Summary of Learning Algorithms Made Simple, by Noorbakhsh Amiri Golilarz et al.
Learning Algorithms Made Simpleby Noorbakhsh Amiri Golilarz, Elias Hossain, Abdoljalil Addeh, Keyan Alexander RahimiFirst submitted…
Summary of Encoding Agent Trajectories As Representations with Sequence Transformers, by Athanasios Tsiligkaridis et al.
Encoding Agent Trajectories as Representations with Sequence Transformersby Athanasios Tsiligkaridis, Nicholas Kalinowski, Zhongheng Li, Elizabeth…
Summary of Deeposets: Non-autoregressive In-context Learning Of Supervised Learning Operators, by Shao-ting Chiu et al.
DeepOSets: Non-Autoregressive In-Context Learning of Supervised Learning Operatorsby Shao-Ting Chiu, Junyuan Hong, Ulisses Braga-NetoFirst submitted…
Summary of Nextlocllm: Next Location Prediction Using Llms, by Shuai Liu et al.
nextlocllm: next location prediction using LLMsby Shuai Liu, Ning Cao, Yile Chen, Yue Jiang, Gao…
Summary of Hierarchical Universal Value Function Approximators, by Rushiv Arora
Hierarchical Universal Value Function Approximatorsby Rushiv AroraFirst submitted to arxiv on: 11 Oct 2024CategoriesMain: Machine…
Summary of Adashadow: Responsive Test-time Model Adaptation in Non-stationary Mobile Environments, by Cheng Fang et al.
AdaShadow: Responsive Test-time Model Adaptation in Non-stationary Mobile Environmentsby Cheng Fang, Sicong Liu, Zimu Zhou,…
Summary of Pretraining Graph Transformers with Atom-in-a-molecule Quantum Properties For Improved Admet Modeling, by Alessio Fallani et al.
Pretraining Graph Transformers with Atom-in-a-Molecule Quantum Properties for Improved ADMET Modelingby Alessio Fallani, Ramil Nugmanov,…
Summary of Verifierq: Enhancing Llm Test Time Compute with Q-learning-based Verifiers, by Jianing Qi et al.
VerifierQ: Enhancing LLM Test Time Compute with Q-Learning-based Verifiersby Jianing Qi, Hao Tang, Zhigang ZhuFirst…
Summary of Packing Analysis: Packing Is More Appropriate For Large Models or Datasets in Supervised Fine-tuning, by Shuhe Wang et al.
Packing Analysis: Packing Is More Appropriate for Large Models or Datasets in Supervised Fine-tuningby Shuhe…
Summary of Enhancing Federated Domain Adaptation with Multi-domain Prototype-based Federated Fine-tuning, by Jingyuan Zhang et al.
Enhancing Federated Domain Adaptation with Multi-Domain Prototype-Based Federated Fine-Tuningby Jingyuan Zhang, Yiyang Duan, Shuaicheng Niu,…