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Paper Citation Record · LEDGER

Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 19 inbound Pith citation observations for arXiv:2401.17377.

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

pith.paper-citation-record.v1
2401.17377 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 19 of 19 standing notices

One-hop event checks from named stored sources.

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

measured 19 of 19 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T20:56:23.009766Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T13:28:19.272629Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 98fe0eaf-9983-4524-9b4a-58990c1f93f1 · inbound

Theoretical Benefit and Limitation of Diffusion Language Model cites this paper.

Theoretical Benefit and Limitation of Diffusion Language Model Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T20:56:23.009766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T20:56:23.009766Z digest=sha256:0f290a69721efb42e3ec9cfac51e2986c5265615504e5306b1ddf0821958ae06

Observation f4c6fef2-e7be-4481-bff0-f80443ce7a4a · inbound

Diagnosing our datasets: How does my language model learn clinical information? cites this paper.

Diagnosing our datasets: How does my language model learn clinical information? Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T15:29:07.971245Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T15:29:07.971245Z digest=sha256:0befbdd18060a8fc421f88a2f997963b452cfc6e2e84668acec8e891c4a54013

Observation 0b49b587-96f2-4f1b-a88e-93b2a2dbd0fe · inbound

ScienceMeter: Tracking Scientific Knowledge Updates in Language Models cites this paper.

ScienceMeter: Tracking Scientific Knowledge Updates in Language Models Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T12:34:43.877443Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:34:43.877443Z digest=sha256:ae0092d35edd292237a02a9c027ca9f634f0052e100e01c31de5cabf93b4f921

Observation 77dc5525-1e1e-41d4-9f1d-ac100d9f1e10 · inbound

Truth over Tricks: Measuring and Mitigating Shortcut Learning in Misinformation Detection cites this paper.

Truth over Tricks: Measuring and Mitigating Shortcut Learning in Misinformation Detection Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T11:29:54.081659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:29:54.081659Z digest=sha256:f6076d3f20b0e8eb9e048a6b6f017d8fe5be1f9f6b6cf331c26df75c1d1b8515

Observation ee3b7064-fe72-48c9-b803-6fd73b01a98c · inbound

Low-Perplexity LLM-Generated Sequences and Where To Find Them cites this paper.

Low-Perplexity LLM-Generated Sequences and Where To Find Them Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T20:44:59.481034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T20:44:59.481034Z digest=sha256:e69e2181aef74e24bc9e0aa7bc799a54bd06ab586e689c5d72269bfea380d7c7

Observation e0264989-7d06-43ef-9954-c1e87a805a77 · inbound

LLM generation novelty through the lens of semantic similarity cites this paper.

LLM generation novelty through the lens of semantic similarity Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-04T07:22:06.164775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:22:06.164775Z digest=sha256:64289a1e8b766b503468b72062e1d3b06e684997d3b7de234f010753eccc31fb

Observation 6d2cb6ed-8285-4e64-b0a6-0d84ef90e5ab · inbound

NGM: A Plug-and-Play Training-Free Memory Module for LLMs cites this paper.

NGM: A Plug-and-Play Training-Free Memory Module for LLMs Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 29

Resolution
metadata mismatch
arxiv_id, observed 2026-05-19T20:52:46.358916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-19T20:47:50.356747Z digest=sha256:ef825e7106e1de8c6fad63bcd352f23d469023c75237dbaab4fd8455514b93d9

Observation 7885334d-0634-415e-a50d-74f0de29878c · inbound

Memory Grafting: Scaling Language Model Pre-training via Offline Conditional Memory cites this paper.

Memory Grafting: Scaling Language Model Pre-training via Offline Conditional Memory Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 32

Resolution
verified exact
arxiv_id, observed 2026-05-21T05:49:40.790156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-21T05:49:14.789955Z digest=sha256:611cf1338dc1f583d5867afe774ebcb700fa58af6e419693a86fb56759650b6e

Observation 4903d2a1-f366-4426-8700-429d15c6ce17 · inbound

PoisonForge: Task-Level Targeted Poisoning Benchmark for Instruction-Tuned LLMs cites this paper.

PoisonForge: Task-Level Targeted Poisoning Benchmark for Instruction-Tuned LLMs Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-25T04:40:23.735624Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-25T04:38:18.169546Z digest=sha256:13c2ae4d317a93585c744669476edd7e3435f9d418820bad131fd1ea2c36cf7d

Observation 95c4339e-860a-4d1d-b6ed-9cabbabf4f52 · inbound

Verifiable Rewards Beyond Math and Code: Lightweight Corpus-Grounded Process Supervision for Factual Question Answering cites this paper.

