Summary of Refine: Boosting Time Series Prediction Of Extreme Events by Reweighting and Fine-tuning, By Jimeng Shi et al.
ReFine: Boosting Time Series Prediction of Extreme Events by Reweighting and Fine-tuningby Jimeng Shi, Azam…
ReFine: Boosting Time Series Prediction of Extreme Events by Reweighting and Fine-tuningby Jimeng Shi, Azam…
Flat-LoRA: Low-Rank Adaption over a Flat Loss Landscapeby Tao Li, Zhengbao He, Yujun Li, Yasheng…
Obliviate: Neutralizing Task-agnostic Backdoors within the Parameter-efficient Fine-tuning Paradigmby Jaehan Kim, Minkyoo Song, Seung Ho…
Instruct-Tuning Pretrained Causal Language Models for Ancient Greek Papyrology and Epigraphyby Eric CullhedFirst submitted to…
One Model is All You Need: ByT5-Sanskrit, a Unified Model for Sanskrit NLP Tasksby Sebastian…
Logically Consistent Language Models via Neuro-Symbolic Integrationby Diego Calanzone, Stefano Teso, Antonio VergariFirst submitted to…
A constrained optimization approach to improve robustness of neural networksby Shudian Zhao, Jan KronqvistFirst submitted…
Deep Learning and Machine Learning, Advancing Big Data Analytics and Management: Tensorflow Pretrained Modelsby Keyu…
Prithvi WxC: Foundation Model for Weather and Climateby Johannes Schmude, Sujit Roy, Will Trojak, Johannes…
Evaluating Defences against Unsafe Feedback in RLHFby Domenic Rosati, Giles Edkins, Harsh Raj, David Atanasov,…