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Paper Citation Record · LEDGER

In-Context Retrieval-Augmented Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 28 inbound Pith citation observations for arXiv:2302.00083.

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

pith.paper-citation-record.v1
2302.00083 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 28 of 28 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 28 of 28 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T10:21:59.345421Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T03:59:32.507711Z

Reference resolution

0 of 0 outbound references displayed

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  • 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 b08fc384-7c3f-4b21-bf81-3441707ed209 · inbound

A Comprehensive Overview of Large Language Models cites this paper.

A Comprehensive Overview of Large Language Models In-Context Retrieval-Augmented Language Models

Reference 198

Resolution
verified exact
arxiv_id, observed 2026-05-19T20:28:39.624950Z

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=2026-05-19T20:28:38.900026Z digest=sha256:26b1b389e3b0e18ec9cd326febe214cf674e1a4645d6cca85495670db0bb26dc

Observation dee39435-7641-4b9b-8a78-d7eb465a5a7a · inbound

Towards General Text Embeddings with Multi-stage Contrastive Learning cites this paper.

Towards General Text Embeddings with Multi-stage Contrastive Learning In-Context Retrieval-Augmented Language Models

Reference 40

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verified exact
arxiv_id, observed 2026-05-12T03:33:45.964863Z

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=2026-05-12T03:33:45.855974Z digest=sha256:c99a641074eab4b3a9bc01ddfdbef725eefca29b4fbb8105bbd07005ef8188f7

Observation 593d3bb4-bcee-4a5e-b0a4-e7b4a0de0cb8 · inbound

DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models cites this paper.

DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models In-Context Retrieval-Augmented Language Models

Reference 85

Resolution
metadata mismatch
arxiv_id, observed 2026-05-16T13:21:24.382857Z

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=2026-05-16T13:21:24.297836Z digest=sha256:59ff7f2b7a9903ec6ecdfe7a130f4e286eb054f8fc92f33e61820b3f6b792eae

Observation d843dc59-ff63-4e79-8ef7-88f514926ef1 · inbound

Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs "Difficult" Downstream Tasks in LLMs cites this paper.

Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs "Difficult" Downstream Tasks in LLMs In-Context Retrieval-Augmented Language Models

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-24T06:34:01.079225Z

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=2026-05-24T06:33:48.456209Z digest=sha256:62292626c632f1548a6af5d56a6a085b02609561c8d50a2ff135070696723adf

Observation 5c53eb12-0177-49c5-9708-2033f8b913dc · inbound

MemGPT: Towards LLMs as Operating Systems cites this paper.

MemGPT: Towards LLMs as Operating Systems In-Context Retrieval-Augmented Language Models

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-10T12:27:29.149446Z

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=2026-05-10T12:27:29.041352Z digest=sha256:7945e0cdd017093f094b8bbdc0628dc82f2db637fb0526e477335f03a8b9d125

Observation 2cce0095-f54c-470f-838a-72745a750b31 · inbound

Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection cites this paper.

Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection In-Context Retrieval-Augmented Language Models

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-05-12T14:15:11.317713Z

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=2026-05-12T14:15:10.907921Z digest=sha256:fe453656c2851fd1c418ba84b04bae832ab82b2485ae84b1cefad4abe2923c82

Observation 64f6fc3f-105f-4c03-af33-42252bef8fcf · 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 Retrieval-Augmented Language Models

Reference 268

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T02:46:27.878655Z

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=2026-05-13T02:46:26.957539Z digest=sha256:a20b6990b2a057ea5dbf8a04ad257dcc41a52a83d6a2699905abbb355eec3fd7

Observation b9773a25-fbac-4a58-bfc7-e09da1bb18d0 · inbound

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

Retrieval-Augmented Generation for Large Language Models: A Survey In-Context Retrieval-Augmented Language Models

Reference 64

Resolution
verified exact
arxiv_id, observed 2026-05-24T05:13:56.926895Z

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=2026-05-24T05:10:25.171044Z digest=sha256:b16806b847c510056f505700b2a16c879047ffa708112c2a72008bc741dc6bcd

Observation de97d298-1098-4f49-a60a-f911eb295e62 · inbound

RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval cites this paper.

RAPTOR: Recursive Abstractive Processing for Tree-Organized Retrieval In-Context Retrieval-Augmented Language Models

Reference 146

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metadata mismatch
arxiv_id, observed 2026-05-15T13:07:16.460510Z

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=2026-05-15T13:07:16.151160Z digest=sha256:5b6140e61c159ac273156cbd791deeab479e2cf693ec94d2e15d9347465ef77c

Observation a05e8086-69d9-4fb2-a5b8-1ed01f13c5c2 · inbound

Retrieval-Augmented Generation for AI-Generated Content: A Survey cites this paper.

