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Paper Citation Record · LEDGER

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models

As of 9 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2506.00773.

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

pith.paper-citation-record.v1
2506.00773 v2

Coverage vector

measured 50 of 50 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:03:44.519800Z

measured 50 of 50 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

50 of 50 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved47
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 12c9a85e-18ab-469b-8045-f9456745db0a · outbound

This paper cites The Llama 3 Herd of Models.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models The Llama 3 Herd of Models

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:40.093460Z digest=sha256:c554a417e1bb830a1e5898b419b40bf0e6ac2a9999bf16c7d2b865ca8d62b89e

Observation 02a18c03-ea77-457a-8ae5-8f90b1fd9fed · outbound

This paper cites Training-Free Long-Context Scaling of Large Language Models.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Training-Free Long-Context Scaling of Large Language Models

Reference 2

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:40.190364Z digest=sha256:4f8751da6cdf3e08df215d6d043bbb2017eea01e388fd31bc86e0551f6d3bd89

Observation c14d79ab-161c-42bf-afb9-b5aec0942410 · outbound

This paper cites Qwen Technical Report.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Qwen Technical Report

Reference 3

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source=arxiv_source observed=2026-08-07T12:03:40.303289Z digest=sha256:80ba602fd9fdf4bc4a982066b035c8ba0cd5f65ea6674f08fb8640ff21602a1d

Observation b275cf8e-3e98-4ddc-a9d5-0333ec3044de · outbound

This paper cites CItruS: Chunked Instruction-aware State Eviction for Long Sequence Modeling.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models CItruS: Chunked Instruction-aware State Eviction for Long Sequence Modeling

Reference 4

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verified exact
local_arxiv, observed 2026-08-07T12:03:45.845512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:03:40.425788Z digest=sha256:6327ce514b85a7cc9c54fa764efa04634308b11f5cd78dc036e502a48b9dd28c

Observation ac8016a0-97ab-4198-bec3-8c0da94bbb03 · outbound

This paper cites an unresolved cited work.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Unresolved cited work

Reference 5

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:40.477506Z digest=sha256:f1538a25a6e484bd571fe329a920bfcd62730ef451990df0b6ed575cfcfa297f

Observation 781cc14f-4c19-4c7d-b22e-1cfadb25b435 · outbound

This paper cites an unresolved cited work.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Unresolved cited work

Reference 6

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malformed identifier
no resolver link, observed 2026-08-07T12:03:40.544349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:40.544349Z digest=sha256:95a354af04ce51de66974e288b485adec0fb96e7cafb47b3931025da9b44a701

Observation 7d198958-4fb4-4cd9-82e4-3504aaf2732f · outbound

This paper cites Longformer: The Long-Document Transformer.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Longformer: The Long-Document Transformer

Reference 7

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T12:03:40.619658Z digest=sha256:f69b8e59d15dedd2e3610b1b41f2c33fe61cc54c7f1d2a74283222a238eb7229

Observation 36fa0ae3-839d-494a-9e2b-3c43555eab20 · outbound

This paper cites Unlimiformer: Long-Range Transformers with Unlimited Length Input.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Unlimiformer: Long-Range Transformers with Unlimited Length Input

Reference 8

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:40.693600Z digest=sha256:dff191eb02463a9f1b2439a86c4ccd18aac26c1f1ef251a3d709695d653fc63b

Observation bac1dbd7-be40-46d5-ae74-0b231b0b1487 · outbound

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

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Extending Context Window of Large Language Models via Positional Interpolation

Reference 9

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source=arxiv_source observed=2026-08-07T12:03:40.776103Z digest=sha256:25d4d7db972ce9da0ffdcb23d56717938a16858f1512a8d1a1e910369e2b3659

Observation 0d9941c5-ec33-45d8-bec3-860ed5957826 · outbound

This paper cites LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models

Reference 10

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:40.872696Z digest=sha256:2852fa6f9930545f9bde84af0101c07685d170a1b45ab24dd0814983f10ddd21

