Summary of Peeb: Part-based Image Classifiers with An Explainable and Editable Language Bottleneck, by Thang M. Pham et al.
PEEB: Part-based Image Classifiers with an Explainable and Editable Language Bottleneckby Thang M. Pham, Peijie…
PEEB: Part-based Image Classifiers with an Explainable and Editable Language Bottleneckby Thang M. Pham, Peijie…
Self-Supervised Multiple Instance Learning for Acute Myeloid Leukemia Classificationby Salome Kazeminia, Max Joosten, Dragan Bosnacki,…
Medical Speech Symptoms Classification via Disentangled Representationby Jianzong Wang, Pengcheng Li, Xulong Zhang, Ning Cheng,…
Best of Both Worlds: A Pliable and Generalizable Neuro-Symbolic Approach for Relation Classificationby Robert Vacareanu,…
Detecting AI-Generated Sentences in Human-AI Collaborative Hybrid Texts: Challenges, Strategies, and Insightsby Zijie Zeng, Shiqi…
A General and Flexible Multi-concept Parsing Framework for Multilingual Semantic Matchingby Dong YaoFirst submitted to…
A Tutorial on the Pretrain-Finetune Paradigm for Natural Language Processingby Yu Wang, Wen QuFirst submitted…
HARGPT: Are LLMs Zero-Shot Human Activity Recognizers?by Sijie Ji, Xinzhe Zheng, Chenshu WuFirst submitted to…
Enhancing Long-Term Person Re-Identification Using Global, Local Body Part, and Head Streamsby Duy Tran Thanh,…
Leveraging Weakly Annotated Data for Hate Speech Detection in Code-Mixed Hinglish: A Feasibility-Driven Transfer Learning…