3 citations · 4 across the 10 of their papers we have counts for
11 papers
UniReason 1.0: A Unified Reasoning Framework for World Knowledge Aligned Image Generation and Editing
Dianyi Wang, Chaofan Ma, Feng Han +8
Unified multimodal models often struggle with complex synthesis tasks that demand deep reasoning, and typically treat text-to-image generation and image editing as isolated capabil…
DeepGen 1.0: A Lightweight Unified Multimodal Model for Advancing Image Generation and Editing
Dianyi Wang, Ruihang Li, Feng Han +17
Current unified multimodal models for image generation and editing typically rely on massive parameter scales (e.g., >10B), entailing prohibitive training costs and deployment foot…
Unified Personalized Reward Model for Vision Generation
Yibin Wang, Yuhang Zang, Feng Han +4
Recent advancements in multimodal reward models (RMs) have significantly propelled the development of visual generation. Existing frameworks typically adopt Bradley-Terry-style pre…
FairExpand: Individual Fairness on Graphs with Partial Similarity Information
Rebecca Salganik, Yibin Wang, Guillaume Salha-Galvan +1
Individual fairness, which requires that similar individuals should be treated similarly by algorithmic systems, has become a central principle in fair machine learning. Individual…
UniREditBench: A Unified Reasoning-based Image Editing Benchmark
Feng Han, Yibin Wang, Chenglin Li +7
Recent advances in multi-modal generative models have driven substantial improvements in image editing. However, current generative models still struggle with handling diverse and…
Lumina-DiMOO: An Omni Diffusion Large Language Model for Multi-Modal Generation and Understanding
Yi Xin, Qi Qin, Siqi Luo +29
We introduce Lumina-DiMOO, an open-source foundational model for seamless multi-modal generation and understanding. Lumina-DiMOO sets itself apart from prior unified models by util…
UniGenBench++: A Unified Semantic Evaluation Benchmark for Text-to-Image Generation
Yibin Wang, Zhimin Li, Yuhang Zang +8
Recent progress in text-to-image (T2I) generation underscores the importance of reliable benchmarks in evaluating how accurately generated images reflect the semantics of their tex…
X-Omni: Reinforcement Learning Makes Discrete Autoregressive Image Generative Models Great Again
Zigang Geng, Yibing Wang, Yeyao Ma +10
Numerous efforts have been made to extend the ``next token prediction'' paradigm to visual contents, aiming to create a unified approach for both image generation and understanding…
EduBot -- Can LLMs Solve Personalized Learning and Programming Assignments?
Yibin Wang, Jiaxi Xie, Lakshminarayanan Subramanian
The prevalence of Large Language Models (LLMs) is revolutionizing the process of writing code. General and code LLMs have shown impressive performance in generating standalone func…
Kangaroo: A Powerful Video-Language Model Supporting Long-context Video Input
Jiajun Liu, Yibing Wang, Hanghang Ma +6
Rapid advancements have been made in extending Large Language Models (LLMs) to Large Multi-modal Models (LMMs). However, extending input modality of LLMs to video data remains a ch…
Behavior Generation with Latent Actions
Seungjae Lee, Yibin Wang, Haritheja Etukuru +3
Generative modeling of complex behaviors from labeled datasets has been a longstanding problem in decision making. Unlike language or image generation, decision making requires mod…