<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Research on PKU ZhiClass</title><link>https://zhi-class.ai/en/research/</link><description>Recent content in Research on PKU ZhiClass</description><generator>Hugo -- gohugo.io</generator><language>en</language><copyright>Copyright © Zhi Class 2022-2026</copyright><lastBuildDate>Thu, 12 Feb 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://zhi-class.ai/en/research/index.xml" rel="self" type="application/rss+xml"/><item><title>LDA-1B: Scaling Latent Dynamics Action Model via Universal Embodied Data Ingestion</title><link>https://zhi-class.ai/en/research/2602.lda-1b/</link><pubDate>Thu, 12 Feb 2026 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/2602.lda-1b/</guid><description>Recent robot foundation models largely rely on large-scale behavior cloning, which imitates expert actions but discards transferable dynamics knowledge embedded in heterogeneous embodied data.</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/2602.lda-1b/featured.zh-cn.jpg"/></item><item><title>NavSpace: How Navigation Agents Follow Spatial Intelligence Instructions</title><link>https://zhi-class.ai/en/research/2601.navspace/</link><pubDate>Sat, 31 Jan 2026 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/2601.navspace/</guid><description>Instruction-following navigation is a key step toward embodied intelligence.</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/2601.navspace/featured.zh-cn.jpg"/></item><item><title>Learning Physics-Grounded 4D Dynamics with Neural Gaussian Force Fields</title><link>https://zhi-class.ai/en/research/2601.learning-physics-grounded-4d-dynamics-with-neura/</link><pubDate>Mon, 26 Jan 2026 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/2601.learning-physics-grounded-4d-dynamics-with-neura/</guid><description>Predicting physical dynamics from visual data remains a fundamental challenge in AI, as it requires both accurate scene understanding and robust physics reasoning.</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/2601.learning-physics-grounded-4d-dynamics-with-neura/featured.zh-cn.jpg"/></item><item><title>MCPMark: A Benchmark for Stress-Testing Realistic and Comprehensive MCP Use</title><link>https://zhi-class.ai/en/research/2601.mcpmark/</link><pubDate>Mon, 26 Jan 2026 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/2601.mcpmark/</guid><description>The MCP standardizes how LLMs interact with external systems, forming the foundation for general agents.</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/2601.mcpmark/featured.zh-cn.jpg"/></item><item><title>Neural Force Field: Few shot learning of generalized physical reasoning</title><link>https://zhi-class.ai/en/research/2601.neural-force-field/</link><pubDate>Mon, 26 Jan 2026 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/2601.neural-force-field/</guid><description>We present NFF, a modeling framework built on NODE that learns interpretable force field representations which can be efficiently integrated through an ODE solver to predict object trajectories.</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/2601.neural-force-field/featured.zh-cn.jpg"/></item><item><title>Generalized Threshold Optimization with Harmony Multi-Threshold Neurons for Accurate ANN-to-SNN Conversion</title><link>https://zhi-class.ai/en/research/2601.generalized-threshold-optimization-with-harmony/</link><pubDate>Tue, 20 Jan 2026 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/2601.generalized-threshold-optimization-with-harmony/</guid><description>Spiking Neural Networks (SNNs) are a promising paradigm designed to emulate the brain’s energy efficient by incorporating the timing of spikes.</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/2601.generalized-threshold-optimization-with-harmony/featured.zh-cn.png"/></item><item><title>Luminark: Training-free, Probabilistically-Certified Watermarking for General Vision Generative Models</title><link>https://zhi-class.ai/en/research/2601.luminark/</link><pubDate>Sat, 03 Jan 2026 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/2601.luminark/</guid><description>In this paper, we introduce \emph{Luminark｝, a training-free and probabilistically-certified watermarking method for general vision generative models.</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/2601.luminark/featured.zh-cn.jpg"/></item><item><title>CorrectNav: Self-Correction Flywheel Empowers Vision-Language-Action Navigation Model</title><link>https://zhi-class.ai/en/research/2511.correctnav/</link><pubDate>Sat, 08 Nov 2025 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/2511.correctnav/</guid><description>Existing vision-and-language navigation models often deviate from the correct trajectory when executing instructions.</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/2511.correctnav/featured.zh-cn.jpg"/></item><item><title>ToolVQA: A Dataset for Multi-step Reasoning VQA with External Tools</title><link>https://zhi-class.ai/en/research/2507.toolvqa/</link><pubDate>Mon, 14 Jul 2025 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/2507.toolvqa/</guid><description/><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/2507.toolvqa/featured.zh-cn.jpg"/></item><item><title>SimLauncher: Launching Sample-Efficient Real-world Robotic Reinforcement Learning via Simulation Pre-training</title><link>https://zhi-class.ai/en/research/2507.simlauncher/</link><pubDate>Sun, 06 Jul 2025 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/2507.simlauncher/</guid><description>Autonomous learning of dexterous, long-horizon robotic skills has been a longstanding pursuit of embodied AI.