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Paper Citation Record · LEDGER

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models

As of 11 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2607.18280.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2607.18280 v1

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T09:43:32.802071Z

measured 64 of 64 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

64 of 64 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved64
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation cd448a93-2549-4b94-a911-6f3431e01745 · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence , volume=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Proceedings of the AAAI Conference on Artificial Intelligence , volume=

Reference 1

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source=arxiv_source observed=2026-08-02T09:43:25.016360Z digest=sha256:7c0be76854635eec30939da0a932e4c6ced714fb5466cfc259d365b70eebd460

Observation da9759b3-9371-4454-b2a6-7cb352aacd1e · outbound

This paper cites Advances in neural information processing systems , volume=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Advances in neural information processing systems , volume=

Reference 2

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source=arxiv_source observed=2026-08-02T09:43:25.078358Z digest=sha256:79a975f6c8005cece5ee81a91eada19676930e2e089e60dd0609ad2b1402a6e1

Observation e3043e66-464d-4222-ac79-7da1b6cbcf6f · outbound

This paper cites Advances in neural information processing systems , volume=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Advances in neural information processing systems , volume=

Reference 3

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source=arxiv_source observed=2026-08-02T09:43:25.178519Z digest=sha256:aec72e77d0c1df998595bdc3729ac658608144a46bd8b9ac65e88a58aeaadaa9

Observation 127e22f4-8866-440a-a2ba-c7c9946fc26b · outbound

This paper cites Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 4

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source=arxiv_source observed=2026-08-02T09:43:25.382134Z digest=sha256:4e8d765bcaf70fad452773b48e87eeb361918602a7e7f8a131305bb5df3830ff

Observation 0db01f1b-bc40-4eef-9262-ae77c1608c9c · outbound

This paper cites Unraveling the Mystery of Scaling Laws: Part I.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Unraveling the Mystery of Scaling Laws: Part I

Reference 5

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source=arxiv_source observed=2026-08-02T09:43:25.526240Z digest=sha256:e3cac7be89669d248a9d8216a54f4905054bcfc7b31e50a4dbe8429483b20e5c

Observation 8c043259-3480-4540-a9a2-e3667249cc64 · outbound

This paper cites WeLM: A Well-Read Pre-trained Language Model for Chinese.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models WeLM: A Well-Read Pre-trained Language Model for Chinese

Reference 6

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source=arxiv_source observed=2026-08-02T09:43:25.728604Z digest=sha256:13f2b8f8ef7d6d7f778f55d4b1819b4207ee9407bceebdb9a1f0ce9c44d78c98

Observation ebd22cef-75a9-4251-a4ac-9b714a1f856a · outbound

This paper cites arXiv preprint arXiv:2602.23699 , year=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models arXiv preprint arXiv:2602.23699 , year=

Reference 7

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source=arxiv_source observed=2026-08-02T09:43:25.912243Z digest=sha256:a80149bb722ebbca89a6a71dd3b4c24497b8ede5c58bbbde403fb68aad9b3fd3

Observation 042bc42c-ad3c-4ad9-8d76-d3f17bda3dd2 · outbound

This paper cites SkipOPU: An FPGA-based Overlay Processor for Large Language Models with Dynamically Allocated Computation.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models SkipOPU: An FPGA-based Overlay Processor for Large Language Models with Dynamically Allocated Computation

Reference 8

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source=arxiv_source observed=2026-08-02T09:43:26.024102Z digest=sha256:e92abdf13d1e49b82a02866cdae333b89fb95129f62b4e6d51517574a025e2cf

Observation 1596ca5e-3ba8-4a52-b04c-06427d871ad3 · outbound

This paper cites 2026 , eprint=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models 2026 , eprint=

Reference 9

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source=arxiv_source observed=2026-08-02T09:43:26.142716Z digest=sha256:335de3de742a5c539cf7cf7385d13be7921d38a7cc5f4826efdfd33d0079b0f8

