From 53f66cb95d6cef68bff149627739533ccd9c8fa4 Mon Sep 17 00:00:00 2001 From: prrao87 Date: Thu, 18 Dec 2025 23:07:27 -0500 Subject: [PATCH 1/2] Add research paper link to the landing page --- docs/overrides/home.html | 18 +++++++++++------- docs/src/assets/stylesheets/home.css | 17 ++++++++++++++++- 2 files changed, 27 insertions(+), 8 deletions(-) diff --git a/docs/overrides/home.html b/docs/overrides/home.html index 090a9db68f3..57109b50c4c 100644 --- a/docs/overrides/home.html +++ b/docs/overrides/home.html @@ -41,8 +41,8 @@ .lance-feature-section .md-button, .lance-intro-section .md-button:not(.md-button--primary) { background-color: transparent; - color: #625EFF; - text-decoration: underline; + color: inherit; + text-decoration: none; border: none; box-shadow: none; } @@ -50,8 +50,8 @@ .lance-feature-section .md-button:hover, .lance-intro-section .md-button:not(.md-button--primary):hover { background-color: transparent; - color: #757575; - text-decoration: underline; + color: #625EFF; + text-decoration: none; } @@ -146,16 +146,20 @@

The Open Lakehouse Format for Multimodal AI

-

What is Lance?

+

What is Lance?

- Lance contains a file format, table format, and catalog spec for multimodal AI, + Lance is a modern, columnar format for multimodal AI. It contains a file format, table format, and catalog spec, allowing you to build a complete open lakehouse on top of object storage to power your AI workflows. Lance brings high-performance vector search, full-text search, random access, and feature engineering capabilities to the lakehouse, while you can still get all the existing lakehouse benefits like SQL analytics, ACID transactions, time travel, and integrations with open engines (Apache Spark, Ray, PyTorch, Trino, DuckDB, etc.) and open catalogs (Apache Polaris, Unity Catalog, Apache Gravitino, Hive Metastore, etc.)

- Learn More +

+ Learn more about the technical details of Lance by reading the research paper: + "Lance: Efficient Random Access in Columnar Storage through Adaptive Structural Encodings" +

+ Read the Docs
diff --git a/docs/src/assets/stylesheets/home.css b/docs/src/assets/stylesheets/home.css index dcf90b5ccdf..086b6b43be6 100644 --- a/docs/src/assets/stylesheets/home.css +++ b/docs/src/assets/stylesheets/home.css @@ -149,7 +149,22 @@ line-height: 1.8; margin-bottom: 32px; opacity: 0.9; - text-align: center; + text-align: left; +} + +.lance-paper-link { + color: var(--md-primary-fg-color); + text-decoration: none; +} + +.lance-paper-link:hover { + color: var(--md-primary-fg-color); + text-decoration: none; +} + +.lance-intro-content a:hover { + color: #757575; + text-decoration: none; } .lance-intro-content .md-button { From cd8ea11d95b1d08b204fc832fe9ea7ebdee76100 Mon Sep 17 00:00:00 2001 From: prrao87 Date: Mon, 29 Dec 2025 12:39:10 -0500 Subject: [PATCH 2/2] Address feedback comments --- docs/overrides/home.html | 7 ++++--- 1 file changed, 4 insertions(+), 3 deletions(-) diff --git a/docs/overrides/home.html b/docs/overrides/home.html index 57109b50c4c..3322267f25e 100644 --- a/docs/overrides/home.html +++ b/docs/overrides/home.html @@ -148,7 +148,7 @@

The Open Lakehouse Format for Multimodal AI

What is Lance?

- Lance is a modern, columnar format for multimodal AI. It contains a file format, table format, and catalog spec, + Lance is a modern, open source lakehouse format for multimodal AI. It contains a file format, table format, and catalog spec, allowing you to build a complete open lakehouse on top of object storage to power your AI workflows. Lance brings high-performance vector search, full-text search, random access, and feature engineering capabilities to the lakehouse, while you can still get all the existing lakehouse benefits @@ -156,8 +156,9 @@

What is Lance?

and open catalogs (Apache Polaris, Unity Catalog, Apache Gravitino, Hive Metastore, etc.)

- Learn more about the technical details of Lance by reading the research paper: - "Lance: Efficient Random Access in Columnar Storage through Adaptive Structural Encodings" + Learn more about Lance's technical details by reading our + research paper + published at VLDB 2025.

Read the Docs