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Paper Citation Record · LEDGER

Curse of High Dimensionality Issue in Transformer for Long-context Modeling

As of 18 August 2026, this Paper Citation Record lists 67 of 67 outbound references and 1 inbound Pith citation observation for arXiv:2505.22107.

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

pith.paper-citation-record.v1
2505.22107 v4

Coverage vector

measured 67 of 67 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:23:18.048778Z

measured 68 of 68 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-27T21:48:14.799377Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T18:57:16.733464Z

Reference resolution

67 of 67 outbound references displayed

  • verified exact0
  • verified fuzzy39
  • unresolved28
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 18651005-b509-4a02-902a-eb052e4dfd87 · outbound

This paper cites Flamingo: a visual language model for few-shot learning.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Flamingo: a visual language model for few-shot learning

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:05.497056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:05.497056Z digest=sha256:573ba2aa84e36e55fe613f8fbdcf652cceded3ab6e349c5004ab4623669a04c5

Observation c213ddd3-63fb-4db1-bee2-722f4144a7d1 · outbound

This paper cites and Krzywinski, M.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling and Krzywinski, M

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:26.932302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:07.321505Z digest=sha256:a0396f108ccb1b2f243424e3a408138a29f3bf7b38eac21ed92ce22cc8441407

Observation 039aee5e-6eb8-4593-9211-82712562113f · outbound

This paper cites Training-free long-context scaling of large language models.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Training-free long-context scaling of large language models

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:26.651407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:07.456894Z digest=sha256:492868660f3c725bfee6e96073c5db22553fc4e5811bf5c51e491986c5186229

Observation 6c76cc74-0855-4198-99b9-b0f4a49cf3ee · outbound

This paper cites V., Du, J., Iyer, S., Pasunuru, R., et al.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling V., Du, J., Iyer, S., Pasunuru, R., et al

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:26.355555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:07.623944Z digest=sha256:aaaea1a4d20832c0b8a75f7812f651fdf67be9ec8ba429925a877f335bc34969

Observation 35d62f6e-259c-4033-be00-0d8112a109d2 · outbound

This paper cites Proof-pile.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Proof-pile

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:26.114633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:08.111044Z digest=sha256:d56055def9591de10366ec51d41ee5dbac5c156dfd850aee63d08e369d968cd9

Observation 10e4d6a9-d381-4914-bf2b-1ac3edd3cec4 · outbound

This paper cites Longbench: A bilingual, multitask benchmark for long context understanding.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Longbench: A bilingual, multitask benchmark for long context understanding

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:25.891181Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:09.937823Z digest=sha256:09c312e88d54090228a46ca36eb623aad8f79fdc1b2b2518f8ee7b046a7dd711

Observation 7cb15523-72a2-4288-b599-a467d9a24ac3 · outbound

This paper cites Longformer: The Long-Document Transformer.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Longformer: The Long-Document Transformer

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:10.048655Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:10.048655Z digest=sha256:17d5961f479033479ab474a2d4433513c84d1171437f4d923533d1667283908f

Observation 36b19264-7f67-484a-a704-28fdec616a79 · outbound

This paper cites Mathematical analysis: an introduction.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Mathematical analysis: an introduction

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:25.637921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:10.190604Z digest=sha256:fabc2a3af4db25f42b808b77e26a175d12cc63adb480b4e9a6e3be59883bf882

Observation c2e4471f-e906-4e82-a20f-aa136f942541 · outbound

This paper cites D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:25.475625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:10.300741Z digest=sha256:b2fbbd972ddba37766bdb234b1a99e71bc480ade4c527cb4a7c705aaa95e795d

Observation eaf36553-f735-4d8e-828d-b49b294c2772 · outbound

This paper cites Improving multi-document summarization via text classification.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Improving multi-document summarization via text classification

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:25.232658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:10.427300Z digest=sha256:f84712e2d2b9d365218790f62cbfa765024d0e0741c09fca0a68516c4af78aa9

Observation 9fd682b8-f344-4cd6-8ce6-66a366169a58 · outbound

This paper cites Slimpajama: A 627b token cleaned and deduplicated version of redpajama.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Slimpajama: A 627b token cleaned and deduplicated version of redpajama

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:24.999777Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:10.578225Z digest=sha256:256c951008bbae1646ed3416bf8e527c7a0bb3cc2f73acd535a4d79f26fd862e

