Dylan Hillier
DylanASHillier
AI & ML interests
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Organizations
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State Space Models
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Repeat After Me: Transformers are Better than State Space Models at Copying
Paper • 2402.01032 • Published • 24 -
Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks
Paper • 2402.04248 • Published • 32 -
Linear Transformers with Learnable Kernel Functions are Better In-Context Models
Paper • 2402.10644 • Published • 81 -
In Search of Needles in a 10M Haystack: Recurrent Memory Finds What LLMs Miss
Paper • 2402.10790 • Published • 42
Benchmarks etc.
State Space Models
-
Repeat After Me: Transformers are Better than State Space Models at Copying
Paper • 2402.01032 • Published • 24 -
Can Mamba Learn How to Learn? A Comparative Study on In-Context Learning Tasks
Paper • 2402.04248 • Published • 32 -
Linear Transformers with Learnable Kernel Functions are Better In-Context Models
Paper • 2402.10644 • Published • 81 -
In Search of Needles in a 10M Haystack: Recurrent Memory Finds What LLMs Miss
Paper • 2402.10790 • Published • 42
models
0
None public yet