Pith. sign in

Paper Citation Record · LEDGER

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

As of 8 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 2026-08-07T06:34:17.273281+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:a459a604dc203f85aaf5270b38ac20a7e39a375f3495a033e54a601e63d1406e

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:07.321505Z digest=sha256:24a2c2f8b1714033590585fd82870b99582a38fb35b3fbe7d2b1af253a365f3b

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:07.456894Z digest=sha256:9538c95ff9aa326237ac56626fd1f21f5c3b82e33618be962884c20db0ef4feb

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:07.623944Z digest=sha256:49df37dbd963065751b2caf1b2c54b3c001b9e17ec63fcf5ae279db4fe05a41d

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:08.111044Z digest=sha256:e935ae7d248bfff0dcf96401ed11e6c876531efd724e9c843825e59d5d2c27cb

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:09.937823Z digest=sha256:226413402ec36d6da50b27e4b777dd5eac399525d09b1c9519eabab18955f36c

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=sha256:96cea15f094a5edbc9d1834758c6587e7b7f892f5c87006b4b3b812ff35612c7

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:10.190604Z digest=sha256:1a2662023c4cebe4e29f8296f89e3f4610617fcc6b233a53ac6c7f099e0570f0

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:10.300741Z digest=sha256:77f4a7e73ddd93171a454e9536b5a992edecd7ccd7362bd5848df9aff8988e73

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:10.427300Z digest=sha256:bb5121a9dbd40590880d3d467e307345c64fc3510b2349b10b8097be05f9b1a2

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:10.578225Z digest=sha256:323e21e246a3140524c23296e8018e95d2eae53a9ca624c5d9ea94f65b8e1979

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=sha256:6986a1a4f15d4c1062e6dc585fce721adb4baedb58c6bdded9f6e68b382cbfdd

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:10.900738Z digest=sha256:d03bacb7463901e1c8e7857495b892702ea8352ec6efda5561b5b39e1ba84a6f

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:11.090094Z digest=sha256:082cc227cec7c17d291fee41d2504e55313cbb650e311243d25af9f6c2cbd485

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:11.230949Z digest=sha256:5f63cae960ae777af6c9b2b391020b79284a019252448420f6d55d8474699a9d

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:11.429368Z digest=sha256:6380f4fd4bda223ec0f9aa4c2b579aff8d06e5b26f139f862f21d69bf931ea6a

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=sha256:9189a0aabbeebef297dd094e2180eb87e62a1aa7afb582b09365794b52cfdbfb

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:11.681991Z digest=sha256:850da951e35bdc2128f1f3d4e4e121d2ba8ff3644dbf8eff2d6131837c62d733

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=sha256:8a496ad2191741a5c1237667182007254d215394661ad136091eb471c6bbada9

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=sha256:79ec798dfcf8d0ff5520282ca46c8a2f490a1b661dddff692edb9cfab0ef4829

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:12.103099Z digest=sha256:c73355b6d27bfe5af5ca96a1fc280ee619b9c73d56bd3bf08c9d4489fdf9e7d2

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:a9315ca7289b42eb3e6b1719575fc45088b0d67b8f7053999a04dd11f29e52ab

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:12.395393Z digest=sha256:3eab957dbdcfaf0037cdd4f2f36affcbd3c105254d6c98b6ee6690fd5909fca1

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:12.497966Z digest=sha256:f798f583f6440d95e82a2cce20f10dd43e6b2c7fc3f4a2423181624ed949d51e

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:ea2b4d9a21dbbd467c842aec358a198868f761b6610223aacae219076c68eced

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:ad50c8f673b436c7c896e8efe0ed308a778b1063d6c64d270b3b8e7883f85e86

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:12.923700Z digest=sha256:5cb823447617e8bb008772c4bed209d960555fb5fb0dcd6ee2ea1df59f06a6fa

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:13.076385Z digest=sha256:6ebfb8c753f0531d86c24cb7b0f78e9ac3e38dd214792f5a93dd3f4d306ec446

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:13.232482Z digest=sha256:82a63589e48bc95c623f35e3ab78e0cf3f9df0d4db67f7566f7b7f9576038ef5

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:13.362829Z digest=sha256:6ce2cb0c8e921a383d5ca36421167efeee4544f616eb30f5ed2ad07409c9e3f7

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:13.510662Z digest=sha256:0c1d875aba764a5a8f594e7bdfdde20b3db0c47216c0496c2f6cb60989ac1910

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=sha256:3f09b9797d9f8d4e4b78d8a5c49185f8c4f44e2e76003dfc06d3c1162315b90d

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:13.861167Z digest=sha256:8c3852d75fc209bff010b983be799118e9e46f8c2c135ec39068ec8b2c376d21