Observation 0ccfb034-e89b-4b8f-9b66-66f0f7d969f7 · outbound

This paper cites arXiv preprint arXiv:2510.13831 , year=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models arXiv preprint arXiv:2510.13831 , year=

Reference 10

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source=arxiv_source observed=2026-08-02T09:43:26.224033Z digest=sha256:12aac5bbb49764735ec05a7088dd3d3f8dbf100932d62e7bbdfaabd664abeb2c

Observation 6e97dca5-79f0-48f7-998b-18e8a93ac22a · outbound

This paper cites arXiv preprint arXiv:2601.18091 , year=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models arXiv preprint arXiv:2601.18091 , year=

Reference 11

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source=arxiv_source observed=2026-08-02T09:43:26.294378Z digest=sha256:9fef8e8f6c5e584d67963d7afb39311d8ad2e6b456ae63a1e329789ce9a3e064

Observation 3c76048e-9682-4062-bdb7-6d36a9a4eaa2 · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 12

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source=arxiv_source observed=2026-08-02T09:43:26.471732Z digest=sha256:ded547d4c596bafb90ca078cacdd47ca2b7955375ab656da1cd0f79e8b34da5b

Observation b0b8dfd5-a146-49ce-81cc-bb8576b8032d · outbound

This paper cites ICLR , year=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models ICLR , year=

Reference 13

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source=arxiv_source observed=2026-08-02T09:43:26.639997Z digest=sha256:2cb8061056c343a4d194af595729cbedef39f843d41183f05c17186cc2be9ad9

Observation e6013595-575e-45da-a205-c58c26c333b0 · outbound

This paper cites Proceedings of the British Machine Vision Conference , pages=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Proceedings of the British Machine Vision Conference , pages=

Reference 14

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source=arxiv_source observed=2026-08-02T09:43:26.829606Z digest=sha256:5cbb1ea8619f297cd56c2edb6801d6546c3afefe8acf097bfdfe66e2719fa3c5

Observation bc7b09fe-c9fe-4243-8a2a-60d1139f8764 · outbound

This paper cites International Conference on Learning Representations , year=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models International Conference on Learning Representations , year=

Reference 15

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source=arxiv_source observed=2026-08-02T09:43:26.985614Z digest=sha256:0bfd4d162ec32b1fc9ed4b244d662a6fc0fa55fb2623eb6d8343ce30cb4eec88

Observation 4a7ed0f4-a97f-4d49-930b-d9d41dab1507 · outbound

This paper cites International Conference on Machine Learning , year=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models International Conference on Machine Learning , year=

Reference 16

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source=arxiv_source observed=2026-08-02T09:43:27.101259Z digest=sha256:45cfb159175683a8c1aabb778e319d1f0133da4b2175859f575e00744b96afc3

Observation 8549e813-832d-41ee-929e-6fefe83f8292 · outbound

This paper cites an unresolved cited work.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Unresolved cited work

Reference 17

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source=arxiv_source observed=2026-08-02T09:43:27.266839Z digest=sha256:ffc10caaf31cf6175e3d97d878e9b20c070b2d440fa293fdf2a997065abcb226

Observation d2b2a07b-c6b1-4ee3-9105-a9f0bbddb642 · outbound

This paper cites , author=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models , author=

Reference 18

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source=arxiv_source observed=2026-08-02T09:43:27.409829Z digest=sha256:309c6821de77f7e39b7f0a842e26ccd80187581c50cc7897875019dad669bb22

Observation 29999203-9746-4201-b9cc-ca1003a463ec · outbound

This paper cites Proceedings of the 40th International Conference on Machine Learning , articleno =.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Proceedings of the 40th International Conference on Machine Learning , articleno =

Reference 19

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source=arxiv_source observed=2026-08-02T09:43:27.529080Z digest=sha256:88875336a0c7ac1914c8085ecd7d03798a147ba7d8358e6133b0d82c70e4f0b8

