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Paper Citation Record · LEDGER

Benchmarking Large Language Models in Retrieval-Augmented Generation

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2309.01431.

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

pith.paper-citation-record.v1
2309.01431 v2

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 2026-08-07T06:34:17.273281+00:00

measured 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:09:33.958225Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T15:59:56.182550Z

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 33845667-6395-494e-8b4e-83727b5c8f1e · inbound

Retrieval-Augmented Generation for Large Language Models: A Survey cites this paper.

Retrieval-Augmented Generation for Large Language Models: A Survey Benchmarking Large Language Models in Retrieval-Augmented Generation

Reference 167

Resolution
verified exact
arxiv_id, observed 2026-05-24T05:13:56.515375Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-24T05:10:25.171044Z digest=sha256:6428d7774cbff939f2822f0b6876e753c40c4c7aad4433edded7cf74d0bddfd7

Observation e212d72d-dc8a-4fab-b5a0-8479cbd48790 · inbound

MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries cites this paper.

MultiHop-RAG: Benchmarking Retrieval-Augmented Generation for Multi-Hop Queries Benchmarking Large Language Models in Retrieval-Augmented Generation

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-15T13:54:19.677200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-15T13:54:19.264893Z digest=sha256:c3218d0dc93a4c1871acc441b2effb948561f1839f0eda172b34af5e64de134d

Observation ff75edf6-ce90-4e86-8e1d-97709f4fc640 · inbound

FinS-Pilot: A Benchmark for Online Financial RAG System cites this paper.

FinS-Pilot: A Benchmark for Online Financial RAG System Benchmarking Large Language Models in Retrieval-Augmented Generation

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T12:09:33.958225Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:09:33.958225Z digest=sha256:17b244affdc9de9a9072b68ca9dcb9bba3be4dd34b4446693a44252a1e2112cc

Observation 1c0023b4-c832-424b-a09d-244b1892ae4c · inbound

Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions cites this paper.

Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions Benchmarking Large Language Models in Retrieval-Augmented Generation

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T05:42:30.832377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:42:30.832377Z digest=sha256:f37b0c03e8f43d70e03990b82597e3bdfd11be4c36615e11adcf1a356ede6618

Observation b07cf664-b701-4a39-a7aa-72b453789ac8 · inbound

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation cites this paper.

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation Benchmarking Large Language Models in Retrieval-Augmented Generation

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:50.354323Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:50.354323Z digest=sha256:e9dd0bd44d22fb0ca516fc5bd5d5cc990d9b190e515acd1a9148551d5bab6f28

Observation 14f09286-b735-4ce0-8edd-f3ddb910014e · inbound

Investigating the Robustness of Retrieval-Augmented Generation at the Query Level cites this paper.

Investigating the Robustness of Retrieval-Augmented Generation at the Query Level Benchmarking Large Language Models in Retrieval-Augmented Generation

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T18:55:54.682167Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:55:54.682167Z digest=sha256:a3480fe4a5a945b4de85dd45a8fd7e37eff7b522ab0509cd2869b249b54aafb8

Observation 858b08f1-d929-47a5-bf18-0706f073017e · inbound

PRGB Benchmark: A Robust Placeholder-Assisted Algorithm for Benchmarking Retrieval-Augmented Generation cites this paper.

PRGB Benchmark: A Robust Placeholder-Assisted Algorithm for Benchmarking Retrieval-Augmented Generation Benchmarking Large Language Models in Retrieval-Augmented Generation

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T14:47:45.647885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:47:45.647885Z digest=sha256:7188fa7cc7b934fb3d70182e2f37c8b583a44ad61374cf0c2cd3425921bc43f1

Observation 9e88a9eb-a9f0-4166-b1c5-21f292897a40 · inbound

VLegal-Bench: Cognitively Grounded Benchmark for Vietnamese Legal Reasoning of Large Language Models cites this paper.

VLegal-Bench: Cognitively Grounded Benchmark for Vietnamese Legal Reasoning of Large Language Models Benchmarking Large Language Models in Retrieval-Augmented Generation

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-16T21:38:34.169422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-16T21:36:24.376401Z digest=sha256:b18adebe7645e260457e0036384ab937c41512fcc292e553328b5f72afa8939f

Observation 45e1bd51-d266-44b2-bcc8-409a45e9d33f · inbound

Beyond the Parameters: A Technical Survey of Contextual Enrichment in Large Language Models: From In-Context Prompting to Causal Retrieval-Augmented Generation cites this paper.

Beyond the Parameters: A Technical Survey of Contextual Enrichment in Large Language Models: From In-Context Prompting to Causal Retrieval-Augmented Generation Benchmarking Large Language Models in Retrieval-Augmented Generation

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-13T20:03:12.194813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-13T20:02:02.300824Z digest=sha256:dd5e58f26c84bfa0cf08571257b3e887d96f8f4f7b900b8c8a781243c1cb172c

Observation 74d8f0b9-40fe-4346-9836-72879ab207eb · inbound

An Annotation Scheme and Classifier for Personal Facts in Dialogue cites this paper.

An Annotation Scheme and Classifier for Personal Facts in Dialogue Benchmarking Large Language Models in Retrieval-Augmented Generation

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-12T05:51:25.334681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-12T04:53:28.491889Z digest=sha256:d58a27a803b0c47fb6e1961352f696e847a16d569723c719631bcee04b327abb

Observation c6d22939-05f9-4a1a-8605-c567d774fe9e · inbound

ProvenAI: Provenance-Native Traces of Evidence in Generated Answers cites this paper.

ProvenAI: Provenance-Native Traces of Evidence in Generated Answers Benchmarking Large Language Models in Retrieval-Augmented Generation

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-07-04T15:59:56.184397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T01:13:29.166367Z digest=sha256:7ab1093a78c0fcefbd1d1dbb6da4d71fef33e914fa45af553a7a1c48b50db788

Observation 2f416189-c012-435d-aa98-57777ae7b434 · inbound

Always-OnAgents:A Survey of Persistent Memory, State, and Governance in LLMAgents cites this paper.

Always-OnAgents:A Survey of Persistent Memory, State, and Governance in LLMAgents Benchmarking Large Language Models in Retrieval-Augmented Generation

Reference 5

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T15:15:48.392474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T03:44:51.320606Z digest=sha256:d4384a7efaec4e3f6f33a296bfe9c0e9cbe3268a3c76b20406c084cd81548d7d