3 citations · 3 across the 11 of their papers we have counts for
11 papers
DuoGen: Towards General Purpose Interleaved Multimodal Generation
Min Shi, Xiaohui Zeng, Jiannan Huang +13
Interleaved multimodal generation enables capabilities beyond unimodal generation models, such as step-by-step instructional guides, visual planning, and generating visual drafts f…
A Cloud-Based Cross-Modal Transformer for Emotion Recognition and Adaptive Human-Computer Interaction
Ziwen Zhong, Zhitao Shu, Yue Zhao
Emotion recognition is a fundamental component of next-generation human-computer interaction (HCI), enabling machines to perceive, understand, and respond to users' affective state…
Pelican-VL 1.0: A Foundation Brain Model for Embodied Intelligence
Yi Zhang, Che Liu, Xiancong Ren +20
This report presents Pelican-VL 1.0, a new family of open-source embodied brain models with parameter scales ranging from 7 billion to 72 billion. Our explicit mission is clearly s…
MapReduce LoRA: Advancing the Pareto Front in Multi-Preference Optimization for Generative Models
Chieh-Yun Chen, Zhonghao Wang, Qi Chen +10
Reinforcement learning from human feedback (RLHF) with reward models has advanced alignment of generative models to human aesthetic and perceptual preferences. However, jointly opt…
Score Matching on Large Geometric Graphs for Cosmology Generation
Diana-Alexandra Onutu, Yue Zhao, Joaquin Vanschoren +1
Generative models are a promising tool to produce cosmological simulations but face significant challenges in scalability, physical consistency, and adherence to domain symmetries,…
Language-Image Alignment with Fixed Text Encoders
Jingfeng Yang, Ziyang Wu, Yue Zhao +1
Currently, the most dominant approach to establishing language-image alignment is to pre-train text and image encoders jointly through contrastive learning, such as CLIP and its va…
Interactive Post-Training for Vision-Language-Action Models
Shuhan Tan, Kairan Dou, Yue Zhao +1
We introduce RIPT-VLA, a simple and scalable reinforcement-learning-based interactive post-training paradigm that fine-tunes pretrained Vision-Language-Action (VLA) models using on…
Automatic Evaluation for Text-to-image Generation: Task-decomposed Framework, Distilled Training, and Meta-evaluation Benchmark
Rong-Cheng Tu, Zi-Ao Ma, Tian Lan +3
Driven by the remarkable progress in diffusion models, text-to-image generation has made significant strides, creating a pressing demand for automatic quality evaluation of generat…
BA-Net: Bridge Attention in Deep Neural Networks
Ronghui Zhang, Runzong Zou, Yue Zhao +5
Attention mechanisms, particularly channel attention, have become highly influential in numerous computer vision tasks. Despite their effectiveness, many existing methods primarily…
DreamScape: 3D Scene Creation via Gaussian Splatting joint Correlation Modeling
Yueming Zhao, Xuening Yuan, Hongyu Yang +1
Recent advances in text-to-3D creation integrate the potent prior of Diffusion Models from text-to-image generation into 3D domain. Nevertheless, generating 3D scenes with multiple…
Forging Vision Foundation Models for Autonomous Driving: Challenges, Methodologies, and Opportunities
Xu Yan, Haiming Zhang, Yingjie Cai +13
The rise of large foundation models, trained on extensive datasets, is revolutionizing the field of AI. Models such as SAM, DALL-E2, and GPT-4 showcase their adaptability by extrac…