The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale | Paper Citation Record

Observation 101d82a9-82ad-4604-bac7-b880e6fab16e · outbound

This paper cites Zoology: Measuring and Improving Recall in Efficient Language Models.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Zoology: Measuring and Improving Recall in Efficient Language Models

Reference 1

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Observation 9e6f8484-7b71-4e09-bade-d177fe7eed16 · outbound

This paper cites Simple linear attention language models balance the recall-throughput tradeoff.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Simple linear attention language models balance the recall-throughput tradeoff

Reference 2

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Observation b011ed9d-dccd-48a5-9b72-5d206c33a998 · outbound

This paper cites Hybrid Architectures for Language Models: Systematic Analysis and Design Insights.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Hybrid Architectures for Language Models: Systematic Analysis and Design Insights

Reference 3

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Observation e701462d-a536-4504-a21a-3f08b24e8fc2 · outbound

This paper cites Barrington.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Barrington

Reference 4

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Observation 9ed1622f-785c-4af7-ac0e-ad3782ea68ee · outbound

This paper cites Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models

Reference 5

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Observation 7241869c-1acf-401b-a44d-95865c955a0c · outbound

This paper cites Priming: Hybrid State Space Models From Pre-trained Transformers.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Priming: Hybrid State Space Models From Pre-trained Transformers

Reference 6

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Observation 37c7cae4-51ab-46c0-b3cb-208b444a242c · outbound

This paper cites Cover and Joy A.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Cover and Joy A

Reference 7

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Observation 6e1a7489-bf97-46d3-bba2-2a8076a1e8cb · outbound

This paper cites Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Reference 8

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Observation 5015a66a-053a-4ab7-ba66-a263aac518b3 · outbound

This paper cites Fu, Stefano Ermon, Atri Rudra, and Christopher Ré.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Fu, Stefano Ermon, Atri Rudra, and Christopher Ré

Reference 9

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Observation ec02a991-72ac-4003-a3ea-5b2ce3f4dd71 · outbound

This paper cites Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Griffin: Mixing Gated Linear Recurrences with Local Attention for Efficient Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-03T02:03:22.713671Z

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Observation ab9a7c4a-926b-468e-99b3-5318109d01a3 · outbound

This paper cites Language Modeling Is Compression.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Language Modeling Is Compression

Reference 11

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Observation ac2f0a18-6a03-484b-8ddc-19bca428c2da · outbound

This paper cites Hymba: A Hybrid-head Architecture for Small Language Models.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Hymba: A Hybrid-head Architecture for Small Language Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T02:03:22.922600Z

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Observation 4c06925c-ec8e-4828-a44b-33acfcd0dc1f · outbound

This paper cites Springer, 1999.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Springer, 1999

Reference 13

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Observation be520e97-6d05-4bcf-8e83-abd7f191bf0a · outbound

This paper cites The Zamba2 Suite: Technical Report.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale The Zamba2 Suite: Technical Report

Reference 14

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Observation b2dbdd2c-6902-45d6-8731-d53428c90e53 · outbound

This paper cites Zamba: A Compact 7B SSM Hybrid Model.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Zamba: A Compact 7B SSM Hybrid Model

Reference 15

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Observation f25cacad-ba6f-4bc4-b6c8-d32b9739b4e8 · outbound

This paper cites Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Unlocking State-Tracking in Linear RNNs Through Negative Eigenvalues

Reference 16

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Observation 06fdc5d0-bdd4-4bbf-8f5d-8a41e4da8186 · outbound

This paper cites Mamba: Linear-Time Sequence Modeling with Selective State Spaces.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Mamba: Linear-Time Sequence Modeling with Selective State Spaces

Reference 17

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Observation 60af7253-46f4-4b26-be6b-f7183096b301 · outbound

This paper cites Efficiently Modeling Long Sequences with Structured State Spaces.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Efficiently Modeling Long Sequences with Structured State Spaces

Reference 18

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Observation bf9f614d-44e6-4d0f-bc4f-8124fc3dbca8 · outbound

This paper cites Training Compute-Optimal Large Language Models.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Training Compute-Optimal Large Language Models

Reference 19

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Observation 935ca9d2-e4b1-490e-90f9-35ba05be4d30 · outbound

This paper cites RULER: What's the Real Context Size of Your Long-Context Language Models?.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale RULER: What's the Real Context Size of Your Long-Context Language Models?

