456 citations · 731 across the 11 of their papers we have counts for
12 papers
AUGUstus: Autonomous Driving VLA Model with Unified Generation and Understanding
Yuqi Ye, Caigao Jiang, Zhuonan Wang +12
Vision-language-action (VLA) models show strong potential for end-to-end autonomous driving by leveraging world knowledge and understanding to excel in long-tail scenarios. However…
Efficient Visual Question Answering Pipeline for Autonomous Driving via Scene Region Compression
Yuliang Cai, Dongqiangzi Ye, Zitian Chen +1
Autonomous driving increasingly relies on Visual Question Answering (VQA) to enable vehicles to understand complex surroundings by analyzing visual inputs and textual queries. Curr…
Meta-Router: Bridging Gold-standard and Preference-based Evaluations in Large Language Model Routing
Yichi Zhang, Fangzheng Xie, Shu Yang +1
In language tasks that require extensive human--model interaction, deploying a single "best" model for every query can be expensive. To reduce inference cost while preserving the q…
RSVP: Reasoning Segmentation via Visual Prompting and Multi-modal Chain-of-Thought
Yi Lu, Jiawang Cao, Yongliang Wu +6
Multi-modal Large Language Models (MLLMs) have demonstrated remarkable reasoning capability while lack explicit mechanisms for visual grounding and segmentation, creating a gap bet…
Leveraging Graph-based Cross-modal Information Fusion for Neural Sign Language Translation
Jiangbin Zheng, Siyuan Li, Cheng Tan +3
Sign Language (SL), as the mother tongue of the deaf community, is a special visual language that most hearing people cannot understand. In recent years, neural Sign Language Trans…
A Comprehensive Study of Deep Video Action Recognition
Yi Zhu, Xinyu Li, Chunhui Liu +7
Video action recognition is one of the representative tasks for video understanding. Over the last decade, we have witnessed great advancements in video action recognition thanks t…
Improving Semantic Segmentation via Self-Training
Yi Zhu, Zhongyue Zhang, Chongruo Wu +6
Deep learning usually achieves the best results with complete supervision. In the case of semantic segmentation, this means that large amounts of pixelwise annotations are required…
A Tailored Pre-Training Model for Task-Oriented Dialog Generation
Jing Gu, Qingyang Wu, Chongruo Wu +2
The recent success of large pre-trained language models such as BERT and GPT-2 has suggested the effectiveness of incorporating language priors in downstream dialog generation task…
ResNeSt: Split-Attention Networks
Hang Zhang, Chongruo Wu, Zhongyue Zhang +9
It is well known that featuremap attention and multi-path representation are important for visual recognition. In this paper, we present a modularized architecture, which applies t…
HPLFlowNet: Hierarchical Permutohedral Lattice FlowNet for Scene Flow Estimation on Large-scale Point Clouds
Xiuye Gu, Yijie Wang, Chongruo wu +2
We present a novel deep neural network architecture for end-to-end scene flow estimation that directly operates on large-scale 3D point clouds. Inspired by Bilateral Convolutional…
Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
Xuanqing Liu, Yao Li, Chongruo Wu +1
We present a new algorithm to train a robust neural network against adversarial attacks. Our algorithm is motivated by the following two ideas. First, although recent work has demo…
Cruciform: Solving Crosswords with Natural Language Processing
Dragomir Radev, Rui Zhang, Steve Wilson +8
Crossword puzzles are popular word games that require not only a large vocabulary, but also a broad knowledge of topics. Answering each clue is a natural language task on its own a…