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Paper Citation Record · LEDGER

A Method for Building Large Language Models with Predefined KV Cache Capacity

As of 13 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2411.15785.

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

pith.paper-citation-record.v1
2411.15785 v2

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:56:42.441755Z

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

9 of 9 outbound references displayed

  • verified exact0
  • verified fuzzy5
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 356f7a31-e04e-43f1-a230-a83a23a041d1 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

A Method for Building Large Language Models with Predefined KV Cache Capacity BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-12T13:56:42.410688Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:56:42.410688Z digest=sha256:db5a3f900ac037277d1a758d4870e0c9e5e80845da6a1b15f64f347a90a7f801

Observation 7b184d4e-cb4b-4049-9ca6-90a5f28c98d0 · outbound

This paper cites Language models are unsupervised multitask learners.

A Method for Building Large Language Models with Predefined KV Cache Capacity Language models are unsupervised multitask learners

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:56:42.587020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:56:42.415624Z digest=sha256:eb08120f21fd723261671e0885fc798f55c5ca7bb62529f0c16ef2259ed238d0

Observation 31c6e77b-281b-4c84-b8ac-7043e3678098 · outbound

This paper cites Attention is all you need.

A Method for Building Large Language Models with Predefined KV Cache Capacity Attention is all you need

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:56:42.573088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:56:42.419707Z digest=sha256:47a41ac5e308d2347efc3fce4a963c522bfb1167322ef7e409d30b7c58c02b2b

Observation 11d7c036-3fe8-4f77-a745-5cac2e497bf2 · outbound

This paper cites Efficient streaming language models with attention sinks.

A Method for Building Large Language Models with Predefined KV Cache Capacity Efficient streaming language models with attention sinks

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:56:42.559847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:56:42.423801Z digest=sha256:c2c33a6446204b6ff474cd0b39290ae097387b86f181ace2f5728d8f2220b4c7

Observation 3e6ff11f-cb84-443f-babb-e88c3cb0d4a8 · outbound

This paper cites Get more with less: Synthesizing recurrence with kv cache compression for efficient llm inference.

A Method for Building Large Language Models with Predefined KV Cache Capacity Get more with less: Synthesizing recurrence with kv cache compression for efficient llm inference

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:56:42.546702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:56:42.427287Z digest=sha256:215106d0474717176074e0d34c2b5141bba63cfeb9e73d3dcca980c844c0a95c

Observation 3fc328af-fea1-426e-9ceb-7b1af717e7e3 · outbound

This paper cites Neural Turing Machines.

A Method for Building Large Language Models with Predefined KV Cache Capacity Neural Turing Machines

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-12T13:56:42.430892Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:56:42.430892Z digest=sha256:7e0e2068fb230ea8bd76c21b0c2aa535cbf0bf9114b01076df312fb384b3f2b2

Observation 8cdcb0a3-14b6-4412-a6a6-abefa1f74fde · outbound

This paper cites Common crawl: A corpus for web-scale information extraction.

A Method for Building Large Language Models with Predefined KV Cache Capacity Common crawl: A corpus for web-scale information extraction

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-12T13:56:42.531703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:56:42.434864Z digest=sha256:d57f7934d301e46ca5e6330ac8cab364d8f70c81c007c40c2b67976f4b60c8b5

Observation 7b1c6afa-01b8-48f1-955f-578db0189259 · outbound

This paper cites Threshold solutions for the intercritical inhomogeneous NLS.

A Method for Building Large Language Models with Predefined KV Cache Capacity Threshold solutions for the intercritical inhomogeneous NLS

Reference 8

Resolution
metadata mismatch
local_arxiv, observed 2026-08-12T13:56:42.491376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-12T13:56:42.438279Z digest=sha256:86785a92f487e9d96a66c750d4bd53dea64aacc5e7fcf3bd04e0a0e8b2856891

Observation 0a3369a6-0046-40e0-b196-8e6875d5b6ca · outbound

This paper cites The Pile: An 800GB Dataset of Diverse Text for Language Modeling.

A Method for Building Large Language Models with Predefined KV Cache Capacity The Pile: An 800GB Dataset of Diverse Text for Language Modeling

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-12T13:56:42.441755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:56:42.441755Z digest=sha256:939cfdbb30f3bcc67070122f23efa756698fa4b9e69e0868a5fc3a8bc9c58c62

Pith citing papers

No inbound Pith citation observations are available.