Reference 20

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Observation 9f380a10-7ecd-48ee-a2fd-0d8bdb9b021c · outbound

This paper cites The Platonic Representation Hypothesis.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale The Platonic Representation Hypothesis

Reference 21

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Observation f54505a8-87b1-45f7-94a5-5caca6574fd7 · outbound

This paper cites IBM granite 4.0: Hybrid Mamba-2/Transformer open models.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale IBM granite 4.0: Hybrid Mamba-2/Transformer open models

Reference 22

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Observation a3aa00d8-fc6d-4ebf-b856-35e685c3f74f · outbound

This paper cites Repeat After Me: Transformers are Better than State Space Models at Copying.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Repeat After Me: Transformers are Better than State Space Models at Copying

Reference 23

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Observation f62b9234-b5bb-4ee6-91bf-c11448e68c1f · outbound

This paper cites an unresolved cited work.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Unresolved cited work

Reference 24

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Observation 0a678735-9e50-4cda-ab0d-861ded2443c1 · outbound

This paper cites Scaling Laws for Neural Language Models.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Scaling Laws for Neural Language Models

Reference 25

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Observation 1e2e89c4-7080-4532-9385-149f6779310f · outbound

This paper cites Transformers are RNNs: Fast autoregressive transformers with linear attention.International Conference on Machine Learning (ICML), 2020.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Transformers are RNNs: Fast autoregressive transformers with linear attention.International Conference on Machine Learning (ICML), 2020

Reference 26

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Observation def46d64-c570-43ff-9648-1dea801a2e65 · outbound

This paper cites Kimi Linear: An Expressive, Efficient Attention Architecture.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Kimi Linear: An Expressive, Efficient Attention Architecture

Reference 27

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Observation e85ac00f-9f3f-452a-b931-fc31409b3d7e · outbound

This paper cites Kimi K3: Open frontier intelligence.arXiv preprint arXiv:2607.24653, 2026.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Kimi K3: Open frontier intelligence.arXiv preprint arXiv:2607.24653, 2026

Reference 28

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Observation d907e6be-629b-4231-93f6-88375686ef6b · outbound

This paper cites Back into Plato's Cave: Examining Cross-modal Representational Convergence at Scale.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Back into Plato's Cave: Examining Cross-modal Representational Convergence at Scale

Reference 29

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Observation 03c6fb99-b378-4981-985c-680bf131e333 · outbound

This paper cites On randomized one-round communication complexity.Computational Complexity, 8(1):21–49, 1999.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale On randomized one-round communication complexity.Computational Complexity, 8(1):21–49, 1999

Reference 30

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Observation 66ba49f6-b44c-4749-ab79-fde02cffe23f · outbound

This paper cites Efficient Memory Management for Large Language Model Serving with PagedAttention.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Efficient Memory Management for Large Language Model Serving with PagedAttention

Reference 31

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Observation 75503299-9936-4bd3-8ce8-120e9f6271f7 · outbound

This paper cites Understanding and enhancing mamba-transformer hybrids for memory recall and language modeling.arXiv preprint arXiv:2510.26912, 2025.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Understanding and enhancing mamba-transformer hybrids for memory recall and language modeling.arXiv preprint arXiv:2510.26912, 2025

Reference 32

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Observation aa69c75c-f5fa-4d08-8029-00631a1b0748 · outbound

This paper cites Universal intelligence: A definition of machine intelligence.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Universal intelligence: A definition of machine intelligence

Reference 33

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Observation 69ee450a-5065-4d44-84c4-0caf65816127 · outbound

This paper cites Chain of Thought Empowers Transformers to Solve Inherently Serial Problems.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Chain of Thought Empowers Transformers to Solve Inherently Serial Problems

Reference 34

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Observation 9da85f3f-7143-4f3e-907d-a2dd197a798f · outbound

This paper cites Jamba: A Hybrid Transformer-Mamba Language Model.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Jamba: A Hybrid Transformer-Mamba Language Model

Reference 35

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Observation 90a492bd-b7c7-4e08-8136-a6de418be8f3 · outbound

This paper cites Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang

Reference 36

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Observation 55414413-c82c-4c8e-876c-a8f54f110de5 · outbound

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The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Unresolved cited work

Reference 37

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Observation 17c42a8b-cb7c-4692-b821-d9c4dd3bcac4 · outbound

This paper cites The Parallelism Tradeoff: Limitations of Log-Precision Transformers.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale The Parallelism Tradeoff: Limitations of Log-Precision Transformers

Reference 38

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Observation d0b7cb57-d1c4-4501-b33b-bd022ad1bcfb · outbound

This paper cites The Illusion of State in State-Space Models.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale The Illusion of State in State-Space Models

Reference 39

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Observation f2d22061-e6b8-45c1-a500-fa6276003ac6 · outbound

This paper cites Some attention is all you need for retrieval.arXiv preprint arXiv:2510.19861, 2025.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Some attention is all you need for retrieval.arXiv preprint arXiv:2510.19861, 2025

Reference 40

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Observation 306bfd41-a9ac-42fe-8b08-b3b61a28e156 · outbound

This paper cites MiniMax-01: Scaling Foundation Models with Lightning Attention.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale MiniMax-01: Scaling Foundation Models with Lightning Attention

Reference 41

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Observation 380a1cb1-8ccf-4367-b2c1-7080e1d36380 · outbound

This paper cites Expansion Span: Combining Fading Memory and Retrieval in Hybrid State Space Models.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Expansion Span: Combining Fading Memory and Retrieval in Hybrid State Space Models

