activity
20242026
most citedSecuring the Skies: A Comprehensive Survey on Anti-UAV Methods, Benchmarking, and Future Directions

1 citations · 1 across the 9 of their papers we have counts for

collaborators

11 papers

cs.AI2026

Agentic World Modeling: Foundations, Capabilities, Laws, and Beyond

Meng Chu, Xuan Billy Zhang, Kevin Qinghong Lin +47

As AI systems move from generating text to accomplishing goals through sustained interaction, the ability to model environment dynamics becomes a central bottleneck. Agents that ma…

cs.CV2026

Language-Conditioned World Modeling for Visual Navigation

Yifei Dong, Fengyi Wu, Yilong Dai +10

We study language-conditioned visual navigation (LCVN), in which an embodied agent is asked to follow a natural language instruction based only on an initial egocentric observation…

cs.CV2026

Emotion-LLaMAv2 and MMEVerse: A New Framework and Benchmark for Multimodal Emotion Understanding

Xiaojiang Peng, Jingyi Chen, Zebang Cheng +11

Understanding human emotions from multimodal signals poses a significant challenge in affective computing and human-robot interaction. While multimodal large language models (MLLMs…

cs.AI2025

Towards Unified World Models for Visual Navigation via Memory-Augmented Planning and Foresight

Yifei Dong, Fengyi Wu, Guangyu Chen +9

Enabling embodied agents to imagine future states is essential for robust and generalizable visual navigation. Yet, state-of-the-art systems typically rely on modular designs that…

cs.CV2025

GoViG: Goal-Conditioned Visual Navigation Instruction Generation via Multimodal Reasoning

Fengyi Wu, Yifei Dong, Yilong Dai +7

We introduce Goal-Conditioned Visual Navigation Instruction Generation (GoViG), a new task that aims to generate contextually coherent navigation instructions solely from egocentri…

cs.CV2025

StableAnimator++: Overcoming Pose Misalignment and Face Distortion for Human Image Animation

Shuyuan Tu, Zhen Xing, Xintong Han +5

Current diffusion models for human image animation often struggle to maintain identity (ID) consistency, especially when the reference image and driving video differ significantly…