Observation 19da10e4-b6ec-4d44-b805-aac4373fc6a3 · outbound

This paper cites Extending Context Window of Large Language Models via Positional Interpolation.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Extending Context Window of Large Language Models via Positional Interpolation

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:10.730745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:10.730745Z digest=sha256:fd6089ab518563dfbad8c5186ad1dc56bf01c7f0001ab3e94d7d67b466ded3c5

Observation 4b167caf-ef02-49a6-95a6-e8fa051c0b25 · outbound

This paper cites Longlora: Efficient fine-tuning of long-context large language models.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Longlora: Efficient fine-tuning of long-context large language models

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:24.745161Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:10.900738Z digest=sha256:9a26e159928189271d2c7ed39ed68ebd92b852bc8223abba6c257c978f3ee40c

Observation 97f79d5b-f42d-4bab-a439-7fff2a8e841b · outbound

This paper cites Core context aware transformers for long context language modeling.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Core context aware transformers for long context language modeling

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:24.480152Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:11.090094Z digest=sha256:aaa9612aebfbd6ee41f88cb93e700b9b28fae10097d41356a39fa2713ede872e

Observation 88055cfa-c820-4caf-b54f-8978810f275f · outbound

This paper cites T., Raskar, S., Kale, B., Ferdaus, F., Tanikanti, A., Raffenetti, K., Taylor, V., Emani, M., and Vishwanath, V.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling T., Raskar, S., Kale, B., Ferdaus, F., Tanikanti, A., Raffenetti, K., Taylor, V., Emani, M., and Vishwanath, V

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:24.202919Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:11.230949Z digest=sha256:5d74b89257b3d9a1d3784896fba4a9fbc7811301ef056cccc23471a0666ba5a9

Observation 517aeb64-6b76-4a08-a313-fd13e8f9df52 · outbound

This paper cites M., Likhosherstov, V., Dohan, D., Song, X., Gane, A., Sarlos, T., Hawkins, P., Davis, J.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling M., Likhosherstov, V., Dohan, D., Song, X., Gane, A., Sarlos, T., Hawkins, P., Davis, J

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:23.906716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:11.429368Z digest=sha256:ff425af879d5676aebcdc31422df93067dd0979567c49efc453fd0cd27aeae11

Observation 4c2cc6f6-ed6a-416b-9cfd-d9335b67701b · outbound

This paper cites Flashattention: Fast and memory-efficient exact attention with io-awareness.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Flashattention: Fast and memory-efficient exact attention with io-awareness

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:11.567632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:11.567632Z digest=sha256:f1b817fa103484398d390d26d376d4e123fb1aa58ec7c6c18d2f62989107f86a

Observation b9152c8f-7bc6-4f7f-8a1d-34f11e075846 · outbound

This paper cites Eigenvalues and condition numbers of random matrices.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Eigenvalues and condition numbers of random matrices

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:23.737833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:11.681991Z digest=sha256:e227be7575fd33b4f25197249702cdf6e989b2aff0759f98f8718da10891d0b7

Observation 6cfc457e-b37f-496a-8bfc-3eb6398b8a76 · outbound

This paper cites GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling GPTQ: Accurate Post-Training Quantization for Generative Pre-trained Transformers

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:11.844293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:11.844293Z digest=sha256:e7accd625cf66c214404957bdf971b6997d055487b37511930d24bb20572e75c

Observation 74e21fdf-8cc7-4f77-9d34-24ad798e1e8a · outbound

This paper cites Data Engineering for Scaling Language Models to 128K Context.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Data Engineering for Scaling Language Models to 128K Context

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:11.956205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:11.956205Z digest=sha256:22c6a30905e57c7eb35ea7ad75fbe344fc6ff8de6c52da4ac66fe59746cddad8

Observation d80de69e-debf-46aa-855e-a36c9fb2f6af · outbound

This paper cites Minillm: Knowledge distillation of large language models.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Minillm: Knowledge distillation of large language models

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:23.487403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:12.103099Z digest=sha256:3104923d3aeb225e357d925dfe39c55ccb94b28385c8bbcc81bb6becc4fca133

Observation b6f39f0d-4cd4-4439-ba1b-049f3fb3b6ab · outbound

This paper cites LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling LM-Infinite: Zero-Shot Extreme Length Generalization for Large Language Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:12.222334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:12.222334Z digest=sha256:07873ee16867b5330048c4dc60b18967a63029d9515e6b7c91899f4dcde99269

