<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>2026 Papers | Xingtong Yu</title><link>https://xingtongyu.netlify.app/2026-publication/</link><atom:link href="https://xingtongyu.netlify.app/2026-publication/index.xml" rel="self" type="application/rss+xml"/><description>2026 Papers</description><generator>Wowchemy (https://wowchemy.com)</generator><language>en-us</language><image><url>https://xingtongyu.netlify.app/media/icon_hu0b7a4cb9992c9ac0e91bd28ffd38dd00_9727_512x512_fill_lanczos_center_3.png</url><title>2026 Papers</title><link>https://xingtongyu.netlify.app/2026-publication/</link></image><item><title>ZeroGAR: Benchmarking the Adversarial Robustness of Zero-Shot Graph Models</title><link>https://xingtongyu.netlify.app/2026-publication/zerogar/</link><pubDate>Sun, 27 Sep 2026 00:00:00 +0000</pubDate><guid>https://xingtongyu.netlify.app/2026-publication/zerogar/</guid><description>&lt;!-- Bibliographic source checked 2026-10-19: https://arxiv.org/abs/2609.33314 --></description></item><item><title>From Parameters to Answers: How LLMs Retrieve and Use Their Internal Knowledge</title><link>https://xingtongyu.netlify.app/2026-publication/from-parameters-to-answers/</link><pubDate>Thu, 10 Sep 2026 00:00:00 +0000</pubDate><guid>https://xingtongyu.netlify.app/2026-publication/from-parameters-to-answers/</guid><description>&lt;!-- Bibliographic source checked 2026-10-19: https://arxiv.org/abs/2609.11859 --></description></item><item><title>TradingMoE: Routing the Right Experts in Evolving Markets</title><link>https://xingtongyu.netlify.app/2026-publication/tradingmoe/</link><pubDate>Wed, 12 Aug 2026 00:00:00 +0000</pubDate><guid>https://xingtongyu.netlify.app/2026-publication/tradingmoe/</guid><description>&lt;!-- Bibliographic source checked 2026-10-19: https://arxiv.org/abs/2608.11785 --></description></item><item><title>Dynamic Graph Prompting via Topology-Routed Mixed-Curvature Experts</title><link>https://xingtongyu.netlify.app/2026-publication/dynamic-graph-prompting-mixed-curvature/</link><pubDate>Thu, 06 Aug 2026 00:00:00 +0000</pubDate><guid>https://xingtongyu.netlify.app/2026-publication/dynamic-graph-prompting-mixed-curvature/</guid><description>&lt;!-- Bibliographic source checked 2026-10-19: https://arxiv.org/abs/2608.06031 --></description></item><item><title>HyperClaim: Fine-Grained Cross-Modal Hypergraph Reasoning for Video Misinformation Detection</title><link>https://xingtongyu.netlify.app/2026-publication/hyperclaim/</link><pubDate>Thu, 30 Jul 2026 00:00:00 +0000</pubDate><guid>https://xingtongyu.netlify.app/2026-publication/hyperclaim/</guid><description>&lt;!-- Bibliographic source checked 2026-10-19: https://arxiv.org/abs/2607.28375 --></description></item><item><title>Clustering as Reasoning: A k-Means Interpretation of Chain-of-Thought Graph Learning</title><link>https://xingtongyu.netlify.app/2026-publication/clustering-as-reasoning/</link><pubDate>Mon, 06 Jul 2026 00:00:00 +0000</pubDate><guid>https://xingtongyu.netlify.app/2026-publication/clustering-as-reasoning/</guid><description>&lt;!-- Bibliographic source checked 2026-10-19: https://proceedings.mlr.press/v306/xie26k.html --></description></item><item><title>StaR-KVQA: Structured Reasoning Traces for Implicit-Knowledge Visual Question Answering</title><link>https://xingtongyu.netlify.app/2026-publication/star-kvqa/</link><pubDate>Mon, 01 Jun 2026 00:00:00 +0000</pubDate><guid>https://xingtongyu.netlify.app/2026-publication/star-kvqa/</guid><description>&lt;!