Observation 9615bdfe-9beb-412e-a2e1-d68775fbe483 · outbound

This paper cites Smith, and Matt Gardner.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Smith, and Matt Gardner

Reference 11

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source=arxiv_source observed=2026-08-07T12:03:40.959250Z digest=sha256:0e331b7980e8d60b81543543d54ab7ab8a5439ee7a965dd910ee0c3bf97652cc

Observation 5d53ce6e-9661-4bfb-9adb-42e0c5140132 · outbound

This paper cites an unresolved cited work.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Unresolved cited work

Reference 12

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no resolver link, observed 2026-08-07T12:03:41.044008Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:41.044008Z digest=sha256:106b6fa7d1b225d8fac29d0bd3d28c72381c3c210912fec117e7138e7f1d4217

Observation 45d42160-98d9-425e-8c53-3d88cfea9aba · outbound

This paper cites HMT: Hierarchical Memory Transformer for Efficient Long Context Language Processing.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models HMT: Hierarchical Memory Transformer for Efficient Long Context Language Processing

Reference 13

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no resolver link, observed 2026-08-07T12:03:41.146893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:41.146893Z digest=sha256:39b43e7dca8a83a233fa8ebe401e8ece371caf53d0a461d9901db10a8e1a5a38

Observation 01dd1903-0daf-432a-84f2-cf6a17cc1606 · outbound

This paper cites an unresolved cited work.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Unresolved cited work

Reference 14

Resolution
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no resolver link, observed 2026-08-07T12:03:41.260219Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:41.260219Z digest=sha256:939f1fd11bc43a6e9c7724b43c2371b9f3da325d3222b0ffeb491188323415a1

Observation 394d5c4d-977e-4182-95ef-d48acf03054f · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models LoRA: Low-Rank Adaptation of Large Language Models

Reference 15

Resolution
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no resolver link, observed 2026-08-07T12:03:41.374429Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:41.374429Z digest=sha256:830c2a09542214291fb291dfabf75e1a06530d6952c64d7ebf59cd991d363408

Observation 505f9b33-adf5-4547-8ce8-426059b6a936 · outbound

This paper cites Mistral 7B.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Mistral 7B

Reference 16

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:41.461651Z digest=sha256:2bf9cfb5011ee4df3fe25a143453b700f29e3eebd3812661e088e95bbb465ef1

Observation 74dbdca3-8635-404e-86e3-82b913ce537b · outbound

This paper cites an unresolved cited work.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Unresolved cited work

Reference 17

Resolution
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raw_fallback, observed 2026-08-07T12:03:46.206673Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:03:41.593449Z digest=sha256:178c2f3a6bc32e93a981bcf95117ceb988bee37e8a8bcc5ac4f99b914e0fe942

Observation 7ab08dbc-e1b7-4959-8723-5e5bc25ba842 · outbound

This paper cites an unresolved cited work.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Unresolved cited work

Reference 18

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no resolver link, observed 2026-08-07T12:03:41.713006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:41.713006Z digest=sha256:9195a21842a85fb8c700e6b84c9944a68ff163ed4edd4a2ab12d1de4f8dce19c

Observation d8fba2f6-3aa6-4199-9bcf-84072ca3e2e8 · outbound

This paper cites LooGLE: Can Long-Context Language Models Understand Long Contexts?.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models LooGLE: Can Long-Context Language Models Understand Long Contexts?

Reference 19

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unresolved
no resolver link, observed 2026-08-07T12:03:41.800526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:41.800526Z digest=sha256:820c4210b875dafcf3596e608870d2bcf3566cd3dc984a47247104c1c0e8d07d

Observation f07e4c77-b7bb-42bc-8709-25c1af426d98 · outbound

This paper cites Mixture of In-Context Experts Enhance LLMs' Long Context Awareness.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Mixture of In-Context Experts Enhance LLMs' Long Context Awareness

Reference 20

Resolution
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no resolver link, observed 2026-08-07T12:03:41.896069Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:41.896069Z digest=sha256:84b900ab29665192ececa1d3af48f2e892ab9f760b5ad7832cbab990df33b168

