Paper Citation Record · LEDGER

One for All: Update Parameterized Knowledge Across Multiple Models

As of 8 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2506.00817.

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

pith.paper-citation-record.v1
2506.00817 v1

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:02:18.075413Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

17 of 17 outbound references displayed

verified exact0
verified fuzzy1
unresolved16
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4ebc940b-e73b-40a0-a929-1602868afb73 · outbound

This paper cites Trends in Integration of Knowledge and Large Language Models: A Survey and Taxonomy of Methods, Benchmarks, and Applications.

One for All: Update Parameterized Knowledge Across Multiple Models Trends in Integration of Knowledge and Large Language Models: A Survey and Taxonomy of Methods, Benchmarks, and Applications

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:17.137527Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c59b5b7-e535-43fb-abff-a69be421bfb1 · outbound

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

One for All: Update Parameterized Knowledge Across Multiple Models A Survey on Hallucination in Large Language Models: Principles, Taxonomy, Challenges, and Open Questions

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:17.246917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 11edae38-5819-4987-b16c-6c22dc203e40 · outbound

This paper cites Routing to the Expert: Efficient Reward-guided Ensemble of Large Language Models.

One for All: Update Parameterized Knowledge Across Multiple Models Routing to the Expert: Efficient Reward-guided Ensemble of Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:17.457767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ad6b2c80-d023-4ff1-800f-dd8a9864cfcb · outbound

This paper cites Meta AI Blog (accessed 2024–04–20).

One for All: Update Parameterized Knowledge Across Multiple Models Meta AI Blog (accessed 2024–04–20)

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:02:18.623187Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 61af6407-8c15-428c-b647-ff0bca05a451 · outbound

This paper cites Massive Editing for Large Language Models via Meta Learning.

One for All: Update Parameterized Knowledge Across Multiple Models Massive Editing for Large Language Models via Meta Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:17.675366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 754d755b-3df8-4b50-b4ac-e4dce5e7f9c4 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

One for All: Update Parameterized Knowledge Across Multiple Models Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:17.743522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation aadc9385-a682-4d8a-908e-5603d387cd2d · outbound

This paper cites Fusing Models with Complementary Expertise.

One for All: Update Parameterized Knowledge Across Multiple Models Fusing Models with Complementary Expertise

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:17.781944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b26a811-6a01-4365-a533-1ecc81497aca · outbound

This paper cites Bridging the Gap between Different Vocabularies for LLM Ensemble.

One for All: Update Parameterized Knowledge Across Multiple Models Bridging the Gap between Different Vocabularies for LLM Ensemble

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:17.817081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b564123f-3a43-4a4e-9b2f-a938c9c709a0 · outbound

This paper cites Editing Large Language Models: Problems, Methods, and Opportunities.

One for All: Update Parameterized Knowledge Across Multiple Models Editing Large Language Models: Problems, Methods, and Opportunities

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:17.911406Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 024585ea-e184-4294-a088-1067809d069b · outbound

This paper cites Determine-Then-Ensemble: Necessity of Top-k Union for Large Language Model Ensembling.

One for All: Update Parameterized Knowledge Across Multiple Models Determine-Then-Ensemble: Necessity of Top-k Union for Large Language Model Ensembling

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:17.969906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38a22920-e678-4d0b-bc9b-30258a91d1b7 · outbound

This paper cites How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances.

One for All: Update Parameterized Knowledge Across Multiple Models How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:18.031020Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44a9400c-26d2-464a-ad22-fb91b02eed8f · outbound

This paper cites Investigating and Mitigating the Multimodal Hallucination Snowballing in Large Vision-Language Models.

One for All: Update Parameterized Knowledge Across Multiple Models Investigating and Mitigating the Multimodal Hallucination Snowballing in Large Vision-Language Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:18.075413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7a590695-6608-4427-ba49-c6ce466928f0 · outbound

This paper cites Zero-Shot Relation Extraction via Reading Comprehension.

One for All: Update Parameterized Knowledge Across Multiple Models Zero-Shot Relation Extraction via Reading Comprehension

Reference 2017

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:17.299880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 963c99f7-a257-4432-b45d-59b87c887ceb · outbound

This paper cites Fast Model Editing at Scale.

One for All: Update Parameterized Knowledge Across Multiple Models Fast Model Editing at Scale

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:17.578120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17a177aa-8e33-4ec2-a1d6-95a25ba3cfcc · outbound

This paper cites GPT-4 Technical Report.

One for All: Update Parameterized Knowledge Across Multiple Models GPT-4 Technical Report

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:17.042297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e8364062-0c8d-40d9-9f6a-aeab4c572f56 · outbound

This paper cites Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in the Era of Large Language Models.

One for All: Update Parameterized Knowledge Across Multiple Models Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in the Era of Large Language Models

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:17.402063Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7169938f-24e1-447c-b0e4-b9cb21400830 · outbound

This paper cites Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced Optimization.

One for All: Update Parameterized Knowledge Across Multiple Models Improving Contextual Faithfulness of Large Language Models via Retrieval Heads-Induced Optimization

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-07T12:02:17.166537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.