Summary of Context-aware Adapter Tuning For Few-shot Relation Learning in Knowledge Graphs, by Ran Liu et al.
Context-Aware Adapter Tuning for Few-Shot Relation Learning in Knowledge Graphsby Ran Liu, Zhongzhou Liu, Xiaoli…
Summary of Parameter-efficient Fine-tuning Of State Space Models, by Kevin Galim et al.
Parameter-Efficient Fine-Tuning of State Space Modelsby Kevin Galim, Wonjun Kang, Yuchen Zeng, Hyung Il Koo,…
Summary of Qeft: Quantization For Efficient Fine-tuning Of Llms, by Changhun Lee et al.
QEFT: Quantization for Efficient Fine-Tuning of LLMsby Changhun Lee, Jun-gyu Jin, Younghyun Cho, Eunhyeok ParkFirst…
Summary of Scalable Representation Learning For Multimodal Tabular Transactions, by Natraj Raman et al.
Scalable Representation Learning for Multimodal Tabular Transactionsby Natraj Raman, Sumitra Ganesh, Manuela VelosoFirst submitted to…
Summary of Sketch to Adapt: Fine-tunable Sketches For Efficient Llm Adaptation, by Tianyi Zhang et al.
Sketch to Adapt: Fine-Tunable Sketches for Efficient LLM Adaptationby Tianyi Zhang, Junda Su, Aditya Desai,…
Summary of Tpp-llm: Modeling Temporal Point Processes by Efficiently Fine-tuning Large Language Models, By Zefang Liu et al.
TPP-LLM: Modeling Temporal Point Processes by Efficiently Fine-Tuning Large Language Modelsby Zefang Liu, Yinzhu QuanFirst…
Summary of Open-rag: Enhanced Retrieval-augmented Reasoning with Open-source Large Language Models, by Shayekh Bin Islam et al.
Open-RAG: Enhanced Retrieval-Augmented Reasoning with Open-Source Large Language Modelsby Shayekh Bin Islam, Md Asib Rahman,…
Summary of Vision-language Models Are Strong Noisy Label Detectors, by Tong Wei and Hao-tian Li and Chun-shu Li and Jiang-xin Shi and Yu-feng Li and Min-ling Zhang
Vision-Language Models are Strong Noisy Label Detectorsby Tong Wei, Hao-Tian Li, Chun-Shu Li, Jiang-Xin Shi,…
Summary of Multi-view and Multi-scale Alignment For Contrastive Language-image Pre-training in Mammography, by Yuexi Du et al.
Multi-View and Multi-Scale Alignment for Contrastive Language-Image Pre-training in Mammographyby Yuexi Du, John Onofrey, Nicha…
Summary of Pace: Marrying Generalization in Parameter-efficient Fine-tuning with Consistency Regularization, by Yao Ni et al.
PACE: Marrying generalization in PArameter-efficient fine-tuning with Consistency rEgularizationby Yao Ni, Shan Zhang, Piotr KoniuszFirst…