study unifies many GNN models in the same framework and gives a comprehensive comparison.", "imgSrc": "", "keywords": [ "Graph Algorithms" @@ -2082,7 +2082,7 @@ "year": 2026, "video": "", "href": "https://www.vldb.org/pvldb/vol19/p958-liu.pdf", - "description": "Autonomous key-value store for fully dynamic online workload has been achieved!", + "description": "Autonomous key-value stores for fully dynamic online workloads have been achieved!", "imgSrc": "", "keywords": [ "Data Systems" @@ -2194,7 +2194,7 @@ "year": 2026, "video": "", "href": "https://dl.acm.org/doi/pdf/10.1145/3802014", - "description": "Learning for Database often assumes the testing workload has the same distribution with the training workload. Is the assumption reliable? This study answers the question.", + "description": "Learning for Database components often assumes the testing workload has the same distribution with the training workload. Is the assumption reliable? This study answers the question.", "imgSrc": "", "keywords": [ "Data Systems" @@ -2223,7 +2223,7 @@ "year": 2026, "video": "", "href": "", - "description": "Diffusion model is not only effective in computer vision, it can do community search well.", + "description": "", "imgSrc": "", "keywords": [ "Graph Algorithms" @@ -2249,7 +2249,7 @@ "year": 2026, "video": "", "href": "https://arxiv.org/pdf/2603.13434", - "description": "When you even do not have text in your graph, can you still effectively do domain alignment for graph models? This paper provides an approach.", + "description": "Without text in graphs, can you still effectively do domain alignment for graph models? This paper provides an approach.", "imgSrc": "", "keywords": [ "Graph Algorithms" @@ -2361,7 +2361,7 @@ "year": 2026, "video": "", "href": "https://www.openproceedings.org/2026/conf/edbt/paper-89.pdf", - "description": "Cache management is a core issue in RocksDB; this paper provides a machine learning approach to address the issue.", + "description": "Cache management is a core issue in LSM-tree systems; this paper provides an adaptive approach to address the issue.", "imgSrc": "", "keywords": [ "Data Systems"