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Paper Citation Record · LEDGER

Understanding the Interplay between Parametric and Contextual Knowledge for Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2410.08414.

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

pith.paper-citation-record.v1
2410.08414 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T15:03:02.697258Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-21T20:40:36.377126Z

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 94f3f7d4-0db5-4f15-a0bd-5206b888f86a · inbound

Massive Values in Self-Attention Modules are the Key to Contextual Knowledge Understanding cites this paper.

Massive Values in Self-Attention Modules are the Key to Contextual Knowledge Understanding Understanding the Interplay between Parametric and Contextual Knowledge for Large Language Models

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-09T15:03:02.697258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T15:03:02.697258Z digest=sha256:3bf7a92cbc3dff2a3306d7efb2af87b49d2268e1a0e3d942a2c5ef04c4dc2075

Observation 2f6b8b88-8861-4f05-9c91-f210d82fe01a · inbound

CryptoX : Compositional Reasoning Evaluation of Large Language Models cites this paper.

CryptoX : Compositional Reasoning Evaluation of Large Language Models Understanding the Interplay between Parametric and Contextual Knowledge for Large Language Models

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-08T18:34:26.696989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T18:34:26.696989Z digest=sha256:7af3e33f6632e0269285b63500238b90100436c3cde4a4897210425d23639565

Observation 3ed040cd-8986-4385-b60e-f88d2bf4c500 · inbound

Learning Compositional Functions with Transformers from Easy-to-Hard Data cites this paper.

Learning Compositional Functions with Transformers from Easy-to-Hard Data Understanding the Interplay between Parametric and Contextual Knowledge for Large Language Models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-07T12:46:34.394535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:46:34.394535Z digest=sha256:aafa6aaaf66f3c5f40dd4e35d2d184479e660aa2fe55e1405838952a098145a2

Observation 6145fd55-f395-4c34-b95a-c61df54d0b18 · inbound

Deep sequence models tend to memorize geometrically; it is unclear why cites this paper.

Deep sequence models tend to memorize geometrically; it is unclear why Understanding the Interplay between Parametric and Contextual Knowledge for Large Language Models

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-21T20:40:36.379581Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-21T20:38:18.005002Z digest=sha256:7d7e3e51380f60731fd61afb7657df0ed44af2a8e062cad375a583e6f8a52281

Observation a34e7b1e-958e-489b-9e2b-51f1f68581f7 · inbound

When LLMs Lag Behind: Knowledge Conflicts from Evolving APIs in Code Generation cites this paper.

When LLMs Lag Behind: Knowledge Conflicts from Evolving APIs in Code Generation Understanding the Interplay between Parametric and Contextual Knowledge for Large Language Models

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T08:11:01.430620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-10T16:48:11.705307Z digest=sha256:260fc74b5137e46528c0b6e5f4197931010b22f9db2fa8b33f0376c0dbc1be03

Observation 6ac0a1f3-3a5b-47e9-a34f-3d7207d702b5 · inbound

Evaluating Retrieval-Augmented Generation for Explainable Malware Analysis cites this paper.

Evaluating Retrieval-Augmented Generation for Explainable Malware Analysis Understanding the Interplay between Parametric and Contextual Knowledge for Large Language Models

Reference 10

Resolution
metadata mismatch
arxiv_id, observed 2026-05-09T06:30:45.160554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-08T18:22:26.131883Z digest=sha256:95d3acfe5d569f89bb8ea7501a2464e4f71d9c1ba735b9d4868a8e9c3086ddbb

Observation 8410d7fe-4bec-462c-b312-8d83b0a52e2a · inbound

Three Regimes of Context-Parametric Conflict: A Predictive Framework and Empirical Validation cites this paper.

Three Regimes of Context-Parametric Conflict: A Predictive Framework and Empirical Validation Understanding the Interplay between Parametric and Contextual Knowledge for Large Language Models

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-13T02:02:06.510337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-05-13T01:59:21.095135Z digest=sha256:50cb213e60f934ac34f0e1723c7780b3dabba02b7397b215cd460bf0cee78d1c