<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Publications | Lifan Zhao</title><link>https://lifan-zhao.github.io/publication/</link><atom:link href="https://lifan-zhao.github.io/publication/index.xml" rel="self" type="application/rss+xml"/><description>Publications</description><generator>Hugo Blox Builder (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Fri, 19 Sep 2025 00:00:00 +0000</lastBuildDate><image><url>https://lifan-zhao.github.io/media/icon_hu4220705106653493934.png</url><title>Publications</title><link>https://lifan-zhao.github.io/publication/</link></image><item><title>Less is More: Unlocking Specialization of Time Series Foundation Models via Structured Pruning</title><link>https://lifan-zhao.github.io/publication/prune-then-finetune/</link><pubDate>Fri, 19 Sep 2025 00:00:00 +0000</pubDate><guid>https://lifan-zhao.github.io/publication/prune-then-finetune/</guid><description/></item><item><title>Proactive Model Adaptation Against Concept Drift for Online Time Series Forecasting</title><link>https://lifan-zhao.github.io/publication/proceed/</link><pubDate>Sat, 01 Feb 2025 00:00:00 +0000</pubDate><guid>https://lifan-zhao.github.io/publication/proceed/</guid><description/></item><item><title>Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators</title><link>https://lifan-zhao.github.io/publication/lift/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://lifan-zhao.github.io/publication/lift/</guid><description/></item><item><title>StockCL: Selective Contrastive Learning for Stock Trend Forecasting via Learnable Concepts</title><link>https://lifan-zhao.github.io/publication/10-1007-978-981-97-5575-2-20/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://lifan-zhao.github.io/publication/10-1007-978-981-97-5575-2-20/</guid><description/></item><item><title>DoubleAdapt: A Meta-learning Approach to Incremental Learning for Stock Trend Forecasting</title><link>https://lifan-zhao.github.io/publication/double-adapt/</link><pubDate>Tue, 01 Aug 2023 00:00:00 +0000</pubDate><guid>https://lifan-zhao.github.io/publication/double-adapt/</guid><description/></item><item><title>RESUS: Warm-up Cold Users via Meta-learning Residual User Preferences in CTR Prediction</title><link>https://lifan-zhao.github.io/publication/10-1145-3564283/</link><pubDate>Wed, 01 Feb 2023 00:00:00 +0000</pubDate><guid>https://lifan-zhao.github.io/publication/10-1145-3564283/</guid><description/></item><item><title>Methods for Acquiring and Incorporating Knowledge into Stock Price Prediction: A Survey</title><link>https://lifan-zhao.github.io/publication/wang-2023-methodsacquiringincorporatingknowledge/</link><pubDate>Sun, 01 Jan 2023 00:00:00 +0000</pubDate><guid>https://lifan-zhao.github.io/publication/wang-2023-methodsacquiringincorporatingknowledge/</guid><description/></item><item><title>Mixed Information Flow for Cross-Domain Sequential Recommendations</title><link>https://lifan-zhao.github.io/publication/10-1145-3487331/</link><pubDate>Sat, 01 Jan 2022 00:00:00 +0000</pubDate><guid>https://lifan-zhao.github.io/publication/10-1145-3487331/</guid><description/></item></channel></rss>