2 citations · 2 across the 15 of their papers we have counts for
15 papers
Color Pass-Through via Camera-Display Coupling
Ruikang Li, Molin Li, Jiarui Wu +3
When a real-world scene is captured by a smartphone camera and viewed on its screen, the displayed image often differs noticeably from the original scene in color, brightness, and…
InstantRetouch: Efficient and High-Fidelity Instruction-Guided Image Retouching with Bilateral Space
Jiarui Wu, Yujin Wang, Ruikang Li +3
Language-guided photo retouching aims to adjust color and tone while preserving geometry and texture. Recently, diffusion-based retouching shows a superior visual quality, but ofte…
Representation Collapse in Sequential Post-Training of Large Language Models
Yichen Liu, Mingyu Chen, Hao Wang +7
Large language models are now adapted through chains of post-training stages rather than through a single instruction-tuning pass. This paper studies whether such sequential post-t…
VQualA 2025 Challenge on Engagement Prediction for Short Videos: Methods and Results
Dasong Li, Sizhuo Ma, Hang Hua +40
This paper presents an overview of the VQualA 2025 Challenge on Engagement Prediction for Short Videos, held in conjunction with ICCV 2025. The challenge focuses on understanding a…
ArtiMuse: Fine-Grained Image Aesthetics Assessment with Joint Scoring and Expert-Level Understanding
Shuo Cao, Nan Ma, Jiayang Li +12
The rapid advancement of educational applications, artistic creation, and AI-generated content (AIGC) technologies has substantially increased practical requirements for comprehens…
AutoEvoEval: An Automated Framework for Evolving Close-Ended LLM Evaluation Data
JiaRu Wu, Mingwei Liu
Large language models (LLMs) have shown remarkable performance on various tasks, but existing evaluation benchmarks are often static and insufficient to fully assess their robustne…
: Generating Instructional Illustrations via Text-Conditioned Diffusion
Jing Bi, Pinxin Liu, Ali Vosoughi +3
The effective communication of procedural knowledge remains a significant challenge in natural language processing (NLP), as purely textual instructions often fail to convey comple…
S2R-HDR: A Large-Scale Rendered Dataset for HDR Fusion
Yujin Wang, Jiarui Wu, Yichen Bian +2
The generalization of learning-based high dynamic range (HDR) fusion is often limited by the availability of training data, as collecting large-scale HDR images from dynamic scenes…
Why Reasoning Matters? A Survey of Advancements in Multimodal Reasoning (v1)
Jing Bi, Susan Liang, Xiaofei Zhou +16
Reasoning is central to human intelligence, enabling structured problem-solving across diverse tasks. Recent advances in large language models (LLMs) have greatly enhanced their re…
Mitigating Hallucinations in Multimodal Spatial Relations through Constraint-Aware Prompting
Jiarui Wu, Zhuo Liu, Hangfeng He
Spatial relation hallucinations pose a persistent challenge in large vision-language models (LVLMs), leading to generate incorrect predictions about object positions and spatial co…
VERIFY: A Benchmark of Visual Explanation and Reasoning for Investigating Multimodal Reasoning Fidelity
Jing Bi, Junjia Guo, Susan Liang +8
Visual reasoning is central to human cognition, enabling individuals to interpret and abstractly understand their environment. Although recent Multimodal Large Language Models (MLL…
Goal Conditioned Reinforcement Learning for Photo Finishing Tuning
Jiarui Wu, Yujin Wang, Lingen Li +2
Photo finishing tuning aims to automate the manual tuning process of the photo finishing pipeline, like Adobe Lightroom or Darktable. Previous works either use zeroth-order optimiz…
NTO3D: Neural Target Object 3D Reconstruction with Segment Anything
Xiaobao Wei, Renrui Zhang, Jiarui Wu +4
Neural 3D reconstruction from multi-view images has recently attracted increasing attention from the community. Existing methods normally learn a neural field for the whole scene,…
PM-DETR: Domain Adaptive Prompt Memory for Object Detection with Transformers
Peidong Jia, Jiaming Liu, Senqiao Yang +3
The Transformer-based detectors (i.e., DETR) have demonstrated impressive performance on end-to-end object detection. However, transferring DETR to different data distributions may…
Exploring Sparse Visual Prompt for Domain Adaptive Dense Prediction
Senqiao Yang, Jiarui Wu, Jiaming Liu +6
The visual prompts have provided an efficient manner in addressing visual cross-domain problems. In previous works, Visual Domain Prompt (VDP) first introduces domain prompts to ta…