Extending LLM Context via Associative Recurrent Memory
Extending the context length of large language models (LLMs) is critical for many real-world applications, yet standard transformers remain constrained by quadratic compute and linear memory scaling. In this work, we investigate the Associa
https://arxiv.org/abs/2607.11614v1 ↗Thesis fit
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Within your typical scope; diligence still required.
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None
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llm, ai
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Gleb Kuzmin
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I
Ivan Rodkin
1.0
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Aydar Bulatov
1.0
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Y
Yuri Kuratov
1.0
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Lyudmila Rvanova
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Mikhail Katkov
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Ilia Sochenkov
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Misha Tsodyks
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Timothy Baldwin
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Mikhail Burtsev
1.0
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A
Artem Shelmanov
1.0
low confidence
Activity & evidence
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