Summary of Eyeclip: a Visual-language Foundation Model For Multi-modal Ophthalmic Image Analysis, by Danli Shi et al.
EyeCLIP: A visual-language foundation model for multi-modal ophthalmic image analysisby Danli Shi, Weiyi Zhang, Jiancheng…
EyeCLIP: A visual-language foundation model for multi-modal ophthalmic image analysisby Danli Shi, Weiyi Zhang, Jiancheng…
LIME: Less Is More for MLLM Evaluationby King Zhu, Qianbo Zang, Shian Jia, Siwei Wu,…
RIRAG: Regulatory Information Retrieval and Answer Generationby Tuba Gokhan, Kexin Wang, Iryna Gurevych, Ted BriscoeFirst…
Accelerating Large Language Model Pretraining via LFR Pedagogy: Learn, Focus, and Reviewby Neha Prakriya, Jui-Nan…
Seek and Solve Reasoning for Table Question Answeringby Ruya Jiang, Chun Wang, Weihong DengFirst submitted…
Towards Building a Robust Knowledge Intensive Question Answering Model with Large Language Modelsby Xingyun Hong,…
Question-Answering Dense Video Eventsby Hangyu Qin, Junbin Xiao, Angela YaoFirst submitted to arxiv on: 6…
COLUMBUS: Evaluating COgnitive Lateral Understanding through Multiple-choice reBUSesby Koen Kraaijveld, Yifan Jiang, Kaixin Ma, Filip…
R2GQA: Retriever-Reader-Generator Question Answering System to Support Students Understanding Legal Regulations in Higher Educationby Phuc-Tinh…
Debate on Graph: a Flexible and Reliable Reasoning Framework for Large Language Modelsby Jie Ma,…