Observation ad254740-002c-47e2-8a31-58b46d8287c0 · outbound

This paper cites Lost in the Middle: How Language Models Use Long Contexts.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Lost in the Middle: How Language Models Use Long Contexts

Reference 21

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source=arxiv_source observed=2026-08-07T12:03:42.014059Z digest=sha256:3b8a72fefdb7ba50162d2551fa7df614b60fd72be7b806121b7277082c098e57

Observation d64e8f79-6918-46ba-904a-bdcc90c9e711 · outbound

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

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang

Reference 22

Resolution
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no resolver link, observed 2026-08-07T12:03:42.110187Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:42.110187Z digest=sha256:1c1242235c690691ffc67a6e5053ef8f8eeab01f7d7a024e32e1cfbb6cbe8c7b

Observation d91dbba7-94e8-45e4-a572-7d034147c3b8 · outbound

This paper cites LLaMAX: Scaling Linguistic Horizons of LLM by Enhancing Translation Capabilities Beyond 100 Languages.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models LLaMAX: Scaling Linguistic Horizons of LLM by Enhancing Translation Capabilities Beyond 100 Languages

Reference 23

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no resolver link, observed 2026-08-07T12:03:42.203785Z

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source=arxiv_source observed=2026-08-07T12:03:42.203785Z digest=sha256:07e97a9f40435447a2a8c3d1c6ab243bd2edaa68f2081667abec4dda02739533

Observation d860466c-31e7-4b19-8ffc-91d98f44ca5d · outbound

This paper cites Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length

Reference 24

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source=arxiv_source observed=2026-08-07T12:03:42.333662Z digest=sha256:6a02f1dae23c02f655dde2cfb76b4f5fd4f22e1c1af888f4c54bce9d0e7461c4

Observation e0da00ea-8990-45a2-9d58-703eb309cec5 · outbound

This paper cites GPT-4 Technical Report.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models GPT-4 Technical Report

Reference 25

Resolution
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no resolver link, observed 2026-08-07T12:03:42.448292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:42.448292Z digest=sha256:b7dc71582cfc6cd91d1250f5c4bac0ce474cd474fdb5636c90e216b443fe0cc1

Observation acd58307-ba1d-475d-989c-cde40fe46f23 · outbound

This paper cites Transformers are Multi-State RNNs.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Transformers are Multi-State RNNs

Reference 26

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no resolver link, observed 2026-08-07T12:03:42.533672Z

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source=arxiv_source observed=2026-08-07T12:03:42.533672Z digest=sha256:eae563068ee71fdf754ccbfc181a7af31aa59b15e6817d9a938bf82c0728ed4e

Observation af5d7a5b-b38f-4a74-bdde-d933be8f2227 · outbound

This paper cites YaRN: Efficient Context Window Extension of Large Language Models.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models YaRN: Efficient Context Window Extension of Large Language Models

Reference 27

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unresolved
no resolver link, observed 2026-08-07T12:03:42.602545Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:42.602545Z digest=sha256:800dbb069f770b7c1cb8e82205bcc0e84ef7e5b2bda44ad20c973e2ce67d89b8

Observation ad1d4e93-ce40-4d56-9551-ab6c777b90e0 · outbound

This paper cites Know What You Don't Know: Unanswerable Questions for SQuAD.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Know What You Don't Know: Unanswerable Questions for SQuAD

Reference 28

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:42.683563Z digest=sha256:33f1b87c2ad5dcd94b974ba05dc6aa8de9ef121470aea600ea7835522d403900

Observation a3b48dcf-2dea-4a96-b713-9946a9b6e2fd · outbound

This paper cites CoQA: A Conversational Question Answering Challenge.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models CoQA: A Conversational Question Answering Challenge

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T12:03:42.763358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:42.763358Z digest=sha256:36949826868306f3e5c8c7d0b39b18642fea480a9f911cee1a4c05371c8c8176