Retrieval-Augmented Generation for AI-Generated Content: A Survey In-Context Retrieval-Augmented Language Models

Reference 87

Resolution
verified exact
arxiv_id, observed 2026-05-15T13:32:17.350761Z

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=2026-05-15T13:32:17.177021Z digest=sha256:b48bc6168bc3e1649c5f1e8835a3f7a09e7d26861a65faadb65b3aa19220998a

Observation 1a2733d2-23da-49c4-bb47-f300e6af16d2 · inbound

SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence cites this paper.

SelfElicit: Your Language Model Secretly Knows Where is the Relevant Evidence In-Context Retrieval-Augmented Language Models

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T23:49:14.656863Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T23:49:14.656863Z digest=sha256:f129c47f117d0beca0f1611724c33f72f1c8bf6d0a76b450d82f5d4dea73a6f5

Observation 0dd9d168-b397-4e15-99c8-395741c4e046 · inbound

ZeroSearch: Incentivize the Search Capability of LLMs without Searching cites this paper.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching In-Context Retrieval-Augmented Language Models

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-17T17:44:13.523496Z

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=2026-05-17T17:44:13.310155Z digest=sha256:aa3b9c2bfb4fae549cf65fc50ecb873c87f5ecefbead09077011aa2ec1ac9570

Observation 08b0c24c-afe1-4f95-a02b-137390c3baa6 · inbound

ZeroSearch: Incentivize the Search Capability of LLMs without Searching cites this paper.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching In-Context Retrieval-Augmented Language Models

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-22T16:06:45.985020Z

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=2026-05-22T16:05:04.715678Z digest=sha256:e37ee8057d30e7b3783b8c2b267340fc2c6162eb14f5ab21a85643126b4d0b0e

Observation 8c40a462-bd6d-432d-89e8-e3b80e7c47cf · inbound

On the Merits of LLM-Based Corpus Enrichment cites this paper.

On the Merits of LLM-Based Corpus Enrichment In-Context Retrieval-Augmented Language Models

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-07T06:06:36.180787Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:06:36.180787Z digest=sha256:68111f2385fe375fb5d92a0eacdbefa929c4c1d9ec37872b25ca5f7fe4cd24b6

Observation 4481cc7b-1372-4743-ba5a-8e0fe63fab75 · inbound

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

HIRAG: Hierarchical-Thought Instruction-Tuning Retrieval-Augmented Generation In-Context Retrieval-Augmented Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-06T19:24:51.610954Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T19:24:51.610954Z digest=sha256:e348cfea6b969179afa131806986acd68342fc5db4c550c7721a504ff2aade55

Observation e6572969-1979-4a75-91a6-b76a38ae753c · inbound

Shifting from Ranking to Set Selection for Retrieval Augmented Generation cites this paper.

Shifting from Ranking to Set Selection for Retrieval Augmented Generation In-Context Retrieval-Augmented Language Models

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T18:57:33.612325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:57:33.612325Z digest=sha256:cb7d9af87284465fc95711b6ae3d358c34794495169ff9f0cc7dbf3c3953c976

Observation 223b0bc9-01f6-4e64-ab1b-bf8fbdfeb7c4 · inbound

Structured Relevance Assessment for Robust Retrieval-Augmented Language Models cites this paper.

Structured Relevance Assessment for Robust Retrieval-Augmented Language Models In-Context Retrieval-Augmented Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T13:00:16.564980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T13:00:16.564980Z digest=sha256:70fa837103a5d99381fb6fa717d764fafe45dcc9caf2aece125c23dafd951de7

Observation a7049742-7bd4-4921-a53c-c6d1248dbdef · inbound

How Training Data Shapes the Use of Parametric and In-Context Knowledge in Language Models cites this paper.

How Training Data Shapes the Use of Parametric and In-Context Knowledge in Language Models In-Context Retrieval-Augmented Language Models

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-18T13:11:23.879065Z

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=2026-05-18T13:10:16.948681Z digest=sha256:a8dd3fb7e771d587d506bc6d2d34c78747487f26372c7bbae55314ba191f35ef

Observation 29496794-7a0d-4828-b5f2-83ae8701243e · inbound

Benchmarking Knowledge-Extraction Attack and Defense on Retrieval-Augmented Generation cites this paper.

Benchmarking Knowledge-Extraction Attack and Defense on Retrieval-Augmented Generation In-Context Retrieval-Augmented Language Models

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-03T03:04:47.687033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T03:04:47.687033Z digest=sha256:2688600f4252173f86618d89925522d0df3d4569945dc3cbfb33fd81ed7da8e7

Observation 522ffcd8-27db-47be-aa56-797aaabb3700 · inbound

A Systematic Study of Retrieval Pipeline Design for Retrieval-Augmented Medical Question Answering cites this paper.

