Summary of Revisiting Zeroth-order Optimization For Memory-efficient Llm Fine-tuning: a Benchmark, by Yihua Zhang et al.
Revisiting Zeroth-Order Optimization for Memory-Efficient LLM Fine-Tuning: A Benchmarkby Yihua Zhang, Pingzhi Li, Junyuan Hong,…
Summary of Loretta: Low-rank Economic Tensor-train Adaptation For Ultra-low-parameter Fine-tuning Of Large Language Models, by Yifan Yang et al.
LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Modelsby Yifan Yang, Jiajun…
Summary of A Curious Case Of Searching For the Correlation Between Training Data and Adversarial Robustness Of Transformer Textual Models, by Cuong Dang et al.
A Curious Case of Searching for the Correlation between Training Data and Adversarial Robustness of…
Summary of Zerog: Investigating Cross-dataset Zero-shot Transferability in Graphs, by Yuhan Li et al.
ZeroG: Investigating Cross-dataset Zero-shot Transferability in Graphsby Yuhan Li, Peisong Wang, Zhixun Li, Jeffrey Xu…
Summary of Aligning Large Language Models by On-policy Self-judgment, By Sangkyu Lee et al.
Aligning Large Language Models by On-Policy Self-Judgmentby Sangkyu Lee, Sungdong Kim, Ashkan Yousefpour, Minjoon Seo,…
Summary of Model Editing by Standard Fine-tuning, By Govind Gangadhar et al.
Model Editing by Standard Fine-Tuningby Govind Gangadhar, Karl StratosFirst submitted to arxiv on: 16 Feb…
Summary of Speculative Streaming: Fast Llm Inference Without Auxiliary Models, by Nikhil Bhendawade et al.
Speculative Streaming: Fast LLM Inference without Auxiliary Modelsby Nikhil Bhendawade, Irina Belousova, Qichen Fu, Henry…
Summary of Tunetables: Context Optimization For Scalable Prior-data Fitted Networks, by Benjamin Feuer et al.
TuneTables: Context Optimization for Scalable Prior-Data Fitted Networksby Benjamin Feuer, Robin Tibor Schirrmeister, Valeriia Cherepanova,…
Summary of Instruction Diversity Drives Generalization to Unseen Tasks, by Dylan Zhang et al.
Instruction Diversity Drives Generalization To Unseen Tasksby Dylan Zhang, Justin Wang, Francois ChartonFirst submitted to…
Summary of Daedra: a Language Model For Predicting Outcomes in Passive Pharmacovigilance Reporting, by Chris Von Csefalvay
DAEDRA: A language model for predicting outcomes in passive pharmacovigilance reportingby Chris von CsefalvayFirst submitted…