2 citations · 3 across the 16 of their papers we have counts for
6 papers · 1 filter
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…
Batch Loss Score for Dynamic Data Pruning
Qing Zhou, Bingxuan Zhao, Tao Yang +3
Dynamic data pruning accelerates deep learning by selectively omitting less informative samples during training. While per-sample loss is a common importance metric, obtaining it c…
Efficient Reasoning via Thought Compression for Language Segmentation
Qing Zhou, Shiyu Zhang, Yuyu Jia +4
Chain-of-thought (CoT) reasoning has significantly improved the performance of large multimodal models in language-guided segmentation, yet its prohibitive computational cost, stem…
Beyond Prompt Degradation: Prototype-guided Dual-pool Prompting for Incremental Object Detection
Yaoteng Zhang, Zhou Qing, Junyu Gao +1
Incremental Object Detection (IOD) aims to continuously learn new object categories without forgetting previously learned ones. Recently, prompt-based methods have gained popularit…
UNICBench: UNIfied Counting Benchmark for MLLM
Chenggang Rong, Tao Han, Zhiyuan Zhao +5
Counting is a core capability for multimodal large language models (MLLMs), yet there is no unified counting dataset to rigorously evaluate this ability across image, text, and aud…
One-Shot Crowd Counting With Density Guidance For Scene Adaptation
Jiwei Chen, Qi Wang, Junyu Gao +3
Crowd scenes captured by cameras at different locations vary greatly, and existing crowd models have limited generalization for unseen surveillance scenes. To improve the generaliz…