7 citations · 32 across the 52 of their papers we have counts for
29 papers · 1 filter
Counterfactual Anatomy-guided Spatial-Temporal Decoding for Annotation-Free Hallucination Mitigation in Medical VLMs
Yifan Lu, Adinath Dukre, Abhijit Das +4
Medical vision-language models (Med-VLMs) have demonstrated strong performance on medical visual question answering, yet they remain prone to hallucination, generating clinically u…
RA-ClipScore: Making Generative Model Evaluation More Interpretable
Yifan Lu, Taras Kucherenko, Hedvig Kjellström +1
Generative models can produce images nearly indistinguishable from real data, yet rigorous and interpretable evaluation remains challenging. Conventional metrics such as FID provid…
NVIDIA OmniDreams: Real-Time Generative World Model for Closed-Loop Autonomous Vehicle Simulation
NVIDIA, :, Aarti Basant +33
As autonomous vehicle capabilities advance, the safe evaluation of driving policies in long-tail scenarios remains a critical bottleneck. In closed-loop simulation, the driving pol…
Gaussian Mixture Modeling for Event-Aware Visual Allocation in Long Video Understanding
Yifan Lu, Ziqi Zhang, Chunfeng Yuan +3
Large Vision-Language Models (LVLMs) face significant challenges in long video understanding due to the excessive computational cost and information loss associated with uniform sa…
PROTON: Prototype-Based Test-Time Online OOD Detection for Medical VLMs
Abhijit Das, Nichula Wasalathilaka, Yifan Lu +4
Medical vision-language models (VLMs) enable zero-shot clinical image classification, yet reliably detecting out-of-distribution (OOD) inputs at deployment remains an open problem.…
PiD: Fast and High-Resolution Latent Decoding with Pixel Diffusion
Yifan Lu, Qi Wu, Jay Zhangjie Wu +4
Most practical high-resolution text-to-image systems, including latent diffusion and autoregressive models, perform generation in a compact latent space, and a decoder maps the gen…
LongCat-Next: Lexicalizing Modalities as Discrete Tokens
Meituan LongCat Team, Bin Xiao, Chao Wang +86
The prevailing Next-Token Prediction (NTP) paradigm has driven the success of large language models through discrete autoregressive modeling. However, contemporary multimodal syste…
World Simulation with Video Foundation Models for Physical AI
NVIDIA, :, Arslan Ali +87
We introduce [Cosmos-Predict2.5], the latest generation of the Cosmos World Foundation Models for Physical AI. Built on a flow-based architecture, [Cosmos-Predict2.5] unifies Text2…
ChronoEdit: Towards Temporal Reasoning for Image Editing and World Simulation
Jay Zhangjie Wu, Xuanchi Ren, Tianchang Shen +11
Recent advances in large generative models have greatly enhanced both image editing and in-context image generation, yet a critical gap remains in ensuring physical consistency, wh…
Mitigating Hallucinations in Large Vision-Language Models by Self-Injecting Hallucinations
Yifan Lu, Ziqi Zhang, Chunfeng Yuan +5
Large Vision-Language Models (LVLMs) suffer from serious hallucination problems, where the model-generated responses are inconsistent with the visual inputs. Existing hallucination…
StreamAgent: Towards Anticipatory Agents for Streaming Video Understanding
Haolin Yang, Feilong Tang, Lingxiao Zhao +10
Real-time streaming video understanding in domains such as autonomous driving and intelligent surveillance poses challenges beyond conventional offline video processing, requiring…
Cosmos-Drive-Dreams: Scalable Synthetic Driving Data Generation with World Foundation Models
Xuanchi Ren, Yifan Lu, Tianshi Cao +13
Collecting and annotating real-world data for safety-critical physical AI systems, such as Autonomous Vehicle (AV), is time-consuming and costly. It is especially challenging to ca…
Cosmos-Transfer1: Conditional World Generation with Adaptive Multimodal Control
NVIDIA, :, Hassan Abu Alhaija +38
We introduce Cosmos-Transfer, a conditional world generation model that can generate world simulations based on multiple spatial control inputs of various modalities such as segmen…
GEN3C: 3D-Informed World-Consistent Video Generation with Precise Camera Control
Xuanchi Ren, Tianchang Shen, Jiahui Huang +7
We present GEN3C, a generative video model with precise Camera Control and temporal 3D Consistency. Prior video models already generate realistic videos, but they tend to leverage…
RoCo-Sim: Enhancing Roadside Collaborative Perception through Foreground Simulation
Yuwen Du, Anning Hu, Zichen Chao +6
Roadside Collaborative Perception refers to a system where multiple roadside units collaborate to pool their perceptual data, assisting vehicles in enhancing their environmental aw…
InfiniCube: Unbounded and Controllable Dynamic 3D Driving Scene Generation with World-Guided Video Models
Yifan Lu, Xuanchi Ren, Jiawei Yang +8
We present InfiniCube, a scalable method for generating unbounded dynamic 3D driving scenes with high fidelity and controllability. Previous methods for scene generation either suf…
SCube: Instant Large-Scale Scene Reconstruction using VoxSplats
Xuanchi Ren, Yifan Lu, Hanxue Liang +6
We present SCube, a novel method for reconstructing large-scale 3D scenes (geometry, appearance, and semantics) from a sparse set of posed images. Our method encodes reconstructed…
Self-Localized Collaborative Perception
Zhenyang Ni, Zixing Lei, Yifan Lu +4
Collaborative perception has garnered considerable attention due to its capacity to address several inherent challenges in single-agent perception, including occlusion and out-of-r…
Towards Collaborative Autonomous Driving: Simulation Platform and End-to-End System
Genjia Liu, Yue Hu, Chenxin Xu +8
Vehicle-to-everything-aided autonomous driving (V2X-AD) has a huge potential to provide a safer driving solution. Despite extensive researches in transportation and communication t…
Editable Scene Simulation for Autonomous Driving via Collaborative LLM-Agents
Yuxi Wei, Zi Wang, Yifan Lu +5
Scene simulation in autonomous driving has gained significant attention because of its huge potential for generating customized data. However, existing editable scene simulation ap…
An Extensible Framework for Open Heterogeneous Collaborative Perception
Yifan Lu, Yue Hu, Yiqi Zhong +3
Collaborative perception aims to mitigate the limitations of single-agent perception, such as occlusions, by facilitating data exchange among multiple agents. However, most current…
Set Prediction Guided by Semantic Concepts for Diverse Video Captioning
Yifan Lu, Ziqi Zhang, Chunfeng Yuan +4
Diverse video captioning aims to generate a set of sentences to describe the given video in various aspects. Mainstream methods are trained with independent pairs of a video and a…
Asynchrony-Robust Collaborative Perception via Bird's Eye View Flow
Sizhe Wei, Yuxi Wei, Yue Hu +4
Collaborative perception can substantially boost each agent's perception ability by facilitating communication among multiple agents. However, temporal asynchrony among agents is i…
Collaboration Helps Camera Overtake LiDAR in 3D Detection
Yue Hu, Yifan Lu, Runsheng Xu +3
Camera-only 3D detection provides an economical solution with a simple configuration for localizing objects in 3D space compared to LiDAR-based detection systems. However, a major…