Observation b668c889-e734-48b2-b3e8-1f4a7e58ef4c · outbound

This paper cites Forty-second International Conference on Machine Learning , year=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Forty-second International Conference on Machine Learning , year=

Reference 20

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source=arxiv_source observed=2026-08-02T09:43:27.713854Z digest=sha256:1089ddfcb465c1773875f6234e8f7c280ed486d1fe4d49b0215f7101ca429a06

Observation 58ede723-473b-4838-a8f1-afc8011b6d59 · outbound

This paper cites Croci and Marcelo Gennari do Nascimento and Torsten Hoefler and James Hensman , booktitle=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Croci and Marcelo Gennari do Nascimento and Torsten Hoefler and James Hensman , booktitle=

Reference 21

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source=arxiv_source observed=2026-08-02T09:43:27.881996Z digest=sha256:6bccfbe5bd6a7665f3f867a463ef683641c63f1ede3128813da7aaa47936f5ad

Observation dd3a70c4-2aea-4551-86bc-d87bfbd9aea5 · outbound

This paper cites 2024 , eprint=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models 2024 , eprint=

Reference 22

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source=arxiv_source observed=2026-08-02T09:43:28.019035Z digest=sha256:0692631ce92b22106b53e1aebdcada9db9c7812ff0bfdb42a0238acef5cbf21a

Observation 78f927a0-c856-4680-b825-83c98f6aa94a · outbound

This paper cites Proceedings of the AAAI Conference on Artificial Intelligence, , year=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Proceedings of the AAAI Conference on Artificial Intelligence, , year=

Reference 23

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source=arxiv_source observed=2026-08-02T09:43:28.195957Z digest=sha256:6c67f3c14d500b8f11ee2ae619eddfdd8e7490261e8a39b0b9a3e3ab28ae395b

Observation 6dfe5407-ea41-44d5-ace1-09307670fcdb · outbound

This paper cites 2023 , eprint=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models 2023 , eprint=

Reference 24

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source=arxiv_source observed=2026-08-02T09:43:28.261632Z digest=sha256:dfb4be70efbc9d4c6a92c9519c10b9f36078878ba9179f24a1f19e8f69f0d0a1

Observation 1646ebd1-1ae6-4a5b-b7d4-774468a4a38c · outbound

This paper cites The Llama 3 Herd of Models.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models The Llama 3 Herd of Models

Reference 25

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source=arxiv_source observed=2026-08-02T09:43:28.376760Z digest=sha256:0857c3c6d8c7abc93c8cf6268de0a5c74c09ffcf0b329b75123c0a6d131a0c1d

Observation 5892d8d3-c45f-44ad-a4d7-d3ef6b88d57f · outbound

This paper cites an unresolved cited work.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Unresolved cited work

Reference 26

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source=arxiv_source observed=2026-08-02T09:43:28.469075Z digest=sha256:54aa2c5d6b9aaf54e5f41097e230167649a52003e444b528ccdd5c66121ed4a5

Observation a0b3cb53-5a52-4214-923f-e7693d35f8fb · outbound

This paper cites Advances in neural information processing systems , volume=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Advances in neural information processing systems , volume=

Reference 27

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no resolver link, observed 2026-08-02T09:43:28.576853Z

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source=arxiv_source observed=2026-08-02T09:43:28.576853Z digest=sha256:18265789198f0b75c439f906f1bcac14ae8c7eb37097564fd09c4973ac56d203

Observation 4b65452a-9bcc-4740-b51e-ecc894384e28 · outbound

This paper cites Shortened.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Shortened

Reference 28

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source=arxiv_source observed=2026-08-02T09:43:28.694269Z digest=sha256:4992e23f8429ee7e678ba976ab612d6daf8165ec2537df5e3ec0a7af2045e3ae

Observation 041f2045-4ed3-423a-8553-d4d95cb17469 · outbound

This paper cites Mixture-of-Depths: Dynamically allocating compute in transformer-based language models.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Mixture-of-Depths: Dynamically allocating compute in transformer-based language models