</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/2507.simlauncher/featured.zh-cn.jpg"/></item><item><title>Playing with Transformer at 30+ FPS via Next-Frame Diffusion</title><link>https://zhi-class.ai/en/research/2506.nextframed/</link><pubDate>Sun, 01 Jun 2025 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/2506.nextframed/</guid><description>In this work, we present Next-Frame Diffusion (NFD), an autoregressive diffusion transformer that incorporates block-wise causal attention, enabling iterative sampling and efficient inference via parallel token generation within each frame.</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/2506.nextframed/featured.zh-cn.png"/></item><item><title>Apply Hierarchical-Chain-of-Generation to Complex Attributes Text-to-3D Generation</title><link>https://zhi-class.ai/en/research/2505.gascol/</link><pubDate>Wed, 07 May 2025 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/2505.gascol/</guid><description/><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/2505.gascol/featured.zh-cn.png"/></item><item><title>OmniPhysGS: 3D Constitutive Gaussians for General Physics-based Dynamics Generation</title><link>https://zhi-class.ai/en/research/2504.omniphysgs/</link><pubDate>Thu, 24 Apr 2025 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/2504.omniphysgs/</guid><description/><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/2504.omniphysgs/featured.zh-cn.png"/></item><item><title>ChemAgent: Self-updating Memories in Large Language Models Improves Chemical Reasoning</title><link>https://zhi-class.ai/en/research/2501.chemagent/</link><pubDate>Fri, 03 Jan 2025 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/2501.chemagent/</guid><description>We present ChemAgent, a novel framework designed to improve the performance of LLMs through a dynamic, self-updating library.</description><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/2501.chemagent/featured.zh-cn.png"/></item><item><title>ProgressGym: Alignment with a Millennium of Moral Progress</title><link>https://zhi-class.ai/en/research/paper8/</link><pubDate>Tue, 10 Dec 2024 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/paper8/</guid><description/><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/paper8/feature.jpg"/></item><item><title>Autonomous Character-Scene Interaction Synthesis from Text Instruction</title><link>https://zhi-class.ai/en/research/paper10/</link><pubDate>Tue, 03 Dec 2024 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/paper10/</guid><description/><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/paper10/feature.jpg"/></item><item><title>DexGraspNet 2.0: Learning Generative Dexterous Grasping in Large-scale Synthetic Cluttered Scenes</title><link>https://zhi-class.ai/en/research/paper6/</link><pubDate>Wed, 06 Nov 2024 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/paper6/</guid><description/><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/paper6/feature.jpg"/></item><item><title>Benchmarking Open-instruction 6-DoF Object Rearrangement and A VLM-based Approach</title><link>https://zhi-class.ai/en/research/paper2/</link><pubDate>Mon, 14 Oct 2024 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/paper2/</guid><description/><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/paper2/feature.jpg"/></item><item><title>Exploring Conditional Multi-Modal Prompts for Zero-shot HOI Detection</title><link>https://zhi-class.ai/en/research/paper4/</link><pubDate>Sun, 29 Sep 2024 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/paper4/</guid><description/><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/paper4/feature.jpg"/></item><item><title>MacDiff: Unified Skeleton Modeling with Masked Conditional Diffusion</title><link>https://zhi-class.ai/en/research/paper3/</link><pubDate>Sun, 29 Sep 2024 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/paper3/</guid><description/><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/paper3/feature.jpg"/></item><item><title>Language Models Represent Beliefs of Self and Others</title><link>https://zhi-class.ai/en/research/paper7/</link><pubDate>Sun, 21 Jul 2024 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/paper7/</guid><description/><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/paper7/feature.jpg"/></item><item><title>Diff-BGM: A Diffusion Model for Video Background Music Generation</title><link>https://zhi-class.ai/en/research/paper9/</link><pubDate>Mon, 17 Jun 2024 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/paper9/</guid><description/><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/paper9/feature.jpg"/></item><item><title>Exploring the Potential of Large Foundation Models for Open-Vocabulary HOI Detection</title><link>https://zhi-class.ai/en/research/paper5/</link><pubDate>Mon, 17 Jun 2024 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/paper5/</guid><description/><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/paper5/feature.jpg"/></item><item><title>Scaling up dynamic human-scene interaction modeling</title><link>https://zhi-class.ai/en/research/paper1/</link><pubDate>Mon, 17 Jun 2024 00:00:00 +0000</pubDate><guid>https://zhi-class.ai/en/research/paper1/</guid><description/><media:content xmlns:media="http://search.yahoo.com/mrss/" url="https://zhi-class.ai/research/paper1/feature.jpg"/></item></channel></rss>