<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Y. Li | 刘均 | 西安交通大学</title><link>https://liujun-xjtu.github.io/zh/authors/y.-li/</link><atom:link href="https://liujun-xjtu.github.io/zh/authors/y.-li/index.xml" rel="self" type="application/rss+xml"/><description>Y. Li</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>zh-Hans</language><lastBuildDate>Thu, 01 Jan 2026 00:00:00 +0000</lastBuildDate><item><title>Locomo-Plus: Beyond-Factual Cognitive Memory Evaluation Framework for LLM Agents</title><link>https://liujun-xjtu.github.io/zh/publication/locomo-plus-beyond-factual-cognitive-memory-evaluation-framework-for-llm-agents/</link><pubDate>Thu, 01 Jan 2026 00:00:00 +0000</pubDate><guid>https://liujun-xjtu.github.io/zh/publication/locomo-plus-beyond-factual-cognitive-memory-evaluation-framework-for-llm-agents/</guid><description/></item><item><title>MUR: Momentum Uncertainty guided Reasoning for Large Language Models</title><link>https://liujun-xjtu.github.io/zh/publication/mur-momentum-uncertainty-guided-reasoning-for-large-language-models/</link><pubDate>Thu, 01 Jan 2026 00:00:00 +0000</pubDate><guid>https://liujun-xjtu.github.io/zh/publication/mur-momentum-uncertainty-guided-reasoning-for-large-language-models/</guid><description/></item><item><title>SketchVL: Policy Optimization via Fine-Grained Credit Assignment for Chart Understanding and More</title><link>https://liujun-xjtu.github.io/zh/publication/sketchvl-policy-optimization-via-fine-grained-credit-assignment-for-chart-understanding-and-more/</link><pubDate>Thu, 01 Jan 2026 00:00:00 +0000</pubDate><guid>https://liujun-xjtu.github.io/zh/publication/sketchvl-policy-optimization-via-fine-grained-credit-assignment-for-chart-understanding-and-more/</guid><description/></item><item><title>ChartSketcher: Reasoning with Multimodal Feedback and Reflection for Chart Understanding</title><link>https://liujun-xjtu.github.io/zh/publication/chartsketcher-reasoning-with-multimodal-feedback-and-reflection-for-chart-understanding/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://liujun-xjtu.github.io/zh/publication/chartsketcher-reasoning-with-multimodal-feedback-and-reflection-for-chart-understanding/</guid><description/></item><item><title>SAGE: Scale-Aware Gradual Evolution for Continual Knowledge Graph Embedding</title><link>https://liujun-xjtu.github.io/zh/publication/sage-scale-aware-gradual-evolution-for-continual-knowledge-graph-embedding/</link><pubDate>Wed, 01 Jan 2025 00:00:00 +0000</pubDate><guid>https://liujun-xjtu.github.io/zh/publication/sage-scale-aware-gradual-evolution-for-continual-knowledge-graph-embedding/</guid><description/></item><item><title>FPrompt-PLM: Flexible-Prompt on Pretrained Language Model for Continual Few-Shot Relation Extraction</title><link>https://liujun-xjtu.github.io/zh/publication/fprompt-plm-flexible-prompt-on-pretrained-language-model-for-continual-few-shot-relation-extraction/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://liujun-xjtu.github.io/zh/publication/fprompt-plm-flexible-prompt-on-pretrained-language-model-for-continual-few-shot-relation-extraction/</guid><description/></item><item><title>Multi-View Cognition with Path Search for One-Shot Part Labeling</title><link>https://liujun-xjtu.github.io/zh/publication/multi-view-cognition-with-path-search-for-one-shot-part-labeling/</link><pubDate>Mon, 01 Jan 2024 00:00:00 +0000</pubDate><guid>https://liujun-xjtu.github.io/zh/publication/multi-view-cognition-with-path-search-for-one-shot-part-labeling/</guid><description/></item><item><title>Jointly Optimized Neural Coreference Resolution with Mutual Attention</title><link>https://liujun-xjtu.github.io/zh/publication/jointly-optimized-neural-coreference-resolution-with-mutual-attention/</link><pubDate>Tue, 01 Jan 2019 00:00:00 +0000</pubDate><guid>https://liujun-xjtu.github.io/zh/publication/jointly-optimized-neural-coreference-resolution-with-mutual-attention/</guid><description/></item></channel></rss>