Observation b631bb18-f4cb-4591-8aeb-e1104e87ddf5 · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 30

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unresolved
no resolver link, observed 2026-08-07T12:03:42.869619Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:42.869619Z digest=sha256:14c22e33a0b52429d5b6b708665ad8c70a512ef3fba2d123533f84c6a165c61e

Observation 68ecd262-64b7-4648-ad95-af566e18b89e · outbound

This paper cites an unresolved cited work.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Unresolved cited work

Reference 31

Resolution
verified exact
doi, observed 2026-08-07T12:03:44.785686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-08-07T12:03:42.951056Z digest=sha256:73ab64e72cd0d4620708a4a00ce42aa45f32ed16abdf845cab4003f6972383da

Observation eb52ef99-3dce-4c01-b882-a553dfacd342 · outbound

This paper cites Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs

Reference 32

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no resolver link, observed 2026-08-07T12:03:43.032861Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:43.032861Z digest=sha256:7d84210f94f9baa8fc83a8d27152b006d46f80b48e8a2b1a30a791bf18699d8e

Observation ba81dd5e-34a4-4013-a036-29eb78f38337 · outbound

This paper cites an unresolved cited work.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Unresolved cited work

Reference 33

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no resolver link, observed 2026-08-07T12:03:43.123191Z

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source=arxiv_source observed=2026-08-07T12:03:43.123191Z digest=sha256:b0f0829e7496780f2ef1f4c70994f419d39126dbc52193cde7ccd719f8e00318

Observation d87ec26e-52f1-4691-a5fb-221ca48b3a4a · outbound

This paper cites an unresolved cited work.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Unresolved cited work

Reference 34

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no resolver link, observed 2026-08-07T12:03:43.191001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:43.191001Z digest=sha256:93f3261795908b0d7e414efbe2f3f6b8ab65939750aa7925676b657e4e4c9968

Observation a315ba3a-8133-4473-a4c6-0d44279f326d · outbound

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

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models LLaMA: Open and Efficient Foundation Language Models

Reference 35

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no resolver link, observed 2026-08-07T12:03:43.280931Z

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source=arxiv_source observed=2026-08-07T12:03:43.280931Z digest=sha256:e761b3d7fc01b8f228c7e692d4aff34a7aa9960f28e8c56e96b2852452daf26b

Observation 9c311621-3475-4611-9d60-834f08a68aae · outbound

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

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 36

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no resolver link, observed 2026-08-07T12:03:43.380073Z

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source=arxiv_source observed=2026-08-07T12:03:43.380073Z digest=sha256:5f5fca9981e948c4d6c4125ba12bc8cc2530ffce80276f6fc34845b610458fe9

Observation 1a3f86fc-f30b-40c6-a998-35f408d867ca · outbound

This paper cites an unresolved cited work.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Unresolved cited work

Reference 37

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no resolver link, observed 2026-08-07T12:03:43.454235Z

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source=arxiv_source observed=2026-08-07T12:03:43.454235Z digest=sha256:3b2b961611d26c70cd90c70cd28ecfe6bdb1856c9119053bf704e308c05b6a8a

Observation 901620cb-afb8-4703-a1ab-902341f9eb23 · outbound

This paper cites MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models MiniLM: Deep Self-Attention Distillation for Task-Agnostic Compression of Pre-Trained Transformers

Reference 38

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unresolved
no resolver link, observed 2026-08-07T12:03:43.526793Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:43.526793Z digest=sha256:8a4e29de91bd5f055212551727c6e4775b1150645992d3443386ff5a11186780

Observation 906da04e-9014-4a49-88c8-1c8b38ae7e8a · outbound

This paper cites Beyond the Limits: A Survey of Techniques to Extend the Context Length in Large Language Models.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Beyond the Limits: A Survey of Techniques to Extend the Context Length in Large Language Models

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T12:03:43.604108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:43.604108Z digest=sha256:d662582b67d39f90787404f3d4cb28d6e7e0038d4eaf35892660d234cf459306

