2 citations · 3 across the 15 of their papers we have counts for
6 papers · 1 filter
Multi-Reward as Condition for Instruction-based Image Editing
Xin Gu, Ming Li, Libo Zhang +4
High-quality training triplets (instruction, original image, edited image) are essential for instruction-based image editing. Predominant training datasets (e.g., InsPix2Pix) are c…
DiffLM: Controllable Synthetic Data Generation via Diffusion Language Models
Ying Zhou, Xinyao Wang, Yulei Niu +6
Recent advancements in large language models (LLMs) have significantly enhanced their knowledge and generative capabilities, leading to a surge of interest in leveraging LLMs for h…
AIPO: Improving Training Objective for Iterative Preference Optimization
Yaojie Shen, Xinyao Wang, Yulei Niu +5
Preference Optimization (PO), is gaining popularity as an alternative choice of Proximal Policy Optimization (PPO) for aligning Large Language Models (LLMs). Recent research on ali…
Beyond Raw Videos: Understanding Edited Videos with Large Multimodal Model
Lu Xu, Sijie Zhu, Chunyuan Li +7
The emerging video LMMs (Large Multimodal Models) have achieved significant improvements on generic video understanding in the form of VQA (Visual Question Answering), where the ra…
CuMo: Scaling Multimodal LLM with Co-Upcycled Mixture-of-Experts
Jiachen Li, Xinyao Wang, Sijie Zhu +6
Recent advancements in Multimodal Large Language Models (LLMs) have focused primarily on scaling by increasing text-image pair data and enhancing LLMs to improve performance on mul…
Edit3K: Universal Representation Learning for Video Editing Components
Xin Gu, Libo Zhang, Fan Chen +4
This paper focuses on understanding the predominant video creation pipeline, i.e., compositional video editing with six main types of editing components, including video effects, a…