Reference 29

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source=arxiv_source observed=2026-08-02T09:43:28.815504Z digest=sha256:f6953d27e43ee6529b533db47ea03543f175aefeb7664ddac73b8ce48455c39f

Observation f5c84c13-a663-4552-a231-485f7283f305 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Advances in Neural Information Processing Systems , volume=

Reference 30

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no resolver link, observed 2026-08-02T09:43:28.924569Z

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source=arxiv_source observed=2026-08-02T09:43:28.924569Z digest=sha256:f1bef6c98b70354bb4e9b8571c91d2fca454ea9ef18a8d707f7b4300613e894f

Observation 700dc7c0-a3c6-47ce-b8c3-8d9a033f10d9 · outbound

This paper cites Streamlining Redundant Layers to Compress Large Language Models , volume =.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Streamlining Redundant Layers to Compress Large Language Models , volume =

Reference 31

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source=arxiv_source observed=2026-08-02T09:43:29.025721Z digest=sha256:a6e408f0a1c5ca9a840b9d2450489e5ba243b68047f8ebb056133b64973be3af

Observation 613e1471-687b-4e08-8434-b78cf005d531 · outbound

This paper cites BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions

Reference 32

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source=arxiv_source observed=2026-08-02T09:43:29.071117Z digest=sha256:fed7747a89eb2e3a1aeef1edbf731ef64d1e25031660d028c2da22238b58e292

Observation 3510b8c1-36e6-4537-8a7e-22f15364da6c · outbound

This paper cites Proceedings of the AAAI conference on artificial intelligence , volume=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Proceedings of the AAAI conference on artificial intelligence , volume=

Reference 33

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no resolver link, observed 2026-08-02T09:43:29.126221Z

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source=arxiv_source observed=2026-08-02T09:43:29.126221Z digest=sha256:982d79a4881d8e026e9b3afa28244fbe479666b086288040a29a34d493fd0d76

Observation 53edb6a7-e767-430c-a77f-2c91a1431d2f · outbound

This paper cites HellaSwag: Can a Machine Really Finish Your Sentence?.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models HellaSwag: Can a Machine Really Finish Your Sentence?

Reference 34

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source=arxiv_source observed=2026-08-02T09:43:29.204046Z digest=sha256:d23bcc459f18c7d752636a2f8a67fe17bc7525132e6d2f1ec2bf5e64758adb7e

Observation d6e1b9e6-6bb6-464f-b7d2-db4972ee112a · outbound

This paper cites Communications of the ACM , volume=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Communications of the ACM , volume=

Reference 35

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source=arxiv_source observed=2026-08-02T09:43:29.316462Z digest=sha256:4f3d8692e892dd45ce16eca1bb8bbed86f5c135358aae01e134811803c59ded9

Observation c2a6383e-bdce-4b47-a15f-9227296f6ee7 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 36

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source=arxiv_source observed=2026-08-02T09:43:29.416679Z digest=sha256:717f1f6131bfdbf363b753c9cf739a61904927e9cd79864db77a439761a36efa

Observation e361d7fa-ecef-4202-bf6d-0a6c0812814a · outbound

This paper cites Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering

Reference 37

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source=arxiv_source observed=2026-08-02T09:43:29.575752Z digest=sha256:46565e70e611712933957068e777e08c506175cc3524a7e29ac115cf0edcff63

Observation 399f8a91-2bdf-4859-a20c-8c45d2efff8a · outbound

This paper cites 2024 , eprint=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models 2024 , eprint=

Reference 38

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source=arxiv_source observed=2026-08-02T09:43:29.761991Z digest=sha256:71387276a2e1be3b39cb2b2eb7b06265fa1bbb105f050757bebce4ba37e47686

Observation a1ea209e-8613-472d-b50f-922ccf05f541 · outbound

This paper cites ICLR , year=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models ICLR , year=

Reference 39

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source=arxiv_source observed=2026-08-02T09:43:29.905315Z digest=sha256:bf14d794bcde67a65447e1f73f408448536a038141f2a41395ebf8e3bd049cfa