Observation 299f8050-4411-4bb5-a4a5-c68ce9bff079 · outbound

This paper cites Hyperattention: Long-context attention in near-linear time.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Hyperattention: Long-context attention in near-linear time

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:23.267125Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:12.395393Z digest=sha256:cb9733aee21ceba71ad562a52bf803a53082e9c5fc14fd8fcfb39d76c331bc91

Observation f130aae4-29b6-4714-b51c-778dcfd423b4 · outbound

This paper cites Overview of supervised learning.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Overview of supervised learning

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:23.031560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:12.497966Z digest=sha256:c636a4694f18ed5916d3696c0cab1a54d669bc726172e8a1113f54630216bfc3

Observation b39b5d56-55ca-4faf-bff3-a4be71881975 · outbound

This paper cites ZipCache: Accurate and Efficient KV Cache Quantization with Salient Token Identification.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling ZipCache: Accurate and Efficient KV Cache Quantization with Salient Token Identification

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:12.619787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:12.619787Z digest=sha256:2e5b2edc9329429cafe8088f5223e7dc259c699e0927d89838a92cfc229f50fb

Observation b199c556-fb14-4647-a38d-c626f9e477c9 · outbound

This paper cites an unresolved cited work.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Unresolved cited work

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:12.810758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:12.810758Z digest=sha256:e6174d03cc9e1b3229a41896e5734db23e4f7dccd4620f33a2e1785d8c8b2933

Observation a9a852a4-fb86-4ea7-84b9-7804ce802148 · outbound

This paper cites Neural autoregressive flows.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Neural autoregressive flows

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:22.833972Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:12.923700Z digest=sha256:2e53c7a95cf36373d735664addfcdd6a0b6f7f43651a0dc189fe26bd9bc3d2d6

Observation f0aed81a-d536-4bfc-8211-e997cec1e746 · outbound

This paper cites and Zhang, T.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling and Zhang, T

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:22.572849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:13.076385Z digest=sha256:5abdb6fca986358e7cfdaede49d278ecb7e8d13e660a96269830d7f3c41c4c8a

Observation 63431ec6-16fa-44ca-9b6c-4f257bddefe4 · outbound

This paper cites H., Li, D., Lin, C.-Y., Yang, Y., and Qiu, L.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling H., Li, D., Lin, C.-Y., Yang, Y., and Qiu, L

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:22.428403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:13.232482Z digest=sha256:7bc3ced6d18fb30fe1d776c37d7852a0dad57edc758cc2ad106d454c37702389

Observation 0999e38a-3b49-45fe-a6f2-691364a638d6 · outbound

This paper cites Transformers are rnns: Fast autoregressive transformers with linear attention.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Transformers are rnns: Fast autoregressive transformers with linear attention

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:22.313392Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:13.362829Z digest=sha256:ad1a67b9287b17aa9e3c6d91630a3484a941ffacd45add51ead1f42f66ae28ad

Observation 138ba262-361c-4dca-89c9-a51e35701dd6 · outbound

This paper cites Continual pre-training of language models.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Continual pre-training of language models

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:22.176420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:13.510662Z digest=sha256:21ad4b68b88be78d14efa8587af9a99ec4948cd700e3fc9c404bd7e1882f6a25

Observation 52d14827-c8dd-401e-bd1e-1c1c4bf69142 · outbound

This paper cites an unresolved cited work.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Unresolved cited work

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:13.671525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:13.671525Z digest=sha256:7bbcd9f7fa8419e309871406256384fee3eccef7c91d1de556b9a73010344b39

Observation 37925fe8-47f5-4821-bf94-17d37850f5a8 · outbound

This paper cites Reformer: The efficient transformer.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Reformer: The efficient transformer

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:21.928588Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:13.861167Z digest=sha256:247780ee9d2c2f5deae2815c481d579fe2ded5499876a45d8ed88ce40a3d41d1

Observation c3d8f57a-17d7-4407-948a-90b6cf94f3e1 · outbound

This paper cites F., Lin, K., Hewitt, J., Paranjape, A., Bevilacqua, M., Petroni, F., and Liang, P.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling F., Lin, K., Hewitt, J., Paranjape, A., Bevilacqua, M., Petroni, F., and Liang, P

