6 citations · 9 across the 9 of their papers we have counts for
9 papers
Spatia: Video Generation with Updatable Spatial Memory
Jinjing Zhao, Fangyun Wei, Zhening Liu +3
Existing video generation models struggle to maintain long-term spatial and temporal consistency due to the dense, high-dimensional nature of video signals. To overcome this limita…
CustomX: Unified Character, Action, and Scene Customization in Video World Models
Yitong Wang, Fangyun Wei, Hongyang Zhang +2
Recent advances in world models have greatly enhanced interactive environment simulation. Existing methods mainly fall into two categories: (1) static world generation models, whic…
From Virtual Games to Real-World Play
Wenqiang Sun, Fangyun Wei, Jinjing Zhao +5
We introduce RealPlay, a neural network-based real-world game engine that enables interactive video generation from user control signals. Unlike prior works focused on game-style v…
EAGLE-3: Scaling up Inference Acceleration of Large Language Models via Training-Time Test
Yuhui Li, Fangyun Wei, Chao Zhang +1
The sequential nature of modern LLMs makes them expensive and slow, and speculative sampling has proven to be an effective solution to this problem. Methods like EAGLE perform auto…
BACON: Improving Clarity of Image Captions via Bag-of-Concept Graphs
Zhantao Yang, Ruili Feng, Keyu Yan +13
Advancements in large Vision-Language Models have brought precise, accurate image captioning, vital for advancing multi-modal image understanding and processing. Yet these captions…
EAGLE-2: Faster Inference of Language Models with Dynamic Draft Trees
Yuhui Li, Fangyun Wei, Chao Zhang +1
Inference with modern Large Language Models (LLMs) is expensive and time-consuming, and speculative sampling has proven to be an effective solution. Most speculative sampling metho…
Revisiting Referring Expression Comprehension Evaluation in the Era of Large Multimodal Models
Jierun Chen, Fangyun Wei, Jinjing Zhao +5
Referring expression comprehension (REC) involves localizing a target instance based on a textual description. Recent advancements in REC have been driven by large multimodal model…
AnyTool: Self-Reflective, Hierarchical Agents for Large-Scale API Calls
Yu Du, Fangyun Wei, Hongyang Zhang
We introduce AnyTool, a large language model agent designed to revolutionize the utilization of a vast array of tools in addressing user queries. We utilize over 16,000 APIs from R…
EAGLE: Speculative Sampling Requires Rethinking Feature Uncertainty
Yuhui Li, Fangyun Wei, Chao Zhang +1
Autoregressive decoding makes the inference of Large Language Models (LLMs) time-consuming. In this paper, we reconsider speculative sampling and derive two key observations. First…