softmax transformers
PulseAugur coverage of softmax transformers — every cluster mentioning softmax transformers across labs, papers, and developer communities, ranked by signal.
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New theorem explains how transformers forget prompts
Researchers have developed a conditional no-hair theorem to explain how autoregressive transformers forget their prompts. The theorem states that a transformer's prompt influence decays as a power law, with trained mode…
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Low-Precision Transformers Can Simulate Turing Machines, Study Finds
Researchers have analyzed the expressive power of standard transformer decoders, focusing on practical aspects like low precision and softmax attention. Their work bridges the gap between theoretical models and real-wor…
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New Theory Explores Linear Transformers for In-Context Learning
Researchers have investigated the theoretical underpinnings of linear transformers for in-context learning, addressing the computational limitations of traditional softmax transformers. The study proposes that linear tr…