Observation 4e21df06-ab3d-4bea-8a79-72b231297fef · outbound

This paper cites an unresolved cited work.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Unresolved cited work

Reference 40

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no resolver link, observed 2026-08-02T09:43:30.037602Z

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source=arxiv_source observed=2026-08-02T09:43:30.037602Z digest=sha256:2543f597393a2130eb6f2aeb9eae394f0279285302dfa9edf0ad122a548d6938

Observation ee99fc4c-552d-4533-83c0-c97251bf245c · outbound

This paper cites High-Dimensional Probability: An Introduction with Applications in Data Science.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models High-Dimensional Probability: An Introduction with Applications in Data Science

Reference 41

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no resolver link, observed 2026-08-02T09:43:30.174185Z

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source=arxiv_source observed=2026-08-02T09:43:30.174185Z digest=sha256:7042e017f4fa65f2c05f9767905f4dc9077c28ddac95b1cbc97172964982088a

Observation 39c08e9c-e859-4756-bd01-0ba755a1c212 · outbound

This paper cites Findings of the Association for Computational Linguistics: ACL 2025 , pages=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Findings of the Association for Computational Linguistics: ACL 2025 , pages=

Reference 42

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source=arxiv_source observed=2026-08-02T09:43:30.295482Z digest=sha256:dc6069a3decc6d4d5fb263464f48ae1111c9cd01dc7cbc96a04088c8d3bed021

Observation ff0665e3-3480-4b28-9727-60e017b3f20a · outbound

This paper cites IEEE Transactions on Software Engineering , year=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models IEEE Transactions on Software Engineering , year=

Reference 43

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source=arxiv_source observed=2026-08-02T09:43:30.488844Z digest=sha256:704fefbadb533725571137114b0c69a9e784ab6ea20303596428525e67000fdd

Observation e31b9b5a-e4a3-44e3-bd48-399b5f9f3a9d · outbound

This paper cites Proceedings of the ACM on Software Engineering , volume=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Proceedings of the ACM on Software Engineering , volume=

Reference 44

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source=arxiv_source observed=2026-08-02T09:43:30.594490Z digest=sha256:e7244cb714f6fabbe911e52a2e140920e35aa3d6f644a4bf8cd6d9958be05d22

Observation 64d75823-856a-4a48-bc55-eb34434c70de · outbound

This paper cites Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop , pages=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop , pages=

Reference 45

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source=arxiv_source observed=2026-08-02T09:43:30.653537Z digest=sha256:567157d1e4f592ee2e0f4b54126857259d4eb3d132cdd02e3e8753c7159bc9b6

Observation 3969746d-2f68-41fe-b6bb-ef61b2cf8133 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Advances in Neural Information Processing Systems , volume=

Reference 46

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no resolver link, observed 2026-08-02T09:43:30.742316Z

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source=arxiv_source observed=2026-08-02T09:43:30.742316Z digest=sha256:4a1ec0293a119867cee79009aca3e3d6d35a80220850f9ddfe87e45dc662f687

Observation 78443be1-1640-406c-98d8-5feae14b216f · outbound

This paper cites International Conference on Machine Learning , pages=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models International Conference on Machine Learning , pages=

Reference 47

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no resolver link, observed 2026-08-02T09:43:30.866619Z

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source=arxiv_source observed=2026-08-02T09:43:30.866619Z digest=sha256:182ed48b77852bf1d4f49436c7866873530e884032f49251757baf8b7d38297e

Observation 34e169a6-fcc1-44b4-8a2e-0117b7ae44bb · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Advances in Neural Information Processing Systems , volume=

Reference 48

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no resolver link, observed 2026-08-02T09:43:31.001536Z

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source=arxiv_source observed=2026-08-02T09:43:31.001536Z digest=sha256:d1d7c4e83b99ebefa280edd38f8170829b2d371c758134e34266f9f561c3222a

