Summary of Zeroth-order Fine-tuning Of Llms with Extreme Sparsity, by Wentao Guo et al.
Zeroth-Order Fine-Tuning of LLMs with Extreme Sparsityby Wentao Guo, Jikai Long, Yimeng Zeng, Zirui Liu,…
Summary of Disentangling Logic: the Role Of Context in Large Language Model Reasoning Capabilities, by Wenyue Hua et al.
Disentangling Logic: The Role of Context in Large Language Model Reasoning Capabilitiesby Wenyue Hua, Kaijie…
Summary of Randomized Geometric Algebra Methods For Convex Neural Networks, by Yifei Wang et al.
Randomized Geometric Algebra Methods for Convex Neural Networksby Yifei Wang, Sungyoon Kim, Paul Chu, Indu…
Summary of Exploring Robustness in Doctor-patient Conversation Summarization: An Analysis Of Out-of-domain Soap Notes, by Yu-wen Chen et al.
Exploring Robustness in Doctor-Patient Conversation Summarization: An Analysis of Out-of-Domain SOAP Notesby Yu-Wen Chen, Julia…
Summary of Towards Learning Foundation Models For Heuristic Functions to Solve Pathfinding Problems, by Vedant Khandelwal et al.
Towards Learning Foundation Models for Heuristic Functions to Solve Pathfinding Problemsby Vedant Khandelwal, Amit Sheth,…
Summary of Frequency Enhanced Pre-training For Cross-city Few-shot Traffic Forecasting, by Zhanyu Liu et al.
Frequency Enhanced Pre-training for Cross-city Few-shot Traffic Forecastingby Zhanyu Liu, Jianrong Ding, Guanjie ZhengFirst submitted…
Summary of Applying Fine-tuned Llms For Reducing Data Needs in Load Profile Analysis, by Yi Hu et al.
Applying Fine-Tuned LLMs for Reducing Data Needs in Load Profile Analysisby Yi Hu, Hyeonjin Kim,…
Summary of Using Self-supervised Learning Can Improve Model Fairness, by Sofia Yfantidou et al.
Using Self-supervised Learning Can Improve Model Fairnessby Sofia Yfantidou, Dimitris Spathis, Marios Constantinides, Athena Vakali,…
Summary of A Study Of Optimizations For Fine-tuning Large Language Models, by Arjun Singh et al.
A Study of Optimizations for Fine-tuning Large Language Modelsby Arjun Singh, Nikhil Pandey, Anup Shirgaonkar,…
Summary of Pefad: a Parameter-efficient Federated Framework For Time Series Anomaly Detection, by Ronghui Xu et al.
PeFAD: A Parameter-Efficient Federated Framework for Time Series Anomaly Detectionby Ronghui Xu, Hao Miao, Senzhang…