Observation 31f8521d-a5be-4c68-a60d-6dffdfe9b143 · outbound

This paper cites an unresolved cited work.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Unresolved cited work

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T12:03:43.685649Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:43.685649Z digest=sha256:36ce94e6c8aadc5a11b6f6a31207072c5c6546379e48293c337103db379c610b

Observation 7347e518-9724-42bb-8e9d-a4b07c2fe652 · outbound

This paper cites Efficient Streaming Language Models with Attention Sinks.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Efficient Streaming Language Models with Attention Sinks

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T12:03:43.762036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:43.762036Z digest=sha256:f8b844b9321e646d0078d0274549a425aee8a2d394a2454e8a3357661ca2f3e9

Observation d238ecb2-aae5-4a22-bd50-946d0b93d14a · outbound

This paper cites Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Contrastive Preference Optimization: Pushing the Boundaries of LLM Performance in Machine Translation

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T12:03:43.858520Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:43.858520Z digest=sha256:e2e3a33ac945d1a08728e210cae07614d9414ce58d243fd60586f75c11b70bca

Observation 9ef6671b-e7cc-4236-bddd-27a7b383bd8e · outbound

This paper cites an unresolved cited work.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Unresolved cited work

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-07T12:03:43.944679Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:43.944679Z digest=sha256:79299c5fac05b5395f35149fd7b94166561b120a0dacc3a14b928fae37ab4971

Observation c1659a60-8da7-4d04-9e93-768854a710ef · outbound

This paper cites ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T12:03:44.019447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:44.019447Z digest=sha256:1d994346dd4e99ab7d9dce8b3d5c28a476a8e660749128e9fb4350c5df777829

Observation 5a391e87-dd8c-425e-9d04-64f02ef6544f · outbound

This paper cites an unresolved cited work.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Unresolved cited work

Reference 45

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unresolved
no resolver link, observed 2026-08-07T12:03:44.111117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:44.111117Z digest=sha256:cddf56f94a3da37b21506201b510944a17bec15bb2e7b9ea2db1195b4f259c1f

Observation 75fd645c-e007-4b07-8a7d-a50a6b0da8d7 · outbound

This paper cites Hashimoto.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Hashimoto

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-07T12:03:44.189639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:44.189639Z digest=sha256:7ca3bcef08d70cf137c28f0eba8970f223a4e376721c43c19f0119ddb54cbb72

Observation 98833a16-6a51-40ea-a0b6-29e12946d327 · outbound

This paper cites H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models H$_2$O: Heavy-Hitter Oracle for Efficient Generative Inference of Large Language Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T12:03:44.277381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:44.277381Z digest=sha256:2dbfdd52077d8938735fd7462cdd0362ad0f3dc7a9947dbe4b59d127ba1d3135

Observation a4e8b44a-0512-4071-86a0-0c167fb7fd0b · outbound

This paper cites Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Reference 48

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unresolved
no resolver link, observed 2026-08-07T12:03:44.341997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:44.341997Z digest=sha256:e69148c2cd9a76c978a468c578a2fcca6b7f4fe5af16c428043759f0c40ef508

Observation f7735807-e57b-43c6-a989-f0f1be7d2bde · outbound

This paper cites online" 'onlinestring :=.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models online" 'onlinestring :=

Reference 49

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unresolved
no resolver link, observed 2026-08-07T12:03:44.430643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:44.430643Z digest=sha256:b82a79b92a7a98e3b32108354a7d2b393ab59ac7f08661ad25e0f93b23347f0a

Observation bd50222d-d2cf-458a-bada-3db0e57ab4f5 · outbound

This paper cites write newline.

Dynamic Chunking and Selection for Reading Comprehension of Ultra-Long Context in Large Language Models write newline

Reference 50

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unresolved
no resolver link, observed 2026-08-07T12:03:44.519800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:03:44.519800Z digest=sha256:7b2f5474b17da13dc26454bdf1b48372366ca160a77d5eddfae8a25cad18e398

Pith citing papers

No inbound Pith citation observations are available.