Observation 75b18ae8-fb8a-45f4-ac87-864522c18cc8 · outbound

This paper cites an unresolved cited work.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Unresolved cited work

Reference 49

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no resolver link, observed 2026-08-02T09:43:31.093164Z

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source=arxiv_source observed=2026-08-02T09:43:31.093164Z digest=sha256:4864de84c29a5e2c7e063343f4094e2d08fcd0a9116349f1b3c3a0861b95a430

Observation 5e2b3bfd-3044-418d-8c51-3a70c618d712 · outbound

This paper cites International Conference on Learning Representations , volume=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models International Conference on Learning Representations , volume=

Reference 50

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no resolver link, observed 2026-08-02T09:43:31.187108Z

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source=arxiv_source observed=2026-08-02T09:43:31.187108Z digest=sha256:3aa3c23a66ce8e7d37307771484b181110cb5e4c384591ba35aaa05fa3a3df20

Observation a30bab1a-46cb-414c-a0ab-e1b6446ecaaf · outbound

This paper cites International Conference on Learning Representations , volume=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models International Conference on Learning Representations , volume=

Reference 51

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no resolver link, observed 2026-08-02T09:43:31.293168Z

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source=arxiv_source observed=2026-08-02T09:43:31.293168Z digest=sha256:c33180fa608823500887e0dfff406918ca111ae141e873ee562d40c9e648d089

Observation 51c7ada3-439c-4b2d-b958-d514a4dd9822 · outbound

This paper cites Findings of the Association for Computational Linguistics: EMNLP 2024 , pages=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Findings of the Association for Computational Linguistics: EMNLP 2024 , pages=

Reference 52

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no resolver link, observed 2026-08-02T09:43:31.409141Z

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source=arxiv_source observed=2026-08-02T09:43:31.409141Z digest=sha256:6dd8ad481d95088db9654bf1d9ebad63ec0984f712ab6267c95ed72ee47d1e24

Observation 1ebbabeb-2cb1-44b1-8c37-b196c4267366 · outbound

This paper cites International Conference on Learning Representations , volume=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models International Conference on Learning Representations , volume=

Reference 53

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no resolver link, observed 2026-08-02T09:43:31.566650Z

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source=arxiv_source observed=2026-08-02T09:43:31.566650Z digest=sha256:d7d83ec2b4aae93206dabbb44f45db4fafc329b4d8b7f6ff5208a3f0dc5aa7af

Observation f995f745-0513-440d-a126-37577fbe81a8 · outbound

This paper cites International Conference on Learning Representations , volume=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models International Conference on Learning Representations , volume=

Reference 54

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source=arxiv_source observed=2026-08-02T09:43:31.702203Z digest=sha256:6f779ed0212eb3c6e9132397568e8b1297d55b001d8aa68aeab9def6c3ed26f7

Observation d5952e94-c144-4332-b5a6-ccfb7a9eb471 · outbound

This paper cites Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing , pages=

Reference 55

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no resolver link, observed 2026-08-02T09:43:31.881595Z

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source=arxiv_source observed=2026-08-02T09:43:31.881595Z digest=sha256:73396982c8c8fd315594a81571ceb6a57758ab4fd9deed81716cd0ec748865bc

Observation 63a00221-fdca-483e-aed4-6cd94d8d9bec · outbound

This paper cites Adaptive Rank Selections for Low-Rank Approximation of Language Models.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Adaptive Rank Selections for Low-Rank Approximation of Language Models

Reference 56

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no resolver link, observed 2026-08-02T09:43:32.007540Z

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source=arxiv_source observed=2026-08-02T09:43:32.007540Z digest=sha256:e27caa56b6facb92f8f4ebb5d165ae33f12129b8a484a8e0ae923c13bd883bfa

Observation b4cf804f-7660-473d-807d-78be63f57497 · outbound

This paper cites arXiv preprint arXiv:2509.25622 , year=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models arXiv preprint arXiv:2509.25622 , year=

Reference 57

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no resolver link, observed 2026-08-02T09:43:32.163470Z