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:14.041225Z digest=sha256:85f477adf7b4250a480d25c8422d6adf8e624c8866393cd4d190860e7fd5cbd2

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:14.195471Z digest=sha256:496310e57560e4f83cda1e532f0cf863bc264fb3eec0875d5f09705817295f17

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:14.372061Z digest=sha256:8858e1d715d35a2378be84a26ff23a67a42c80c679c12445a3a1295ee3d86965

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:14.484747Z digest=sha256:eb55fd0f7d476538c3c46f569c5e120d74cfc55b9cecc28a911a075b63ec3bf8

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:14.622471Z digest=sha256:ff1d65e709091e82aeb2180a582a934c9556d5d9ee5fd643b82f81be8a30f23e

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:14.725369Z digest=sha256:2da5b00e3b3791b73febaf4d2abbb1059990de5e342ea085a1d7ceb0b098cec5

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=sha256:7eaddc2b74036122c04825ab36c4beaaa84c83703fd62ad7e18bc24066f9c46f

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:14.939720Z digest=sha256:9ed54cb9a71ca9772664d125f385dfd5ad5e93b670707f887abb6dab2970d501

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=sha256:46bd3cdec00a1fd83806c1e095f282a97eb04f19c50e63e518cfb68c24b7b39f

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:15.111944Z digest=sha256:8c00cff30afc12f46b6ef0413b911ffa9dbbbb6557499482ca62f680c0f8f738

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:15.176797Z digest=sha256:53a28e969c160bddc74b9cdf467644e88f9c3c12051e1db864683134f52d110f

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:e50f01c8d5bbb4c02d978cf32b016b22d60784078da812b034e0d41f7368281b

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=sha256:2364d6f09f57093f61e473a6f8fb5ca54a9306869ea79b7b77156d771e0c6ce7

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:15.586474Z digest=sha256:b7e05101d076c3fe094c0cae4713906238daefbcb1c27faa1b2d509cf3ad5ef9

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:15.676961Z digest=sha256:689bccded8886980b7d1049906362ac2d7aac295aa2c81188211ca83b0de5923

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:15.822810Z digest=sha256:27adb0a9e5b8b2876d8e9827f601ca97d77ed49a59b5a91094d68b39648fa77c

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=sha256:019de12419feaa44ef0d6bf8aab684d4ba48bd184964f3fffe7250ff979107a5

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:16.043002Z digest=sha256:c1ceb75216c22b74b2636a2bdb9b7d597d4bbf26d6a7335e83b03ababcdfca57

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=sha256:90fb9f8d9d030c2170f2b41cae0daf58aaf5a8b8174da1ef43cd6db9f5ff2c59

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:e9c5d0a683ec97e91a4fa8770e499a28fed0151995add31e2c686e3ca8da4f0c

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:16.386129Z digest=sha256:73d0cfb4bba3c3aa823fd4b37b0295a09fc63d74bbaecc7261809d03954e058a

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=sha256:1dd52d96df8c774b722ec3cc3afeeb889af485993b1c0b3915d78b32ceb870eb

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=sha256:6441285b463324d1fec1ce034508b39100edc2897841db7305acb033c496403a

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=sha256:144558b8136a9504c77fb9fa55fe9a0d3299f764061cf917229b1d5efe012ddc

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=sha256:69c08256ad4b5e2802d59edb0fbf4404a3b0e101e349e0adf059743d750bb640

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:17.013916Z digest=sha256:3ed8a165830c1ded3e408244b67d41616fb0dd108c5d415735a371e5befe3e03

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:17.147867Z digest=sha256:670f28f409dc009d999a8517e7f6d9ef450b1680ad116c0fbcce3532cac35a87

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:17.231268Z digest=sha256:d9f96f93240713b334f7ddf1a3eabee239ffc8bcb4ab20225c9f668df9eb7c51

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:e7a8db7840780b3df0b4fff6e0b11298ee27eb4f34be58950e87b540fa0f3fe8

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:afe681857071e4926ce5bff821281d47cbd3a932fb42063669b60d5e124cf94c

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=sha256:6e15c5c0b9dc39c9897196a1685f0f9f3f0c3b0ac3a3abcaea2472db59b3b01d

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=sha256:57b74526a88d652ade49b13215e6771b8c37422c7bf1b5e18051d8f04f6e7dda

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-08-07T13:23:17.886475Z digest=sha256:9cc99684405603af00e45fea17ceed8633c35c9a6969a98578c5314ad79b7bb9

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:ba4f72e5c115053806afdd79d7b7b81769305a2debbb0aee8dcd97866c94a68b

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 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-27T21:48:14.799377Z digest=sha256:f1af39c20c78f5e4bf57fd879f3337e0901f4cf497b7982506dbc14433268333