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Paper Citation Record · LEDGER

Auto-Patching: Enhancing Multi-Hop Reasoning in Language Models

As of 8 August 2026, this Paper Citation Record lists 9 of 9 outbound references and 0 inbound Pith citation observations for arXiv:2506.00483.

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

pith.paper-citation-record.v1
2506.00483 v1

Coverage vector

measured 9 of 9 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:09:48.834696Z

measured 9 of 9 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

9 of 9 outbound references displayed

  • verified exact0
  • verified fuzzy4
  • unresolved5
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1b3f63c9-ef2b-43f2-b671-c29d56bd1e41 · outbound

This paper cites an unresolved cited work.

Auto-Patching: Enhancing Multi-Hop Reasoning in Language Models Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-07T12:09:49.901272Z

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.

source=arxiv_source observed=2026-08-07T12:09:48.114810Z digest=sha256:42f04957d83d12dc905f00890f30d386d078fc2d4341ebefd98f79e369c6bcc8

Observation 6f0722d5-b4ff-422e-8d42-b7c596c3dee7 · outbound

This paper cites Question answering by reasoning across documents with graph convolutional networks.

Auto-Patching: Enhancing Multi-Hop Reasoning in Language Models Question answering by reasoning across documents with graph convolutional networks

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T12:09:48.194798Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:48.194798Z digest=sha256:7ca88890a2abfff8d65dda3776f7182d736fc03d3160fcf0e7cf641fd50fee9d

Observation 9e5446f6-3dbf-45d2-a02e-2e9a090bc2dd · outbound

This paper cites Musique: A large-scale dataset for music recommendation with user-centric information, 2021.

Auto-Patching: Enhancing Multi-Hop Reasoning in Language Models Musique: A large-scale dataset for music recommendation with user-centric information, 2021

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:09:49.643014Z

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.

source=arxiv_source observed=2026-08-07T12:09:48.278239Z digest=sha256:5ae0ef82ba7aa400d0d3a36d4d39f28f0e53d6f2baf2798dce6eaa4199faaa58

Observation acafeb63-840c-4b0a-a1f7-075737607ca5 · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Auto-Patching: Enhancing Multi-Hop Reasoning in Language Models Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:09:49.426897Z

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.

source=arxiv_source observed=2026-08-07T12:09:48.373698Z digest=sha256:99341f91d5775384a841f932272569444b1b20df7e68e9d4672b91f7988a587f

Observation 9478e2ab-558d-4ed3-a314-e2de38f6df50 · outbound

This paper cites Patchscopes: A unifying framework for inspecting hidden representations of language models, 2024.

Auto-Patching: Enhancing Multi-Hop Reasoning in Language Models Patchscopes: A unifying framework for inspecting hidden representations of language models, 2024

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:09:49.262333Z

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.

source=arxiv_source observed=2026-08-07T12:09:48.479008Z digest=sha256:f66a6cb7a8302eddcc818d56bd4bd26200eb30655e5ad629c6764cc9c3bc5b88

Observation 2e3d85b8-401b-44ce-80e5-27ac6f0e55c1 · outbound

This paper cites Llama: Open and efficient foundation language models, 2023.

Auto-Patching: Enhancing Multi-Hop Reasoning in Language Models Llama: Open and efficient foundation language models, 2023

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T12:09:48.594594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:48.594594Z digest=sha256:a320051f5eb1df17c249a67c23f000375e87299f74505dc1ca8cdee07081b34a

Observation 1ed0e472-7155-46af-bedd-c142de3b059d · outbound

This paper cites Towards understanding chain-of-thought prompting: An empirical study of what matters.

Auto-Patching: Enhancing Multi-Hop Reasoning in Language Models Towards understanding chain-of-thought prompting: An empirical study of what matters

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T12:09:48.684699Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:48.684699Z digest=sha256:1b83befdd4184885a2da34da0e782e7327c2fb63b6c1af74a5678469b47506ec

Observation 620a580f-c4ee-4551-9959-e2088b6547e3 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models, 2023.

Auto-Patching: Enhancing Multi-Hop Reasoning in Language Models Chain-of-thought prompting elicits reasoning in large language models, 2023

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T12:09:48.757173Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:09:48.757173Z digest=sha256:02e2383e72019cb227d5e8e55ada2ba5316b41fb3a126d17f4001f5ac99fc7c2

Observation f3055168-eb1f-4994-b832-c05919a3fbcc · outbound

This paper cites Automatic chain of thought prompting in large language models, 2022.

Auto-Patching: Enhancing Multi-Hop Reasoning in Language Models Automatic chain of thought prompting in large language models, 2022

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:09:49.084958Z

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.

source=arxiv_source observed=2026-08-07T12:09:48.834696Z digest=sha256:9810d0e93fdaaab61494b7c03ad91914282310388306f1832ee6ba5ca0bc0ed7

Pith citing papers

No inbound Pith citation observations are available.