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:21.681311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:14.041225Z digest=sha256:ba6635dedd2f02bba40856f1fe1f5e4b7ddccb6ca08355fbaa40e5607a1bf299

Observation ff0e39dc-ca5c-400e-9fad-9cd93295b999 · outbound

This paper cites Scaling laws of rope-based extrapolation.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Scaling laws of rope-based extrapolation

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:21.514077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:14.195471Z digest=sha256:d9a5bbead49c628556d3980deb1de6a3db713dc11ce0cb34a38aa5f130e810bc

Observation 65c7cbbe-2678-4700-9c13-84911fe8f69f · outbound

This paper cites an unresolved cited work.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Unresolved cited work

Reference 36

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:23:21.302798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:14.372061Z digest=sha256:b621f59a73cc985022b58c6c303a8153f7537234c109fd83ac7a716ebaf9cfe4

Observation f2735ae3-7396-4d4e-8e96-b7a3f1eea879 · outbound

This paper cites Learn to explain: Multimodal reasoning via thought chains for science question answering.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Learn to explain: Multimodal reasoning via thought chains for science question answering

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:21.119597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:14.484747Z digest=sha256:39f29765c46a734757a9d9b2a601af0f00430853c1be6d3f5dccc78f9e14e218

Observation 03b2cd6d-a5a7-44e2-b8c1-465649052280 · outbound

This paper cites an unresolved cited work.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Unresolved cited work

Reference 38

Resolution
unresolved
raw_fallback, observed 2026-08-07T13:23:20.968019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:14.622471Z digest=sha256:c7cfcf152f8cd3abae9311d3927e6f8627a3add3e745c0239de82b7db041e39a

Observation 11d0f157-9be2-49d5-9aa5-d8efe0ce3325 · outbound

This paper cites The spectral norm of a nonnegative matrix.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling The spectral norm of a nonnegative matrix

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:20.788216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:14.725369Z digest=sha256:55df636f0328d62d30cd042d84c0aec64c2c681fc5acaed328af464cdad25332

Observation 2e501e07-2701-4d9a-b01d-8b65e82adb6a · outbound

This paper cites Landmark Attention: Random-Access Infinite Context Length for Transformers.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Landmark Attention: Random-Access Infinite Context Length for Transformers

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:14.831997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:14.831997Z digest=sha256:5cd5593e7707698e9ecba03b853b1f08af533b58dd314f7ecac49f81105054fc

Observation 16f7f092-32d2-4705-946e-33d40cb74eea · outbound

This paper cites An overview of the supervised machine learning methods.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling An overview of the supervised machine learning methods

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:20.639432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:14.939720Z digest=sha256:3e426a398eb612f88abfe56281ef22ab8b62b40221b0be5032e0fff77f9bfa5e

Observation fdf156eb-a02b-4c4e-9df9-28e6a0c48363 · outbound

This paper cites GPT-4 Technical Report.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling GPT-4 Technical Report

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:15.012231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:15.012231Z digest=sha256:578dca19b49ea4da99529bb78c9ecb20b7ba7bbde52555a70fdeded98d20ccaa

Observation c94da18e-f10e-4a5f-8fa7-d048b94a3e17 · outbound

This paper cites Data augmentation for abstractive query-focused multi-document summarization.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Data augmentation for abstractive query-focused multi-document summarization

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:20.504675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:15.111944Z digest=sha256:ada80f9e68675db61e807575d92b255b3e122ee92d69147b76aa415abedc9541

Observation 54d28dc8-a9a0-4740-aaf2-58fbf48e6fce · outbound

This paper cites Yarn: Efficient context window extension of large language models.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Yarn: Efficient context window extension of large language models

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:20.365654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:15.176797Z digest=sha256:1d837e3f9926caf3cd74a4aa6814adc330d632767cbc146da2ffbf99a92c5cae

Observation be1d2524-bcde-4aa4-85a3-eed6af8735cd · outbound

This paper cites Language models are unsupervised multitask learners.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Language models are unsupervised multitask learners

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:15.294294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:15.294294Z digest=sha256:77492d3d86d2c49de10459f65dd5c7a411a30a5307308388f7275aa1677b1afe

Observation cec19125-3f2c-443c-bac0-ad8140c62852 · outbound

This paper cites W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:15.453551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:15.453551Z digest=sha256:fb1061acfdedeed477bff77ecff2d5a98c8fd79efc0714e0c3d79fd07d0be82f

