Summary of Library Learning Doesn’t: the Curious Case Of the Single-use “library”, by Ian Berlot-attwell et al.
Library Learning Doesn’t: The Curious Case of the Single-Use “Library”by Ian Berlot-Attwell, Frank Rudzicz, Xujie…
Summary of Notes on the Mathematical Structure Of Gpt Llm Architectures, by Spencer Becker-kahn
Notes on the Mathematical Structure of GPT LLM Architecturesby Spencer Becker-KahnFirst submitted to arxiv on:…
Summary of Inference Time Llm Alignment in Single and Multidomain Preference Spectrum, by Sadat Shahriar et al.
Inference time LLM alignment in single and multidomain preference spectrumby Sadat Shahriar, Zheng Qi, Nikolaos…
Summary of Research on Key Technologies For Cross-cloud Federated Training Of Large Language Models, by Haowei Yang et al.
Research on Key Technologies for Cross-Cloud Federated Training of Large Language Modelsby Haowei Yang, Mingxiu…
Summary of Dynamic Vocabulary Pruning in Early-exit Llms, by Jort Vincenti et al.
Dynamic Vocabulary Pruning in Early-Exit LLMsby Jort Vincenti, Karim Abdel Sadek, Joan Velja, Matteo Nulli,…
Summary of Unbounded: a Generative Infinite Game Of Character Life Simulation, by Jialu Li et al.
Unbounded: A Generative Infinite Game of Character Life Simulationby Jialu Li, Yuanzhen Li, Neal Wadhwa,…
Summary of Ferret-ui 2: Mastering Universal User Interface Understanding Across Platforms, by Zhangheng Li et al.
Ferret-UI 2: Mastering Universal User Interface Understanding Across Platformsby Zhangheng Li, Keen You, Haotian Zhang,…
Summary of Baton: Enhancing Batch-wise Inference Efficiency For Large Language Models Via Dynamic Re-batching, by Peizhuang Cong et al.
BATON: Enhancing Batch-wise Inference Efficiency for Large Language Models via Dynamic Re-batchingby Peizhuang Cong, Qizhi…
Summary of A Little Help Goes a Long Way: Efficient Llm Training by Leveraging Small Lms, By Ankit Singh Rawat et al.
A Little Help Goes a Long Way: Efficient LLM Training by Leveraging Small LMsby Ankit…
Summary of Pod-attention: Unlocking Full Prefill-decode Overlap For Faster Llm Inference, by Aditya K Kamath et al.
POD-Attention: Unlocking Full Prefill-Decode Overlap for Faster LLM Inferenceby Aditya K Kamath, Ramya Prabhu, Jayashree…