Verifiable Rewards Beyond Math and Code: Lightweight Corpus-Grounded Process Supervision for Factual Question Answering Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T08:03:14.375987Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-29T07:58:00.374310Z digest=sha256:c79ccad7b7eced7c065e206150f4f150e0179458cdcb9eaab8281548b12d7ea4

Observation 9ab3db6e-2dc1-449e-b5e2-2baf5f308754 · inbound

Measuring, Localizing, and Ablating Alignment Signatures in LLMs cites this paper.

Measuring, Localizing, and Ablating Alignment Signatures in LLMs Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T08:13:15.500654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-29T08:07:39.515963Z digest=sha256:afa00dfea5cabd02afb033e74fcf356b6ec5f2a702fb4f3616c37015a585f71a

Observation 9345edaf-b381-4a7e-86ca-e29d610a96d2 · inbound

Rethinking the Idiomaticity Decomposability Hypothesis: Evidence from Distributional Learning cites this paper.

Rethinking the Idiomaticity Decomposability Hypothesis: Evidence from Distributional Learning Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 38

Resolution
verified exact
arxiv_id, observed 2026-07-02T03:26:29.081382Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T10:04:41.040033Z digest=sha256:6b8e1a44038458dce094f9184bfbbd8b21fe5116670e52b4e61ce256a6fd7fe0

Observation 87c95ccd-e2da-41ce-88ff-a065adb7f8c2 · inbound

LLMs Can Leak Training Data But Do They Want To? A Propensity-Aware Evaluation of Memorization in LLMs cites this paper.

LLMs Can Leak Training Data But Do They Want To? A Propensity-Aware Evaluation of Memorization in LLMs Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-07-02T12:56:57.456684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T01:40:53.284131Z digest=sha256:6a76bbbc110b58629acc65f34e7f94f19de06dd4ac835f0ebd8dfdc8ee4519c0

Observation c4c5924d-cb7e-4b98-8aa4-5fbadff9a338 · inbound

Principles and Practice of Deep Representation Learning: or a Mathematical Theory of Memory cites this paper.

Principles and Practice of Deep Representation Learning: or a Mathematical Theory of Memory Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 57

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T11:46:55.372106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-28T03:07:52.730713Z digest=sha256:ce18f635c21481a6f7ca65e03786071e221ef6e4ec8d920cddb078d05cd03dc9

Observation a894f81e-d7df-40fb-91f9-4385addd4d77 · inbound

The Holistic Storage of Verb+Up Phrases in Text-based and Audio-based Language Models cites this paper.

The Holistic Storage of Verb+Up Phrases in Text-based and Audio-based Language Models Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-04T04:48:46.467025Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T04:48:46.467025Z digest=sha256:4c7dd901024a13f7d87fc05e11540e170faa30128e70b1eec4290b1e4c08e7db

Observation ad14430f-bda4-4c04-91e2-798ed42876c0 · inbound

RELIANCE: Curating and Evaluating Reproductive Health Information on Social Media cites this paper.

RELIANCE: Curating and Evaluating Reproductive Health Information on Social Media Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-07-03T13:28:19.274103Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-27T07:56:36.600805Z digest=sha256:863b3274d882034a3fc8f8dcb2daa0ead1f0594703383960dace226b5dc4ea3c

Observation e112678e-5070-4c27-b55f-1d63531ef80c · inbound

Frontier AI performance across the business disciplines: a case-grounded benchmark of knowledge work and analytical reasoning cites this paper.

Frontier AI performance across the business disciplines: a case-grounded benchmark of knowledge work and analytical reasoning Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-01T21:31:54.359771Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:31:54.359771Z digest=sha256:09661784f7f3692c574cb430e2851caa34e2d36cdabe520204ff31377bf9f8b0

Observation 10b2918e-3b25-4bca-a52b-c75663e80698 · inbound

Frontier AI performance across the business disciplines: a case-grounded benchmark of knowledge work and analytical reasoning cites this paper.

Frontier AI performance across the business disciplines: a case-grounded benchmark of knowledge work and analytical reasoning Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-03T00:49:50.919601Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T00:49:50.919601Z digest=sha256:b54355d78d877925ff261614e154c48fe1828d321b0ee40dc67b4e1a000bf229

Observation c3ed716b-bcc2-48f3-b9af-b5b5417049b8 · inbound

When Trivia Is Not Trivial: Everyday Knowledge Failures in Multilingual LLMs cites this paper.

When Trivia Is Not Trivial: Everyday Knowledge Failures in Multilingual LLMs Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-01T07:29:01.914639Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T07:29:01.914639Z digest=sha256:186266561043091c22cd2cadfe1dadafad0a9985869522cd500738d734caf132