-- Bibliographic source checked 2026-10-19: https://openaccess.thecvf.com/content/CVPR2026/html/Wen_StaR-KVQA_Structured_Reasoning_Traces_for_Implicit-Knowledge_Visual_Question_Answering_CVPR_2026_paper.html --></description></item><item><title>PrimeKG-CL: A Continual Graph Learning Benchmark on Evolving Biomedical Knowledge Graphs</title><link>https://xingtongyu.netlify.app/2026-publication/primekg-cl/</link><pubDate>Mon, 11 May 2026 00:00:00 +0000</pubDate><guid>https://xingtongyu.netlify.app/2026-publication/primekg-cl/</guid><description>&lt;!-- Bibliographic source checked 2026-10-19: https://arxiv.org/abs/2605.10529 --></description></item><item><title>CoEvoT: Co-Evolving Chain-of-Thought Prompting for Graph-LLM Reasoning</title><link>https://xingtongyu.netlify.app/2026-publication/coevot/</link><pubDate>Fri, 08 May 2026 00:00:00 +0000</pubDate><guid>https://xingtongyu.netlify.app/2026-publication/coevot/</guid><description>&lt;!-- Bibliographic source checked 2026-10-19: https://arxiv.org/abs/2607.14114 --></description></item><item><title>GraphReAct: Reasoning and Acting for Multi-step Graph Inference</title><link>https://xingtongyu.netlify.app/2026-publication/graphreact/</link><pubDate>Fri, 08 May 2026 00:00:00 +0000</pubDate><guid>https://xingtongyu.netlify.app/2026-publication/graphreact/</guid><description>&lt;!-- Bibliographic source checked 2026-10-19: https://arxiv.org/abs/2605.07357 --></description></item><item><title>Learning Multi-Relational Graph Representations for DNA Methylation-Based Biological Age Estimation</title><link>https://xingtongyu.netlify.app/2026-publication/relage-gnn/</link><pubDate>Fri, 08 May 2026 00:00:00 +0000</pubDate><guid>https://xingtongyu.netlify.app/2026-publication/relage-gnn/</guid><description>&lt;!-- Bibliographic source checked 2026-10-19: https://arxiv.org/abs/2605.07175 --></description></item><item><title>UniDetect: LLM-Driven Universal Fraud Detection across Heterogeneous Blockchains</title><link>https://xingtongyu.netlify.app/2026-publication/unidetect/</link><pubDate>Tue, 14 Apr 2026 00:00:00 +0000</pubDate><guid>https://xingtongyu.netlify.app/2026-publication/unidetect/</guid><description>&lt;!-- Bibliographic source checked 2026-10-19: https://arxiv.org/abs/2604.12329 --></description></item><item><title>A2GBD: Attack-Agnostic Graph Backdoor Defense</title><link>https://xingtongyu.netlify.app/2026-publication/a2gbd/</link><pubDate>Mon, 13 Apr 2026 00:00:00 +0000</pubDate><guid>https://xingtongyu.netlify.app/2026-publication/a2gbd/</guid><description>&lt;!-- Bibliographic source checked 2026-10-19: https://ponderly.github.io/pub/A2GBD_WWW2026.pdf --></description></item><item><title>Evaluating Progress in Graph Foundation Models: A Comprehensive Benchmark and New Insights</title><link>https://xingtongyu.netlify.app/2026-publication/evaluating-progress-in-graph-foundation-models/</link><pubDate>Sat, 28 Feb 2026 00:00:00 +0000</pubDate><guid>https://xingtongyu.netlify.app/2026-publication/evaluating-progress-in-graph-foundation-models/</guid><description>&lt;!-- Bibliographic source checked 2026-10-19: https://arxiv.org/abs/2603.10033 --></description></item><item><title>UrbanGraphEmbeddings: Learning and Evaluating Spatially Grounded Multimodal Embeddings for Urban Science</title><link>https://xingtongyu.netlify.app/2026-publication/urbangraphembeddings/</link><pubDate>Mon, 09 Feb 2026 00:00:00 +0000</pubDate><guid>https://xingtongyu.netlify.app/2026-publication/urbangraphembeddings/</guid><description>&lt;!-- Bibliographic source checked 2026-10-19: https://xingtongyu.netlify.app/uploads/resume.pdf --></description></item></channel></rss>