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 20 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 20 of 20 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 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:17:33.631642Z

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 9c9120e5-9cf8-442f-b561-0e83a97bb372 · inbound

Can Large Language Models Understand Preferences in Personalized Recommendation? cites this paper.

Can Large Language Models Understand Preferences in Personalized Recommendation? Infini-gram: Scaling Unbounded n-gram Language Models to a Trillion Tokens

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-10T16:17:33.631642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.