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source=arxiv_source observed=2026-08-02T09:43:32.163470Z digest=sha256:45f59fa9055a77ef999042a2f20dac0aaaf02efecbb3538b9396cc86494f843a

Observation d9f275fc-20b5-4e1a-8cf8-dd46e0824117 · outbound

This paper cites Findings of the Association for Computational Linguistics: EACL 2026 , pages=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Findings of the Association for Computational Linguistics: EACL 2026 , pages=

Reference 58

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no resolver link, observed 2026-08-02T09:43:32.250083Z

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source=arxiv_source observed=2026-08-02T09:43:32.250083Z digest=sha256:d08200ffe7c9beed8fca577ac7191aab17777641f9667f7066a35998c1471477

Observation 175ba3af-89c3-4a46-b4f3-f8bf81717e27 · outbound

This paper cites The Fourteenth International Conference on Learning Representations , year=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models The Fourteenth International Conference on Learning Representations , year=

Reference 59

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no resolver link, observed 2026-08-02T09:43:32.330847Z

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source=arxiv_source observed=2026-08-02T09:43:32.330847Z digest=sha256:b3f9ca473efa9d97c5b9fc02a36cd9c010ea5e2469919ad11378237913aeeaba

Observation d1ca7849-d635-4fba-a970-c716ec9d1d19 · outbound

This paper cites The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter , volume =.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter , volume =

Reference 60

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no resolver link, observed 2026-08-02T09:43:32.396380Z

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source=arxiv_source observed=2026-08-02T09:43:32.396380Z digest=sha256:d6b87b376055b5074b46a12872879c61277c808c7bcb7dbc1d91bf873e379926

Observation 15a65fbe-6608-4568-a8a4-96989aeea9aa · outbound

This paper cites International Conference on Learning Representations , volume=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models International Conference on Learning Representations , volume=

Reference 61

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no resolver link, observed 2026-08-02T09:43:32.475146Z

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source=arxiv_source observed=2026-08-02T09:43:32.475146Z digest=sha256:d8d05474014d82e6378397cf2eeccc028a61d9da4ee31f5810ade2f5a15889ce

Observation 2ec31fe6-68da-456d-98de-4f68d9d933d4 · outbound

This paper cites Workshop on Efficient Systems for Foundation Models II@ ICML2024 , year=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Workshop on Efficient Systems for Foundation Models II@ ICML2024 , year=

Reference 62

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source=arxiv_source observed=2026-08-02T09:43:32.622263Z digest=sha256:1858ac49ddb9382f1bf0b7d72d44fac9dc17a77d603c93e03bd7ad80f00ae9fb

Observation b849494b-db02-4abd-9e03-7e7186f3d6c8 · outbound

This paper cites Findings of the Association for Computational Linguistics: EMNLP 2024 , pages=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models Findings of the Association for Computational Linguistics: EMNLP 2024 , pages=

Reference 63

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no resolver link, observed 2026-08-02T09:43:32.712626Z

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source=arxiv_source observed=2026-08-02T09:43:32.712626Z digest=sha256:b2db2fcae50035251f4069b538c5dd113597746e69a9d2eeaa15d6c1f7eddd23

Observation 8e92b25a-eb3e-4968-8d2b-a1db12c1cd30 · outbound

This paper cites NeurIPS 2025 Workshop on Structured Probabilistic Inference \ & \ Generative Modeling , year=.

Beyond Single-Dimensional Compression: The Compound Sparsity Frontier of Large Language Models NeurIPS 2025 Workshop on Structured Probabilistic Inference \ & \ Generative Modeling , year=

Reference 64

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no resolver link, observed 2026-08-02T09:43:32.802071Z

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source=arxiv_source observed=2026-08-02T09:43:32.802071Z digest=sha256:1d3f5d689da23735ab53583a087ecc5a8a7d02b02fe1f275bf5e1ff4e5fd222f

Pith citing papers

No inbound Pith citation observations are available.