56 citations · 213 across the 61 of their papers we have counts for
62 papers
AerialDojo-200K: A Large-Scale Benchmark Suite for Open-World Aerial Object-Goal Search
Tongtong Feng, Xin Wang, Haoran Hou +9
Open-world aerial object-goal search is a foundational yet challenging task, requiring aerial agents to autonomously explore large-scale, unstructured three-dimensional environment…
Modularized Dynamic-Granularity Video LLM for Multi-Event Long Video Understanding
Wei Feng, Xin Wang, Yu-Wei Zhan +2
Video Large Language Models (Video LLMs) have made significant advancements in various video understanding tasks. However, long-video scenarios remain challenging due to the tensio…
Autonomous Video Generation with Counterfactual Controllability for Self-Evolving World Models
Xin Wang, Wenxuan Liu, Tongtong Feng +1
Large-scale video generation models are increasingly described as world models because they can learn rich spatiotemporal regularities from visual data. However, we argue that an i…
OOD-GraphLLM: Graph Large Language Model for Out-of-Distribution Generalized Drug Synergy Prediction
Xin Wang, Linxin Xiao, Yang Yao +1
Drug synergy prediction (DSP) aims to identify efficacious drug combinations under various cellular contexts with different targets. However, the continual emergence of novel compo…
WorldArena 2.0: Extending Embodied World Model Benchmarking on Modality, Functionality and Platform
Yu Shang, Yinzhou Tang, Yiding Ma +26
World models have emerged as a central paradigm for embodied intelligence, enabling agents to predict action-conditioned future and reason about environmental dynamics. However, ex…
A Unified Graph Language Model for Multi-Domain Multi-Task Graph Alignment Instruction Tuning
Haibo Chen, Xin Wang, Jiaheng Chao +2
Leveraging Graph Neural Networks (GNNs) as graph encoders and aligning the resulting representations with Large Language Models (LLMs) through alignment instruction tuning has beco…
Agentic AIs Are the Missing Paradigm for Out-of-Distribution Generalization in Foundation Models
Xin Wang, Haibo Chen, Wenxuan Liu +1
Foundation models (FMs) are increasingly deployed in open-world settings where distribution shift is the rule rather than the exception. The out-of-distribution (OOD) phenomena the…
Asymmetric Generative Recommendation via Kronecker Residual Bridge and Multi-Faceted Hierarchical Quantization
Bin Huang, Xin Wang, Junwei Pan +6
Generative Recommendation (GenRec) models reformulate recommendation as a sequence generation task, representing items as discrete Semantic IDs used symmetrically as both inputs an…
AV-Unified: A Unified Framework for Audio-visual Scene Understanding
Guangyao Li, Xin Wang, Wenwu Zhu
When humans perceive the world, they naturally integrate multiple audio-visual tasks within dynamic, real-world scenes. However, current works such as event localization, parsing,…
Self-evolving Embodied AI
Tongtong Feng, Xin Wang, Wenwu Zhu
Embodied Artificial Intelligence (AI) is an intelligent system formed by agents and their environment through active perception, embodied cognition, and action interaction. Existin…
Out-of-Distribution Generalization in Graph Foundation Models
Haoyang Li, Haibo Chen, Xin Wang +1
Graphs are a fundamental data structure for representing relational information in domains such as social networks, molecular systems, and knowledge graphs. However, graph learning…
Aerial World Model for Long-horizon Visual Generation and Navigation in 3D Space
Weichen Zhang, Peizhi Tang, Xin Zeng +12
Unmanned aerial vehicles (UAVs) have emerged as powerful embodied agents. One of the core abilities is autonomous navigation in large-scale three-dimensional environments. Existing…
PhyVLLM: Physics-Guided Video Language Model with Motion-Appearance Disentanglement
Yu-Wei Zhan, Xin Wang, Hong Chen +6
Video Large Language Models (Video LLMs) have shown impressive performance across a wide range of video-language tasks. However, they often fail in scenarios requiring a deeper und…
BiTAgent: A Task-Aware Modular Framework for Bidirectional Coupling between Multimodal Large Language Models and World Models
Yu-Wei Zhan, Xin Wang, Pengzhe Mao +3
Building generalist embodied agents requires a unified system that can interpret multimodal goals, model environment dynamics, and execute reliable actions across diverse real-worl…
Embodied AI: From LLMs to World Models
Tongtong Feng, Xin Wang, Yu-Gang Jiang +1
Embodied Artificial Intelligence (AI) is an intelligent system paradigm for achieving Artificial General Intelligence (AGI), serving as the cornerstone for various applications and…
U2UData+: A Scalable Swarm UAVs Autonomous Flight Dataset for Embodied Long-horizon Tasks
Tongtong Feng, Xin Wang, Feilin Han +2
Swarm UAV autonomous flight for Embodied Long-Horizon (ELH) tasks is crucial for advancing the low-altitude economy. However, existing methods focus only on specific basic tasks du…
Dynamic Mixture of Curriculum LoRA Experts for Continual Multimodal Instruction Tuning
Chendi Ge, Xin Wang, Zeyang Zhang +5
Continual multimodal instruction tuning is crucial for adapting Multimodal Large Language Models (MLLMs) to evolving tasks. However, most existing methods adopt a fixed architectur…
Towards Multimodal Graph Large Language Model
Xin Wang, Zeyang Zhang, Linxin Xiao +3
Multi-modal graphs, which integrate diverse multi-modal features and relations, are ubiquitous in real-world applications. However, existing multi-modal graph learning methods are…
Embodied-R: Collaborative Framework for Activating Embodied Spatial Reasoning in Foundation Models via Reinforcement Learning
Baining Zhao, Ziyou Wang, Jianjie Fang +7
Humans can perceive and reason about spatial relationships from sequential visual observations, such as egocentric video streams. However, how pretrained models acquire such abilit…
Modular-Cam: Modular Dynamic Camera-view Video Generation with LLM
Zirui Pan, Xin Wang, Yipeng Zhang +4
Text-to-Video generation, which utilizes the provided text prompt to generate high-quality videos, has drawn increasing attention and achieved great success due to the development…
Modular Machine Learning: An Indispensable Path towards New-Generation Large Language Models
Xin Wang, Haoyang Li, Haibo Chen +2
Large language models (LLMs) have substantially advanced machine learning research, including natural language processing, computer vision, data mining, etc., yet they still exhibi…
Towards Better Alignment: Training Diffusion Models with Reinforcement Learning Against Sparse Rewards
Zijing Hu, Fengda Zhang, Long Chen +6
Diffusion models have achieved remarkable success in text-to-image generation. However, their practical applications are hindered by the misalignment between generated images and c…
Behavior Importance-Aware Graph Neural Architecture Search for Cross-Domain Recommendation
Chendi Ge, Xin Wang, Ziwei Zhang +6
Cross-domain recommendation (CDR) mitigates data sparsity and cold-start issues in recommendation systems. While recent CDR approaches using graph neural networks (GNNs) capture co…
EvolvingAgent: Curriculum Self-evolving Agent with Continual World Model for Long-Horizon Tasks
Tongtong Feng, Xin Wang, Zekai Zhou +5
Completing Long-Horizon (LH) tasks in open-ended worlds is an important yet difficult problem for embodied agents. Existing approaches suffer from two key challenges: (1) they heav…