Summary of Exact Conversion Of In-context Learning to Model Weights in Linearized-attention Transformers, by Brian K Chen et al.
Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformersby Brian K Chen, Tianyang…
Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformersby Brian K Chen, Tianyang…
Oscillations enhance time-series prediction in reservoir computing with feedbackby Yuji Kawai, Takashi Morita, Jihoon Park,…
Combinatorial Optimization with Automated Graph Neural Networksby Yang Liu, Peng Zhang, Yang Gao, Chuan Zhou,…
Replicability in High Dimensional Statisticsby Max Hopkins, Russell Impagliazzo, Daniel Kane, Sihan Liu, Christopher YeFirst…
Evidentially Calibrated Source-Free Time-Series Domain Adaptation with Temporal Imputationby Mohamed Ragab, Peiliang Gong, Emadeldeen Eldele,…
EchoMamba4Rec: Harmonizing Bidirectional State Space Models with Spectral Filtering for Advanced Sequential Recommendationby Yuda Wang,…
E-ICL: Enhancing Fine-Grained Emotion Recognition through the Lens of Prototype Theoryby Zhaochun Ren, Zhou Yang,…
Exploring Effects of Hyperdimensional Vectors for Tsetlin Machinesby Vojtech Halenka, Ahmed K. Kadhim, Paul F.…
By Fair Means or Foul: Quantifying Collusion in a Market Simulation with Deep Reinforcement Learningby…
RoutePlacer: An End-to-End Routability-Aware Placer with Graph Neural Networkby Yunbo Hou, Haoran Ye, Yingxue Zhang,…