5 citations · 7 across the 15 of their papers we have counts for
15 papers
A Survey of Large Language Models for Perception and Measurement of Human Psychology
Yudong Li, Xiaoyi Chen, Jiawei Cai +4
Against the backdrop of the rapid advancement of Large Language Models (LLMs), their application in the field of psychology has garnered significant academic attention. A central i…
X-PCR: A Benchmark for Cross-modality Progressive Clinical Reasoning in Ophthalmic Diagnosis
Gui Wang, Zehao Zhong, YongSong Zhou +6
Despite significant progress in Multi-modal Large Language Models (MLLMs), their clinical reasoning capacity for multi-modal diagnosis remains largely unexamined. Current benchmark…
SurgCoT: Advancing Spatiotemporal Reasoning in Surgical Videos through a Chain-of-Thought Benchmark
Gui Wang, YongSong Zhou, Kaijun Deng +4
Fine-grained spatiotemporal reasoning on surgical videos is critical, yet the capabilities of Multi-modal Large Language Models (MLLMs) in this domain remain largely unexplored. To…
DIRCR: Dual-Inference Rule-Contrastive Reasoning for Solving RAVENs
Jiachen Zhang, Chengtai Li, Jianfeng Ren +3
Abstract visual reasoning remains challenging as existing methods often prioritize either global context or local row-wise relations, failing to integrate both, and lack intermedia…
KoCo: Conditioning Language Model Pre-training on Knowledge Coordinates
Yudong Li, Jiawei Cai, Linlin Shen
Standard Large Language Model (LLM) pre-training typically treats corpora as flattened token sequences, often overlooking the real-world context that humans naturally rely on to co…
Text-Conditioned Multi-Expert Regression Framework for Fully Automated Multi-Abutment Design
Mianjie Zheng, Xinquan Yang, Xuefen Liu +4
Dental implant abutments serve as the geometric and biomechanical interface between the implant fixture and the prosthetic crown, yet their design relies heavily on manual effort a…
FineXtrol: Controllable Motion Generation via Fine-Grained Text
Keming Shen, Bizhu Wu, Junliang Chen +2
Recent works have sought to enhance the controllability and precision of text-driven motion generation. Some approaches leverage large language models (LLMs) to produce more detail…
EyePCR: A Comprehensive Benchmark for Fine-Grained Perception, Knowledge Comprehension and Clinical Reasoning in Ophthalmic Surgery
Gui Wang, Yang Wennuo, Xusen Ma +7
MLLMs (Multimodal Large Language Models) have showcased remarkable capabilities, but their performance in high-stakes, domain-specific scenarios like surgical settings, remains lar…
RedNote-Vibe: A Dataset for Capturing Temporal Dynamics of AI-Generated Text in Lifestyle Social Media
Yudong Li, Yufei Sun, Peiru Yang +7
We introduce RedNote-Vibe, a dataset spanning five years (pre-LLM to July 2025) sourced from lifestyle platform RedNote (Xiaohongshu), capturing the temporal dynamics of content cr…
DisFaceRep: Representation Disentanglement for Co-occurring Facial Components in Weakly Supervised Face Parsing
Xiaoqin Wang, Xianxu Hou, Meidan Ding +4
Face parsing aims to segment facial images into key components such as eyes, lips, and eyebrows. While existing methods rely on dense pixel-level annotations, such annotations are…
Medical Reasoning in the Era of LLMs: A Systematic Review of Enhancement Techniques and Applications
Zizhan Ma, Wenxuan Wang, Meidan Ding +7
The proliferation of Large Language Models (LLMs) in medicine has enabled impressive capabilities, yet a critical gap remains in their ability to perform systematic, transparent, a…
A Survey of Multimodal Ophthalmic Diagnostics: From Task-Specific Approaches to Foundational Models
Xiaoling Luo, Ruli Zheng, Qiaojian Zheng +6
Visual impairment represents a major global health challenge, with multimodal imaging providing complementary information that is essential for accurate ophthalmic diagnosis. This…
FineMotion: A Dataset and Benchmark with both Spatial and Temporal Annotation for Fine-grained Motion Generation and Editing
Bizhu Wu, Jinheng Xie, Meidan Ding +5
Generating realistic human motions from textual descriptions has undergone significant advancements. However, existing methods often overlook specific body part movements and their…
MG-MotionLLM: A Unified Framework for Motion Comprehension and Generation across Multiple Granularities
Bizhu Wu, Jinheng Xie, Keming Shen +5
Recent motion-aware large language models have demonstrated promising potential in unifying motion comprehension and generation. However, existing approaches primarily focus on coa…
Reversed Active Learning based Atrous DenseNet for Pathological Image Classification
Yuexiang Li, Xinpeng Xie, Linlin Shen +1
Witnessed the development of deep learning in recent years, increasing number of researches try to adopt deep learning model for medical image analysis. However, the usage of deep…