Observation fc8f9e81-8e5a-451c-8bfa-23eb5ebfcfc2 · outbound

This paper cites and Lin, S.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling and Lin, S

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:20.196227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:15.586474Z digest=sha256:7bc82cdf694cc30bc67d14c6d00b8ae723c03c35811dd9efa58dc54c014b61d2

Observation fb92a7a4-729d-4d90-bc04-852bf0c02b86 · outbound

This paper cites Are emergent abilities of large language models a mirage? Advances in Neural Information Processing Systems, 36, 2023.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Are emergent abilities of large language models a mirage? Advances in Neural Information Processing Systems, 36, 2023

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:20.091877Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:15.676961Z digest=sha256:4e13d05ec894f6f175cd114cdd5d20c3b1e66dce8a4cfe67f3a86d14cd956ec5

Observation b65a00ec-6579-499b-892e-707bc58af9bc · outbound

This paper cites R., Cole-Lewis, H., et al.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling R., Cole-Lewis, H., et al

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:19.908040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:15.822810Z digest=sha256:caa80d2b80e20718957d97fb20f21930134840e5f6ef8a63a8bbe9b71e8a555c

Observation d6615869-bd2d-41b9-bc50-aa1944c51ee5 · outbound

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

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Retentive Network: A Successor to Transformer for Large Language Models

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:15.954492Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:15.954492Z digest=sha256:3cc56389fa695175203117d784e01057e1b6b48f3420aa03a3f5a37f4c7939dd

Observation 45df5808-40aa-4e04-bb69-d7e02c445085 · outbound

This paper cites Sparse attention with learning to hash.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Sparse attention with learning to hash

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:19.670386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:16.043002Z digest=sha256:3d6538c442063982b4e609d7d1a82cc5bd48869e6337a895eee48084a4a82051

Observation c3dbd60f-dea9-4aa4-aaa1-cbf67bc6369e · outbound

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

Curse of High Dimensionality Issue in Transformer for Long-context Modeling LLaMA: Open and Efficient Foundation Language Models

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:16.146762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:16.146762Z digest=sha256:237ec40b3f5cf401f03f01d00d254282a689dcc608057ca8177f0295d56dcbab

Observation b422c2a4-0013-4502-aa35-17d807464fc1 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:16.277430Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:16.277430Z digest=sha256:d11f65e2a983f78b9429bf5141e3bdaee53ac24411c2aacae228f0dfcb901c52

Observation 84a3b04e-5b8d-44c6-82b7-27af9452da45 · outbound

This paper cites Focused transformer: Contrastive training for context scaling.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Focused transformer: Contrastive training for context scaling

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:19.478740Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:16.386129Z digest=sha256:86673ffdb509a56ac8e2538101777da21bfefddfd0ad91a73f13be3401d03bc1

Observation 87e4d887-0a83-4a15-8e22-2e011a254f15 · outbound

This paper cites Attention is all you need.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Attention is all you need

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:16.512204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:16.512204Z digest=sha256:ff3fc5160d5de11033a8c14da95b580c9b9915742ddd98f1ee0a9fc707d4f05e

Observation c97b554d-698a-4c8e-ac4d-4f4c4aec1bff · outbound

This paper cites Emu3: Next-Token Prediction is All You Need.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Emu3: Next-Token Prediction is All You Need

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:16.626693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:16.626693Z digest=sha256:9908525081f3f965f1677a0ef35b92cb9ad69879a195c5e2ba070c2e68ac38ce

Observation 55799ab1-3984-4f1f-8861-7db453514f8c · outbound

This paper cites Model Tells You Where to Merge: Adaptive KV Cache Merging for LLMs on Long-Context Tasks.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Model Tells You Where to Merge: Adaptive KV Cache Merging for LLMs on Long-Context Tasks

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:16.748973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:16.748973Z digest=sha256:bd5f88878c62a8984a373fa0dacd311b2b53d02cf43b909a41fb9d9dc0c3d395

Observation a9f749b2-475b-4492-9d5f-065a4318b63d · outbound

This paper cites V., Zhou, D., et al.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling V., Zhou, D., et al

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:16.882892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:16.882892Z digest=sha256:770b97aee4ce1ae97f02b7842d28557d525979fbc10d963da0c43774dbbafbb1

Observation fa9203f0-0b0a-4f8f-9e78-e801f189ccf9 · outbound

This paper cites Efficient streaming language models with attention sinks.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Efficient streaming language models with attention sinks

