14 citations · 20 across the 10 of their papers we have counts for
10 papers
UR-VC: Unsupervised Robotic Value Correction for Time-Derived Progress Proxies
Lirui Zhao, Modi Shi, Li Chen +3
Modern robot learning systems increasingly rely on dense progress or value signals to evaluate intermediate states, guide policy learning, and detect task completion, making the qu…
: Resource-Aware Robust Manipulation via Taming Distributional Inconsistencies
Checheng Yu, Chonghao Sima, Gangcheng Jiang +14
High-reliability long-horizon robotic manipulation has traditionally relied on large-scale data and compute to understand complex real-world dynamics. However, we identify that the…
UniFork: Exploring Modality Alignment for Unified Multimodal Understanding and Generation
Teng Li, Quanfeng Lu, Lirui Zhao +5
Unified image understanding and generation has emerged as a promising paradigm in multimodal artificial intelligence. Despite recent progress, the optimal architectural design for…
OpenING: A Comprehensive Benchmark for Judging Open-ended Interleaved Image-Text Generation
Pengfei Zhou, Xiaopeng Peng, Jiajun Song +15
Multimodal Large Language Models (MLLMs) have made significant strides in visual understanding and generation tasks. However, generating interleaved image-text content remains a ch…
Diffree: Text-Guided Shape Free Object Inpainting with Diffusion Model
Lirui Zhao, Tianshuo Yang, Wenqi Shao +5
This paper addresses an important problem of object addition for images with only text guidance. It is challenging because the new object must be integrated seamlessly into the ima…
Lumina-Next: Making Lumina-T2X Stronger and Faster with Next-DiT
Le Zhuo, Ruoyi Du, Han Xiao +19
Lumina-T2X is a nascent family of Flow-based Large Diffusion Transformers that establishes a unified framework for transforming noise into various modalities, such as images and vi…
DiffAgent: Fast and Accurate Text-to-Image API Selection with Large Language Model
Lirui Zhao, Yue Yang, Kaipeng Zhang +5
Text-to-image (T2I) generative models have attracted significant attention and found extensive applications within and beyond academic research. For example, the Civitai community,…
Boosting the Cross-Architecture Generalization of Dataset Distillation through an Empirical Study
Lirui Zhao, Yuxin Zhang, Fei Chao +1
The poor cross-architecture generalization of dataset distillation greatly weakens its practical significance. This paper attempts to mitigate this issue through an empirical study…
Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs
Yuxin Zhang, Lirui Zhao, Mingbao Lin +6
The ever-increasing large language models (LLMs), though opening a potential path for the upcoming artificial general intelligence, sadly drops a daunting obstacle on the way towar…
OmniQuant: Omnidirectionally Calibrated Quantization for Large Language Models
Wenqi Shao, Mengzhao Chen, Zhaoyang Zhang +7
Large language models (LLMs) have revolutionized natural language processing tasks. However, their practical deployment is hindered by their immense memory and computation requirem…