7 citations · 13 across the 26 of their papers we have counts for
29 papers
Complexity-Aware Surgical Video Reasoning Segmentation with Digital Twin and Context Memory
Yiqing Shen, Mathias Unberath
Conventional surgical segmentation relies on closed-set categories or explicit text queries, which cannot resolve implicit queries that require reasoning about workflows, instrumen…
AffordTissue: Dense Affordance Prediction for Tool-Action Specific Tissue Interaction
Aiza Maksutova, Lalithkumar Seenivasan, Hao Ding +5
Surgical action automation has progressed rapidly toward achieving surgeon-like dexterous control, driven primarily by advances in learning from demonstration and vision-language-a…
Point-Supervised Skeleton-Based Human Action Segmentation
Hongsong Wang, Yiqin Shen, Pengbo Yan +2
Skeleton-based temporal action segmentation is a fundamental yet challenging task, playing a crucial role in enabling intelligent systems to perceive and respond to human activitie…
Counterfactual World Models via Digital Twin-conditioned Video Diffusion
Yiqing Shen, Aiza Maksutova, Chenjia Li +1
World models learn to predict the temporal evolution of visual observations given a control signal, potentially enabling agents to reason about environments through forward simulat…
Text-Driven Reasoning Video Editing via Reinforcement Learning on Digital Twin Representations
Yiqing Shen, Chenjia Li, Mathias Unberath
Text-driven video editing enables users to modify video content only using text queries. While existing methods can modify video content if explicit descriptions of editing targets…
Reasoning Text-to-Video Retrieval via Digital Twin Video Representations and Large Language Models
Yiqing Shen, Chenxiao Fan, Chenjia Li +1
The goal of text-to-video retrieval is to search large databases for relevant videos based on text queries. Existing methods have progressed to handling explicit queries where the…
Fast Reasoning Segmentation for Images and Videos
Yiqing Shen, Mathias Unberath
Reasoning segmentation enables open-set object segmentation via implicit text queries, therefore serving as a foundation for embodied agents that should operate autonomously in rea…
Constructing and Interpreting Digital Twin Representations for Visual Reasoning via Reinforcement Learning
Yiqing Shen, Mathias Unberath
Visual reasoning may require models to interpret images and videos and respond to implicit text queries across diverse output formats, from pixel-level segmentation masks to natura…
TwinOR: Photorealistic Digital Twins of Dynamic Operating Rooms for Embodied AI Research
Han Zhang, Yiqing Shen, Roger D. Soberanis-Mukul +11
Developing embodied AI for intelligent surgical systems requires safe, controllable environments for continual learning and evaluation. However, safety regulations and operational…
Understanding the Implicit User Intention via Reasoning with Large Language Model for Image Editing
Yijia Wang, Yiqing Shen, Weiming Chen +1
Existing image editing methods can handle simple editing instructions very well. To deal with complex editing instructions, they often need to jointly fine-tune the large language…
Hyperspectral Image Recovery Constrained by Multi-Granularity Non-Local Self-Similarity Priors
Zhuoran Peng, Yiqing Shen
Hyperspectral image (HSI) recovery, as an upstream image processing task, holds significant importance for downstream tasks such as classification, segmentation, and detection. In…
Mitigating Hallucinations in Large Language Models via Causal Reasoning
Yuangang Li, Yiqing Shen, Yi Nian +7
Large language models (LLMs) exhibit logically inconsistent hallucinations that appear coherent yet violate reasoning principles, with recent research suggesting an inverse relatio…
Temporally-Constrained Video Reasoning Segmentation and Automated Benchmark Construction
Yiqing Shen, Chenjia Li, Chenxiao Fan +1
Conventional approaches to video segmentation are confined to predefined object categories and cannot identify out-of-vocabulary objects, let alone objects that are not identified…
Reasoning Segmentation for Images and Videos: A Survey
Yiqing Shen, Chenjia Li, Fei Xiong +4
Reasoning Segmentation (RS) aims to delineate objects based on implicit text queries, the interpretation of which requires reasoning and knowledge integration. Unlike the tradition…
AutoP2C: An LLM-Based Agent Framework for Code Repository Generation from Multimodal Content in Academic Papers
Zijie Lin, Yiqing Shen, Qilin Cai +3
Machine Learning (ML) research is spread through academic papers featuring rich multimodal content, including text, diagrams, and tabular results. However, translating these multim…
RBench-V: A Primary Assessment for Visual Reasoning Models with Multi-modal Outputs
Meng-Hao Guo, Xuanyu Chu, Qianrui Yang +12
The rapid advancement of native multi-modal models and omni-models, exemplified by GPT-4o, Gemini, and o3, with their capability to process and generate content across modalities s…
RVTBench: A Benchmark for Visual Reasoning Tasks
Yiqing Shen, Chenjia Li, Chenxiao Fan +1
Visual reasoning, the capability to interpret visual input in response to implicit text query through multi-step reasoning, remains a challenge for deep learning models due to the…
Position: Foundation Models Need Digital Twin Representations
Yiqing Shen, Hao Ding, Lalithkumar Seenivasan +2
Current foundation models (FMs) rely on token representations that directly fragment continuous real-world multimodal data into discrete tokens. They limit FMs to learning real-wor…
Online Reasoning Video Segmentation with Just-in-Time Digital Twins
Yiqing Shen, Bohan Liu, Chenjia Li +2
Reasoning segmentation (RS) aims to identify and segment objects of interest based on implicit text queries. As such, RS is a catalyst for embodied AI agents, enabling them to inte…
Operating Room Workflow Analysis via Reasoning Segmentation over Digital Twins
Yiqing Shen, Chenjia Li, Bohan Liu +3
Analyzing operating room (OR) workflows to derive quantitative insights into OR efficiency is important for hospitals to maximize patient care and financial sustainability. Prior w…
An Intrinsically Explainable Approach to Detecting Vertebral Compression Fractures in CT Scans via Neurosymbolic Modeling
Blanca Inigo, Yiqing Shen, Benjamin D. Killeen +4
Vertebral compression fractures (VCFs) are a common and potentially serious consequence of osteoporosis. Yet, they often remain undiagnosed. Opportunistic screening, which involves…
Memorizing SAM: 3D Medical Segment Anything Model with Memorizing Transformer
Xinyuan Shao, Yiqing Shen, Mathias Unberath
Segment Anything Models (SAMs) have gained increasing attention in medical image analysis due to their zero-shot generalization capability in segmenting objects of unseen classes a…
DiffuseReg: Denoising Diffusion Model for Obtaining Deformation Fields in Unsupervised Deformable Image Registration
Yongtai Zhuo, Yiqing Shen
Deformable image registration aims to precisely align medical images from different modalities or times. Traditional deep learning methods, while effective, often lack interpretabi…
Performance and Non-adversarial Robustness of the Segment Anything Model 2 in Surgical Video Segmentation
Yiqing Shen, Hao Ding, Xinyuan Shao +1
Fully supervised deep learning (DL) models for surgical video segmentation have been shown to struggle with non-adversarial, real-world corruptions of image quality including smoke…