68 citations · 124 across the 17 of their papers we have counts for
18 papers
MIRA: Multimodal Iterative Reasoning Agent for Image Editing
Ziyun Zeng, Hang Hua, Jiebo Luo
Instruction-guided image editing offers an intuitive way for users to edit images with natural language. However, diffusion-based editing models often struggle to accurately interp…
Latent Chain-of-Thought for Visual Reasoning
Guohao Sun, Hang Hua, Jian Wang +5
Chain-of-thought (CoT) reasoning is critical for improving the interpretability and reliability of Large Vision-Language Models (LVLMs). However, existing training algorithms such…
MMIG-Bench: Towards Comprehensive and Explainable Evaluation of Multi-Modal Image Generation Models
Hang Hua, Ziyun Zeng, Yizhi Song +5
Recent multimodal image generators such as GPT-4o, Gemini 2.0 Flash, and Gemini 2.5 Pro excel at following complex instructions, editing images and maintaining concept consistency.…
The Tenth NTIRE 2025 Efficient Super-Resolution Challenge Report
Bin Ren, Hang Guo, Lei Sun +143
This paper presents a comprehensive review of the NTIRE 2025 Challenge on Single-Image Efficient Super-Resolution (ESR). The challenge aimed to advance the development of deep mode…
FINECAPTION: Compositional Image Captioning Focusing on Wherever You Want at Any Granularity
Hang Hua, Qing Liu, Lingzhi Zhang +5
The advent of large Vision-Language Models (VLMs) has significantly advanced multimodal tasks, enabling more sophisticated and accurate reasoning across various applications, inclu…
MMCOMPOSITION: Revisiting the Compositionality of Pre-trained Vision-Language Models
Hang Hua, Yunlong Tang, Ziyun Zeng +5
The advent of large Vision-Language Models (VLMs) has significantly advanced multimodal understanding, enabling more sophisticated and accurate integration of visual and textual in…
PromptFix: You Prompt and We Fix the Photo
Yongsheng Yu, Ziyun Zeng, Hang Hua +2
Diffusion models equipped with language models demonstrate excellent controllability in image generation tasks, allowing image processing to adhere to human instructions. However,…
BattleAgent: Multi-modal Dynamic Emulation on Historical Battles to Complement Historical Analysis
Shuhang Lin, Wenyue Hua, Lingyao Li +7
This paper presents BattleAgent, an emulation system that combines the Large Vision-Language Model and Multi-agent System. This novel system aims to simulate complex dynamic intera…
FINEMATCH: Aspect-based Fine-grained Image and Text Mismatch Detection and Correction
Hang Hua, Jing Shi, Kushal Kafle +5
Recent progress in large-scale pre-training has led to the development of advanced vision-language models (VLMs) with remarkable proficiency in comprehending and generating multimo…
V2Xum-LLM: Cross-Modal Video Summarization with Temporal Prompt Instruction Tuning
Hang Hua, Yolo Yunlong Tang, Chenliang Xu +1
Video summarization aims to create short, accurate, and cohesive summaries of longer videos. Despite the existence of various video summarization datasets, a notable limitation is…
Empowering LLMs with Pseudo-Untrimmed Videos for Audio-Visual Temporal Understanding
Yolo Yunlong Tang, Daiki Shimada, Jing Bi +3
Large language models (LLMs) have demonstrated remarkable capabilities in natural language and multimodal domains. By fine-tuning multimodal LLMs with temporal annotations from wel…
GaussianStyle: Gaussian Head Avatar via StyleGAN
Pinxin Liu, Luchuan Song, Daoan Zhang +5
Existing methods like Neural Radiation Fields (NeRF) and 3D Gaussian Splatting (3DGS) have made significant strides in facial attribute control such as facial animation and compone…
VideoXum: Cross-modal Visual and Textural Summarization of Videos
Jingyang Lin, Hang Hua, Ming Chen +4
Video summarization aims to distill the most important information from a source video to produce either an abridged clip or a textual narrative. Traditionally, different methods h…
PromptCap: Prompt-Guided Task-Aware Image Captioning
Yushi Hu, Hang Hua, Zhengyuan Yang +3
Knowledge-based visual question answering (VQA) involves questions that require world knowledge beyond the image to yield the correct answer. Large language models (LMs) like GPT-3…
Improving Pre-trained Language Model Fine-tuning with Noise Stability Regularization
Hang Hua, Xingjian Li, Dejing Dou +2
The advent of large-scale pre-trained language models has contributed greatly to the recent progress in natural language processing. Many state-of-the-art language models are first…
Noise Stability Regularization for Improving BERT Fine-tuning
Hang Hua, Xingjian Li, Dejing Dou +2
Fine-tuning pre-trained language models such as BERT has become a common practice dominating leaderboards across various NLP tasks. Despite its recent success and wide adoption, th…
Tracking Public Opinion in China through Various Stages of the COVID-19 Pandemic
Yuqi Gao, Hang Hua, Jiebo Luo
In recent months, COVID-19 has become a global pandemic and had a huge impact on the world. People under different conditions have very different attitudes toward the epidemic. Due…
Controllable Unsupervised Text Attribute Transfer via Editing Entangled Latent Representation
Ke Wang, Hang Hua, Xiaojun Wan
Unsupervised text attribute transfer automatically transforms a text to alter a specific attribute (e.g. sentiment) without using any parallel data, while simultaneously preserving…