Paper Citation Record · LEDGER

InPars: Data Augmentation for Information Retrieval using Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2202.05144.

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

pith.paper-citation-record.v1
2202.05144 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 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 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:35:19.120001Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:29:51.648971Z

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 babc9a32-38f2-494c-8c1a-a25f811452e4 · inbound

A Survey on Knowledge Distillation of Large Language Models cites this paper.

A Survey on Knowledge Distillation of Large Language Models InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 139

Resolution: verified exact; arxiv_id, observed 2026-05-17T23:31:11.701421Z

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.

Observation 39c98544-9c84-4d1c-983d-5a2154395ebf · inbound

RankFlow: A Multi-Role Collaborative Reranking Workflow Utilizing Large Language Models cites this paper.

RankFlow: A Multi-Role Collaborative Reranking Workflow Utilizing Large Language Models InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-23T04:37:31.886637Z

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.

Observation 143c241c-06e1-49b9-82a4-919fdc9999b7 · inbound

RaDeR: Reasoning-aware Dense Retrieval Models cites this paper.

RaDeR: Reasoning-aware Dense Retrieval Models InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:35:19.120001Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 84df3de8-de0b-4f44-98b4-834c90729a4b · inbound

Conventional Contrastive Learning Often Falls Short: Improving Dense Retrieval with Cross-Encoder Listwise Distillation and Synthetic Data cites this paper.

Conventional Contrastive Learning Often Falls Short: Improving Dense Retrieval with Cross-Encoder Listwise Distillation and Synthetic Data InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:23:37.241122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0e37d3e0-ba86-4f29-8476-3b7645af4ad0 · inbound

Aligning Web Query Generation with Ranking Objectives via Direct Preference Optimization cites this paper.

Aligning Web Query Generation with Ranking Objectives via Direct Preference Optimization InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-07T14:21:52.322777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31aa87bd-e47b-4849-bbc4-81f1d4323bb4 · inbound

How Good are LLM-based Rerankers? An Empirical Analysis of State-of-the-Art Reranking Models cites this paper.

How Good are LLM-based Rerankers? An Empirical Analysis of State-of-the-Art Reranking Models InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-05T17:15:15.244567Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4049f2e4-a220-4580-b31d-4d68d31dd6dc · inbound

Negative Matters: Multi-Granularity Hard-Negative Synthesis and Anchor-Token-Aware Pooling for Enhanced Text Embeddings cites this paper.

Negative Matters: Multi-Granularity Hard-Negative Synthesis and Anchor-Token-Aware Pooling for Enhanced Text Embeddings InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-05T13:16:26.730577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45cf7666-8990-4a68-9834-1a98fc368b69 · inbound

Scaling Search Relevance: Augmenting App Store Ranking with LLM-Generated Judgments cites this paper.

Scaling Search Relevance: Augmenting App Store Ranking with LLM-Generated Judgments InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T20:27:46.184823Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7a4ffb6-f6ed-4041-8187-d9247763bd12 · inbound

Are LLM-Based Retrievers Worth Their Cost? An Empirical Study of Efficiency, Robustness, and Reasoning Overhead cites this paper.

Are LLM-Based Retrievers Worth Their Cost? An Empirical Study of Efficiency, Robustness, and Reasoning Overhead InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-13T17:23:02.630270Z

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.

Observation 918a4e4c-35de-4e9e-8ea9-d0c8a84c4f2a · inbound

ARHN: Answer-Centric Relabeling of Hard Negatives with Open-Source LLMs for Dense Retrieval cites this paper.

ARHN: Answer-Centric Relabeling of Hard Negatives with Open-Source LLMs for Dense Retrieval InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:11:12.382002Z

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.

Observation 7f3c9f0a-2514-48c5-828f-0e38d584cfa4 · inbound

UnIte: Uncertainty-based Iterative Document Sampling for Domain Adaptation in Information Retrieval cites this paper.

UnIte: Uncertainty-based Iterative Document Sampling for Domain Adaptation in Information Retrieval InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-12T00:06:15.879925Z

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.

Observation 2d69f4d0-7740-41fe-9563-c3e322e3b6f8 · inbound

Bridging the Cold-Start Gap: LLM-Powered Synthetic Data Generation for Natural Language Search at Airbnb cites this paper.

Bridging the Cold-Start Gap: LLM-Powered Synthetic Data Generation for Natural Language Search at Airbnb InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-22T08:04:43.080450Z

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.

Observation c2c66393-d3d1-49e1-8027-f52e1b0d1c9a · 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 InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 173

Resolution: verified exact; arxiv_id, observed 2026-05-22T07:11:13.035595Z

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.

Observation 6d98cae9-308f-464e-a7fb-22134a6e9f20 · inbound

RAG-Match: Retrieval-Augmented Knowledge Injection and Hierarchical Reasoning for Calibrated Semantic Relevance cites this paper.

RAG-Match: Retrieval-Augmented Knowledge Injection and Hierarchical Reasoning for Calibrated Semantic Relevance InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-06-29T20:53:58.026524Z

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.

Observation b3e07a9d-70f1-4bdb-bd66-3babb1f04673 · inbound

SPECTRA: Synthetic IR Test Collections with Relevance Oracles and Controlled Distractor Diagnostics cites this paper.

SPECTRA: Synthetic IR Test Collections with Relevance Oracles and Controlled Distractor Diagnostics InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-06-28T20:42:37.229789Z

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.

Observation bd1d1f3d-82e4-40eb-928b-b2cc95fa76c9 · 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 InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 184

Resolution: verified exact; arxiv_id, observed 2026-07-04T03:59:32.630516Z

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.

Observation ee3dd59a-bf49-42d3-84f7-c45529b9961e · inbound

Designing Reward Signals for Portable Query Generation: A Case Study in Industrial Semantic Job Search cites this paper.

Designing Reward Signals for Portable Query Generation: A Case Study in Industrial Semantic Job Search InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-07-04T13:29:51.650301Z

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.

Observation 818d35a8-6baf-4d1f-b72d-64a7955514e9 · inbound

Self-Study Reconsidered: The Hidden Fragility of Learning from Self-Generated QA cites this paper.

Self-Study Reconsidered: The Hidden Fragility of Learning from Self-Generated QA InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 3

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T10:45:42.785309Z

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.

Observation 383eff12-16a2-41f9-9957-31a2107c6274 · inbound

SMART: LLM-Augmented Hybrid Retrieval for Dynamic Product Ads cites this paper.

SMART: LLM-Augmented Hybrid Retrieval for Dynamic Product Ads InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-01T03:36:58.387806Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5297a7ab-6489-4bae-8c52-f0ad6d87efda · inbound

Bekko Embedding: Parameter-Efficient Multilingual Retrieval with Ultra-Compact Encoders cites this paper.

Bekko Embedding: Parameter-Efficient Multilingual Retrieval with Ultra-Compact Encoders InPars: Data Augmentation for Information Retrieval using Large Language Models

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-01T03:15:58.067080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.