Summary of Crisperwhisper: Accurate Timestamps on Verbatim Speech Transcriptions, by Laurin Wagner et al.
CrisperWhisper: Accurate Timestamps on Verbatim Speech Transcriptionsby Laurin Wagner, Bernhard Thallinger, Mario ZusagFirst submitted to…
Summary of Physics Of Language Models: Part 2.2, How to Learn From Mistakes on Grade-school Math Problems, by Tian Ye et al.
Physics of Language Models: Part 2.2, How to Learn From Mistakes on Grade-School Math Problemsby…
Summary of Lemon: Learning to Learn Multi-operator Networks, by Jingmin Sun et al.
LeMON: Learning to Learn Multi-Operator Networksby Jingmin Sun, Zecheng Zhang, Hayden SchaefferFirst submitted to arxiv…
Summary of Artificial Neural Network and Deep Learning: Fundamentals and Theory, by M. M. Hammad
Artificial Neural Network and Deep Learning: Fundamentals and Theoryby M. M. HammadFirst submitted to arxiv…
Summary of Exploring Selective Layer Fine-tuning in Federated Learning, by Yuchang Sun and Yuexiang Xie and Bolin Ding and Yaliang Li and Jun Zhang
Exploring Selective Layer Fine-Tuning in Federated Learningby Yuchang Sun, Yuexiang Xie, Bolin Ding, Yaliang Li,…
Summary of Gift-sw: Gaussian Noise Injected Fine-tuning Of Salient Weights For Llms, by Maxim Zhelnin et al.
GIFT-SW: Gaussian noise Injected Fine-Tuning of Salient Weights for LLMsby Maxim Zhelnin, Viktor Moskvoretskii, Egor…
Summary of Constrained Diffusion Models Via Dual Training, by Shervin Khalafi and Dongsheng Ding and Alejandro Ribeiro
Constrained Diffusion Models via Dual Trainingby Shervin Khalafi, Dongsheng Ding, Alejandro RibeiroFirst submitted to arxiv…
Summary of Unsupervised-to-online Reinforcement Learning, by Junsu Kim et al.
Unsupervised-to-Online Reinforcement Learningby Junsu Kim, Seohong Park, Sergey LevineFirst submitted to arxiv on: 27 Aug…
Summary of Curlora: Stable Llm Continual Fine-tuning and Catastrophic Forgetting Mitigation, by Muhammad Fawi
CURLoRA: Stable LLM Continual Fine-Tuning and Catastrophic Forgetting Mitigationby Muhammad FawiFirst submitted to arxiv on:…
Summary of Efficient Fine-tuning Of 37-level Graphcast with the Canadian Global Deterministic Analysis, by Christopher Subich
Efficient fine-tuning of 37-level GraphCast with the Canadian global deterministic analysisby Christopher SubichFirst submitted to…