Reference 42

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Observation fbfbccab-fad0-463d-9f20-a935fc5fd667 · outbound

This paper cites Retrievit: In-context Retrieval Capabilities of Transformers, State Space Models, and Hybrid Architectures.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Retrievit: In-context Retrieval Capabilities of Transformers, State Space Models, and Hybrid Architectures

Reference 43

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Observation d9ea82d2-e8e4-47ed-b0d8-8539dd21b940 · outbound

This paper cites RWKV: Reinventing RNNs for the Transformer Era.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale RWKV: Reinventing RNNs for the Transformer Era

Reference 44

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Observation 6d254963-10ef-4f5d-b0bf-0fa0277d6446 · outbound

This paper cites Rethinking the role of efficient attention in hybrid architectures.arXiv preprint arXiv:2606.15378, 2026.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Rethinking the role of efficient attention in hybrid architectures.arXiv preprint arXiv:2606.15378, 2026

Reference 45

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Observation 42438cbc-fd3b-46e1-af76-872f42287e4f · outbound

This paper cites Qwen3-next: Towards ultimate training and inference efficiency.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Qwen3-next: Towards ultimate training and inference efficiency

Reference 46

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Observation 02de8e85-0002-4487-8e6b-6659f7f8669f · outbound

This paper cites Qwen3.8-Max preview.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Qwen3.8-Max preview

Reference 47

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Observation ff8c0729-ceeb-41b5-9518-1c5c0bbe404c · outbound

This paper cites Hopfield Networks is All You Need.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Hopfield Networks is All You Need

Reference 48

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Observation e60408e7-c8f7-41cf-88a2-6ffe1439e804 · outbound

This paper cites Reasoning Primitives in Hybrid and Non-Hybrid LLMs: Do Architectural Differences Yield Advantages in State-Tracking and Recall?.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Reasoning Primitives in Hybrid and Non-Hybrid LLMs: Do Architectural Differences Yield Advantages in State-Tracking and Recall?

Reference 49

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Observation 4140f7bf-c2d4-43dc-a5a2-db42a5e210d1 · outbound

This paper cites The expressive capacity of state space models: A formal language perspective.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale The expressive capacity of state space models: A formal language perspective

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-03T02:03:25.406151Z

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Observation c75930d9-0701-4102-ba3a-0175066d0b18 · outbound

This paper cites an unresolved cited work.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Unresolved cited work

Reference 51

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Observation 8851018d-0419-4d80-a59f-a7f846f7eb2b · outbound

This paper cites DeltaProduct: Improving state-tracking in linear RNNs via householder products.arXiv preprint arXiv:2502.10297, 2025.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale DeltaProduct: Improving state-tracking in linear RNNs via householder products.arXiv preprint arXiv:2502.10297, 2025

Reference 52

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Observation 7da99554-2e5e-48b3-82c6-3b266cac057d · outbound

This paper cites Retentive Network: A Successor to Transformer for Large Language Models.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Retentive Network: A Successor to Transformer for Large Language Models

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-03T02:03:25.419611Z

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Observation 189c1e13-2839-4b5a-bc80-026b5f9e2982 · outbound

This paper cites Convergence Without Understanding: When Language Models Agree on Representations but Disagree on Reasoning.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Convergence Without Understanding: When Language Models Agree on Representations but Disagree on Reasoning

Reference 54

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Observation 6c93400c-ce01-4a93-b93f-57c3aca4a23e · outbound

This paper cites Gomez, Lukasz Kaiser, and Illia Polosukhin.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Gomez, Lukasz Kaiser, and Illia Polosukhin

Reference 55

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Observation 1e8813a3-8e20-4445-85c8-c714aa8fcd48 · outbound

This paper cites An Empirical Study of Mamba-based Language Models.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale An Empirical Study of Mamba-based Language Models

Reference 56

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Observation ab9985f5-551e-4400-ad27-28d9255d6877 · outbound

This paper cites The Mamba in the Llama: Distilling and Accelerating Hybrid Models.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale The Mamba in the Llama: Distilling and Accelerating Hybrid Models

Reference 57

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Observation 8b9a51b3-bdaf-4644-83ec-dc2a6ca9bd5e · outbound

This paper cites Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Understanding and Mitigating Bottlenecks of State Space Models through the Lens of Recency and Over-smoothing

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-03T02:03:25.442040Z

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Observation f67a540b-f25e-443c-a978-e1a1d23e7770 · outbound

This paper cites Gated Linear Attention Transformers with Hardware-Efficient Training.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Gated Linear Attention Transformers with Hardware-Efficient Training

Reference 59

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Observation 9d0cee44-1c53-457a-84aa-25b52a35f6e6 · outbound

This paper cites Probabilistic computations: Toward a unified measure of complexity.

The Capability Convergence Hypothesis: Capability from Access Structure, Not Scale Probabilistic computations: Toward a unified measure of complexity

Reference 60

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