A Systematic Study of Retrieval Pipeline Design for Retrieval-Augmented Medical Question Answering In-Context Retrieval-Augmented Language Models

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:00:56.840519Z

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=2026-05-10T17:51:41.539951Z digest=sha256:0ae3a4d0e51921664f020f3407453305f08f4334dbb197a8298b81922f82a75f

Observation 10cb5e1a-ab84-452a-950f-f9098da1ec1e · inbound

IG-Search: Step-Level Information Gain Rewards for Search-Augmented Reasoning cites this paper.

IG-Search: Step-Level Information Gain Rewards for Search-Augmented Reasoning In-Context Retrieval-Augmented Language Models

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-10T11:20:10.657400Z

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=2026-05-10T11:17:36.658624Z digest=sha256:4d0479aaf33cdca22e3ef46681fded221874ac7e6c5ed32dd80225326c2a46e5

Observation e36a066f-18a7-4a8f-98a5-aa2e69a907fc · inbound

AgenticRAG: Agentic Retrieval for Enterprise Knowledge Bases cites this paper.

AgenticRAG: Agentic Retrieval for Enterprise Knowledge Bases In-Context Retrieval-Augmented Language Models

Reference 25

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T19:21:08.698498Z

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=2026-05-08T12:10:01.748436Z digest=sha256:3d420f0cd098cc5a37ce32dba6df237eec2b8c790bada313ae0124fa198b984c

Observation b5840a00-e2e9-48e1-85b5-70212f0d288d · inbound

Assisted Counterspeech Writing at the Crossroads of Hate Speech and Misinformation cites this paper.

Assisted Counterspeech Writing at the Crossroads of Hate Speech and Misinformation In-Context Retrieval-Augmented Language Models

Reference 176

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T07:11:13.041201Z

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=2026-05-22T07:07:36.726431Z digest=sha256:8112972eb1d1ca632ef92c3d4a46ef64fc4217341f26738759ae1945a7658715

Observation 3d886110-bfad-4e3a-b0f6-f5899a6db256 · inbound

SIFT: Selective-Index For Fast Compute of RAG Prefill by Exploiting Attention Invariance cites this paper.

SIFT: Selective-Index For Fast Compute of RAG Prefill by Exploiting Attention Invariance In-Context Retrieval-Augmented Language Models

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-07-03T01:37:31.212964Z

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=2026-06-27T16:24:31.109508Z digest=sha256:7387e89444a11f5aa8d551209235b58eeb147f884eebec6ae57aaa4afbb4a841

Observation d537827f-e6ab-418a-afef-b8961f996df2 · inbound

CATCH-ME if you RAG: a dataset of Contextually Annotated multi-Turn Counterspeech against Hate and Misinformation Exchanges cites this paper.

CATCH-ME if you RAG: a dataset of Contextually Annotated multi-Turn Counterspeech against Hate and Misinformation Exchanges In-Context Retrieval-Augmented Language Models

Reference 187

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T03:59:32.510261Z

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=2026-06-26T17:30:07.053955Z digest=sha256:bf2c4f05afc51067d6c3493c3774ad7382c473b6ed67af1b50cd96b9fa9386dd

Observation 1e140bd4-5890-4a31-bd35-56dad2afc9c1 · inbound

BM25 Wins at Scale: A Scaling Study of Retrieval-Augmented Generation Paradigms cites this paper.

BM25 Wins at Scale: A Scaling Study of Retrieval-Augmented Generation Paradigms In-Context Retrieval-Augmented Language Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-01T14:35:26.234244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T14:35:26.234244Z digest=sha256:b24e5b874a71d7bc13caba20b9418fa9e593d5a755f1dcd29704dd63666b393d

Observation 5f24706e-36a2-4882-8d39-2f83379eacb3 · inbound

BM25 Wins at Scale: A Scaling Study of Retrieval-Augmented Generation Paradigms cites this paper.

BM25 Wins at Scale: A Scaling Study of Retrieval-Augmented Generation Paradigms In-Context Retrieval-Augmented Language Models

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-03T01:44:58.960285Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T01:44:58.960285Z digest=sha256:96457c7c98cb101baa80fde2684b3cc042cbb62f515f288c923fc57e5335bd07

Observation 54b12895-8ad8-4145-b0ce-faf5178e3eee · inbound

Align-RAG: Alignment Is All You Need for TSFM In-Context Learning cites this paper.

Align-RAG: Alignment Is All You Need for TSFM In-Context Learning In-Context Retrieval-Augmented Language Models

Reference 2023

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unresolved
no resolver link, observed 2026-08-08T10:21:59.345421Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T10:21:59.345421Z digest=sha256:5d4ab6b037fc290bde4d2a16d7c97c813249dfead3d8f734f3f6e44d6edbff38