Summary of Conditioning Llms with Emotion in Neural Machine Translation, by Charles Brazier et al.
Conditioning LLMs with Emotion in Neural Machine Translationby Charles Brazier, Jean-Luc RouasFirst submitted to arxiv…
Summary of Leveraging Parameter Efficient Training Methods For Low Resource Text Classification: a Case Study in Marathi, by Pranita Deshmukh et al.
Leveraging Parameter Efficient Training Methods for Low Resource Text Classification: A Case Study in Marathiby…
Summary of Relief: Reinforcement Learning Empowered Graph Feature Prompt Tuning, by Jiapeng Zhu et al.
RELIEF: Reinforcement Learning Empowered Graph Feature Prompt Tuningby Jiapeng Zhu, Zichen Ding, Jianxiang Yu, Jiaqi…
Summary of Sara: Singular-value Based Adaptive Low-rank Adaption, by Jihao Gu and Shuai Chen and Zelin Wang and Yibo Zhang and Ping Gong
SARA: Singular-Value Based Adaptive Low-Rank Adaptionby Jihao Gu, Shuai Chen, Zelin Wang, Yibo Zhang, Ping…
Summary of A Framework For Fine-tuning Llms Using Heterogeneous Feedback, by Ryan Aponte (1) et al.
A Framework for Fine-Tuning LLMs using Heterogeneous Feedbackby Ryan Aponte, Ryan A. Rossi, Shunan Guo,…
Summary of Harmonic: Harnessing Llms For Tabular Data Synthesis and Privacy Protection, by Yuxin Wang et al.
HARMONIC: Harnessing LLMs for Tabular Data Synthesis and Privacy Protectionby Yuxin Wang, Duanyu Feng, Yongfu…
Summary of Rag Foundry: a Framework For Enhancing Llms For Retrieval Augmented Generation, by Daniel Fleischer et al.
RAG Foundry: A Framework for Enhancing LLMs for Retrieval Augmented Generationby Daniel Fleischer, Moshe Berchansky,…
Summary of Metawears: a Shortcut in Wearable Systems Lifecycle with Only a Few Shots, by Alireza Amirshahi et al.
MetaWearS: A Shortcut in Wearable Systems Lifecycle with Only a Few Shotsby Alireza Amirshahi, Maedeh…
Summary of Recent Advances in Multi-choice Machine Reading Comprehension: a Survey on Methods and Datasets, by Shima Foolad et al.
Recent Advances in Multi-Choice Machine Reading Comprehension: A Survey on Methods and Datasetsby Shima Foolad,…
Summary of Image Clustering Algorithm Based on Self-supervised Pretrained Models and Latent Feature Distribution Optimization, by Qiuyu Zhu and Liheng Hu and Sijin Wang
Image Clustering Algorithm Based on Self-Supervised Pretrained Models and Latent Feature Distribution Optimizationby Qiuyu Zhu,…