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Paper Citation Record · LEDGER

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search

As of 23 August 2026, this Paper Citation Record lists 16 of 16 outbound references and 0 inbound Pith citation observations for arXiv:2602.23620.

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

pith.paper-citation-record.v1
2602.23620 v2

Coverage vector

measured 16 of 16 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-15T19:27:17.802597Z

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+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

16 of 16 outbound references displayed

  • verified exact9
  • verified fuzzy0
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 5feb4833-e595-4d2d-800f-2594ee99bd6c · outbound

This paper cites an unresolved cited work.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-05-15T19:31:31.897582Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:7a68e94fcb4276f16d520006360cdc9afa902bcd23af5a7072b9d02004f08940

Observation af9b26ff-7ea0-4a68-a53c-783b9b157cdc · outbound

This paper cites an unresolved cited work.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search Unresolved cited work

Reference 2

Resolution
unresolved
raw_fallback, observed 2026-05-15T19:31:31.902500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:252efc6f5d2fd8f63b85a6b0b9a4d7ce86ce2a6e5fc0804bccd94f47ff45d4e4

Observation 25c330be-1b94-428e-bf81-e95a9246ae6a · outbound

This paper cites REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization

Reference 3

Resolution
verified exact
local_arxiv, observed 2026-05-15T19:30:16.775303Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:6b4cd13e608aa022ea090aea085a6b7bb44990f51fdf97051794306e69b35109

Observation ce3a6a37-c4af-4964-9a27-b8505cb44637 · outbound

This paper cites an unresolved cited work.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search Unresolved cited work

Reference 4

Resolution
unresolved
raw_fallback, observed 2026-05-15T19:31:31.888069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:3120b5fc3a37e8b659b5d5bdb01ea425220cbd76efe67e83a330c445bee92760

Observation 3457f512-1dd3-4b36-a6c5-4a3aa91de7c9 · outbound

This paper cites Generative Retrieval with Preference Optimization for E-commerce Search.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search Generative Retrieval with Preference Optimization for E-commerce Search

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-15T19:30:16.795453Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:b58eb753ddca02fc1a6aac9197ea3ec622667e713bb768abe7bdc556386f9a5b

Observation 1699cc91-6354-4864-8077-cea8fdb78b0e · outbound

This paper cites arXiv preprint arXiv:2511.13885 , year=.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search arXiv preprint arXiv:2511.13885 , year=

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-15T19:30:16.796311Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:1169f2b8542139d26b75ab5c2579e7b457e2b0bf00685b7d5727bb1092bfb212

Observation 9dcd0c44-eb61-4e33-ae8f-e57ecd3baeb4 · outbound

This paper cites RL-based query rewriting with dis- tilled LLM for online e-commerce systems.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search RL-based query rewriting with dis- tilled LLM for online e-commerce systems

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-05-15T19:30:16.780304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:c7819074db41f5cee021bf5409165ffa2503aa102fc5341d5fe5e9f7a121caa7

Observation 4a770b33-ccb0-4c49-aaf7-f5905fb07010 · outbound

This paper cites an unresolved cited work.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search Unresolved cited work

Reference 8

Resolution
unresolved
raw_fallback, observed 2026-05-15T19:31:31.869356Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:e1f0312d57e5a17c64cb85d0c77f18e1649e4d60d13590e2f5f577466c20ca21

Observation 3f41488a-a9f2-4b14-b5f9-15435ac11773 · outbound

This paper cites an unresolved cited work.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search Unresolved cited work

Reference 9

Resolution
unresolved
raw_fallback, observed 2026-05-15T19:31:31.863379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:7c6077c5c4c3dabb1f9cf5355e35b8426d1448573c949f7494ea6282b7fee30a

Observation 8bf059a9-a3e1-4ca1-be96-b22915a2709a · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-05-15T19:30:16.779191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:46ffdaa618792ba39f773e37beae88ee41d813ea7d2f06ce24eea3ff666b6133

Observation 08e6c655-7b2b-46e9-8164-082a1dc5a466 · outbound

This paper cites One Embedder, Any Task: Instruction-Finetuned Text Embeddings.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search One Embedder, Any Task: Instruction-Finetuned Text Embeddings

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-15T19:30:16.762903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:689ed84dae25d663034838ef041472d67c74f2015ce9d2f83eec31338d40b4af

Observation 60e45620-1d2d-40bb-bd30-a11510e4bcc6 · outbound

This paper cites an unresolved cited work.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-05-15T19:31:31.880064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:8985bdb38bb2e84f942713bdc545aa92746a00b26cfe9e20bcba1178bf334e49

Observation cad7aad1-58b4-4b40-ae75-c7c578b63a76 · outbound

This paper cites Qwen3 Technical Report.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search Qwen3 Technical Report

Reference 13

Resolution
verified exact
local_arxiv, observed 2026-05-15T19:30:16.767631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:181f2563712bf28393efa80765e027fc6f649e52cc5864dea87f4332a71d5116

Observation 1f86f5e7-f68a-4dca-baf8-2f190263c6a5 · outbound

This paper cites TaoSR-AGRL: Adaptive Guided Reinforcement Learning Framework for E-commerce Search Relevance.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search TaoSR-AGRL: Adaptive Guided Reinforcement Learning Framework for E-commerce Search Relevance

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-07-07T03:17:12.927851Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:72d6222cebee12dae2c5d6d0bf3cb7c5165ac0f2ba470d2bff4e7c96854fee79

Observation 030a5f85-d9bf-455e-95db-2a6264cc3d52 · outbound

This paper cites an unresolved cited work.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search Unresolved cited work

Reference 15

Resolution
unresolved
raw_fallback, observed 2026-05-15T19:31:31.874231Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:5f4ab08b3dc97b449a74b2fbb20fb2600854f0dbad3d5e446b4a6e159e4a49b9

Observation 3c443da4-0b33-4846-9293-b38a3b3d4091 · outbound

This paper cites Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models.

Synthetic Data Powers Product Retrieval for Long-tail Knowledge-Intensive Queries in E-commerce Search Qwen3 Embedding: Advancing Text Embedding and Reranking Through Foundation Models

Reference 16

Resolution
verified exact
local_arxiv, observed 2026-05-15T19:30:16.785013Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T19:27:17.802597Z digest=sha256:e15c02154a790791c82d461021a9ad357b259b015586499a3e25dd083b162429

Pith citing papers

No inbound Pith citation observations are available.