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:19.253659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:17.013916Z digest=sha256:fb4ce2cdddf34f5762d1cb0973216f371fefca0df2b97c0e759ce47aad8af559

Observation 1b6c7e42-8989-425b-9aad-819a31bd7dd0 · outbound

This paper cites A., Oguz, B., Khabsa, M., Fang, H., Mehdad, Y., Narang, S., Malik, K., Fan, A., Bhosale, S., Edunov, S., Lewis, M., Wang, S., and Ma, H.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling A., Oguz, B., Khabsa, M., Fang, H., Mehdad, Y., Narang, S., Malik, K., Fan, A., Bhosale, S., Edunov, S., Lewis, M., Wang, S., and Ma, H

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:19.026709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:17.147867Z digest=sha256:dd6b28578b2105759f37044e3c2eedd4e36f8c11169eca072c2e92d6715b2de8

Observation 1a6a0cb8-764c-4015-b57a-1585ca714643 · outbound

This paper cites Long-context language modeling with parallel context encoding.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Long-context language modeling with parallel context encoding

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:18.749679Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:17.231268Z digest=sha256:2945f949e938b63dfa7427297b03e8888bf5d535f7d3a85afc269f141f4ae5a2

Observation 906dbd58-3240-4530-a03c-1e4d84aa0c9c · outbound

This paper cites A., Ainslie, J., Alberti, C., Ontanon, S., Pham, P., Ravula, A., Wang, Q., Yang, L., et al.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling A., Ainslie, J., Alberti, C., Ontanon, S., Pham, P., Ravula, A., Wang, Q., Yang, L., et al

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:17.318637Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:17.318637Z digest=sha256:1c17912b4f8c9fc709a32b630deb80a558531ea0f3f78bb95e15de7e8f879722

Observation c0cc82a2-9832-452d-874d-a6320360af00 · outbound

This paper cites Generative Verifiers: Reward Modeling as Next-Token Prediction.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Generative Verifiers: Reward Modeling as Next-Token Prediction

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:17.432878Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:17.432878Z digest=sha256:7f8b8d1f14df684268c3a69dd2b20970638133b8bbbeb569bdbd7505840885c8

Observation a9301f6d-79c7-40ea-8265-2caf6e639b1b · outbound

This paper cites OPT: Open Pre-trained Transformer Language Models.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling OPT: Open Pre-trained Transformer Language Models

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:17.614845Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:17.614845Z digest=sha256:4eee34370b656e9a36e504b4c9edfba5299a8798e120127049b1895e6a8b9782

Observation e336b779-99da-4b72-b53d-88cc1c33af2d · outbound

This paper cites H2o: Heavy-hitter oracle for efficient generative inference of large language models.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling H2o: Heavy-hitter oracle for efficient generative inference of large language models

Reference 65

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:17.750697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:17.750697Z digest=sha256:8d34601cbfeb8dcaee57d184386d84aef79eaa5418604e8bc5b5d44d826f722f

Observation 86f2e456-ecf4-4ac3-a030-f06d3c57879d · outbound

This paper cites Pose: Efficient context window extension of llms via positional skip-wise training.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling Pose: Efficient context window extension of llms via positional skip-wise training

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T13:23:18.495756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-08-07T13:23:17.886475Z digest=sha256:6237fbd77393d85ef376cb6ae5236581185b62b02715448d392c44cb7ac7e5d5

Observation 1cf7fd48-3584-4635-871c-c3ce72914c83 · outbound

This paper cites write newline.

Curse of High Dimensionality Issue in Transformer for Long-context Modeling write newline

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-07T13:23:18.048778Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:23:18.048778Z digest=sha256:a754653859dcba11dbaa3f6ea49a5231aa350decd0666ab594206cf577e7a96c

Pith citing papers

Observation d2243730-4e23-4389-a64d-66de4541f70a · inbound

Geometry of Semantic Space: Comparative Study of Discrete and Continuous Models cites this paper.

Geometry of Semantic Space: Comparative Study of Discrete and Continuous Models Curse of High Dimensionality Issue in Transformer for Long-context Modeling

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-02T18:57:16.734945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-06-27T21:48:14.799377Z digest=sha256:bd86a7f687c47028f6105c9e4a66ce467ddaf1f065268197fc01d4f41443673a