Pith. sign in

Paper Citation Record · LEDGER

In-context Pretraining: Language Modeling Beyond Document Boundaries

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2310.10638.

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

pith.paper-citation-record.v1
2310.10638 v6

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T13:07:59.528029Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

3
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 27d3c865-0e18-47fb-8375-7ac74397b58b · inbound

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions cites this paper.

A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions In-context Pretraining: Language Modeling Beyond Document Boundaries

Reference 289

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T02:47:07.704647Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-13T02:46:26.957539Z digest=sha256:1a141fcb4b0d54554669d32c5a76e57aeb694d2f1d037894dc8a0e548c842b4f

Observation c02eedc5-d600-41cb-952d-a5757ab61743 · inbound

The Faiss library cites this paper.

The Faiss library In-context Pretraining: Language Modeling Beyond Document Boundaries

Reference 73

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T01:47:20.107090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-12T01:47:19.947054Z digest=sha256:a4eaf47613f7a7f13dadf42175147e121ac8b8f9e59895e3a29690a476599ab1

Observation 7e1d40e7-9587-48a7-873c-6d4de01fa1ef · inbound

Hallucination is Inevitable: An Innate Limitation of Large Language Models cites this paper.

Hallucination is Inevitable: An Innate Limitation of Large Language Models In-context Pretraining: Language Modeling Beyond Document Boundaries

Reference 62

Resolution
verified exact
arxiv_id, observed 2026-05-15T20:38:43.593860Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-15T20:38:43.411206Z digest=sha256:b9232ea1ec93228f3ea039cf01831a38d4eaaf5df0611be028c30356531c4165

Observation 1a7cc606-b14a-4375-90d6-6091c6221dd2 · inbound

In-Context Deep Learning via Transformer Models cites this paper.

In-Context Deep Learning via Transformer Models In-context Pretraining: Language Modeling Beyond Document Boundaries

Reference 2017

Resolution
unresolved
no resolver link, observed 2026-08-12T13:07:59.528029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T13:07:59.528029Z digest=sha256:6035911744da9be9c5e5c52500643334744b3fe66e20891125a8b2c7b551289f

Observation 51b64677-5aa3-4de8-b7f2-c306e339f586 · inbound

Yi-Lightning Technical Report cites this paper.

Yi-Lightning Technical Report In-context Pretraining: Language Modeling Beyond Document Boundaries

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-12T04:34:12.094024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T04:34:12.094024Z digest=sha256:6f0804079ee44e587620b25ee74334e5e0d05ba3381233291a5566abdc366ccd

Observation 5aa6f4d4-9dc3-4eca-be91-bea308aa08ed · inbound

CPRM: A LLM-based Continual Pre-training Framework for Relevance Modeling in Commercial Search cites this paper.

CPRM: A LLM-based Continual Pre-training Framework for Relevance Modeling in Commercial Search In-context Pretraining: Language Modeling Beyond Document Boundaries

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-12T04:34:14.626194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T04:34:14.626194Z digest=sha256:3b2649091b71e26d75e069b4018537debd21e507563add0060862a5d4867a75b

Observation d8672f83-f6bf-4502-baf1-c61c0f9622df · inbound

NExtLong: Toward Effective Long-Context Training without Long Documents cites this paper.

NExtLong: Toward Effective Long-Context Training without Long Documents In-context Pretraining: Language Modeling Beyond Document Boundaries

Reference 84

Resolution
unresolved
no resolver link, observed 2026-08-10T16:52:49.832757Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-10T16:52:49.832757Z digest=sha256:aac8858b4794ed0e81e1572c00eb02eb93b0c786384e410ce9fe3a9d877d2da0

Observation 9e06abd8-7c70-49a0-a9d6-7203803adab8 · inbound

LongMagpie: A Self-synthesis Method for Generating Large-scale Long-context Instructions cites this paper.

LongMagpie: A Self-synthesis Method for Generating Large-scale Long-context Instructions In-context Pretraining: Language Modeling Beyond Document Boundaries

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T15:08:02.498031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:08:02.498031Z digest=sha256:8ce74230d221ee73ddb38dbad1f0099124814538450777186e7b8cf69713a80e

Observation 1e878c9d-0e19-408c-b586-d0bd9fa81cb3 · inbound

DICE: Dynamic In-Context Example Selection in LLM Agents via Efficient Knowledge Transfer cites this paper.

DICE: Dynamic In-Context Example Selection in LLM Agents via Efficient Knowledge Transfer In-context Pretraining: Language Modeling Beyond Document Boundaries

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-06T10:43:49.403131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T10:43:49.403131Z digest=sha256:7f8373dbd282311da5ac8f06c6b63dad6d8b7c8ab4ba050625655dcfe2103a4c

Observation 7bbd3cda-c4b5-453d-9aa4-d1ec227040c4 · inbound

HSAP: A Hierarchical Sequence-aware Parallelism for Hybrid-Context Generative Models cites this paper.

HSAP: A Hierarchical Sequence-aware Parallelism for Hybrid-Context Generative Models In-context Pretraining: Language Modeling Beyond Document Boundaries

Reference 73

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T07:34:21.009272Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-06-30T07:27:34.161517Z digest=sha256:582999334d342d3f67fe8c3dd338295a1d523106cbbeff4057ecce6dc66b41f9

Observation 85929125-4fe5-429a-bffa-4b031edb86b7 · inbound

HSAP: A Hierarchical Sequence-aware Parallelism for Hybrid-Context Generative Models cites this paper.

HSAP: A Hierarchical Sequence-aware Parallelism for Hybrid-Context Generative Models In-context Pretraining: Language Modeling Beyond Document Boundaries

Reference 73

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T07:05:27.821220Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-07-01T06:58:30.817223Z digest=sha256:8e76c82264bc067285bf597bed615e65cd3117cf8414507be5a20c77e916e41a

Observation e9abcef8-18ab-41a3-a3f9-f08c92629748 · inbound

The Cost of Knowing: A Resource-Aware Protocol for Benchmarking Hallucination Beyond Static Leaderboards cites this paper.

The Cost of Knowing: A Resource-Aware Protocol for Benchmarking Hallucination Beyond Static Leaderboards In-context Pretraining: Language Modeling Beyond Document Boundaries

Reference 18

Resolution
unresolved
no resolver link, observed 2026-07-31T23:11:42.150685Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T23:11:42.150685Z digest=sha256:845dd57c29f9d477788d1ca2851a052fa01fe80514a8ae1c94bead7a3091c7b2