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Paper Citation Record · LEDGER

Semantic Retrieval for Product Search in E-Commerce

As of 5 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 0 inbound Pith citation observations for arXiv:2606.01504.

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

pith.paper-citation-record.v1
2606.01504 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T15:59:02.057914Z

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+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

13 of 13 outbound references displayed

  • verified exact2
  • verified fuzzy0
  • unresolved7
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch4

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation af7ab131-13b3-40f3-af1d-11790d7a6419 · outbound

This paper cites InProceedings of the 2017 ACM on Conference on Information and Knowledge Management, pages 1747–1756.

Semantic Retrieval for Product Search in E-Commerce InProceedings of the 2017 ACM on Conference on Information and Knowledge Management, pages 1747–1756

Reference 1

Resolution
unresolved
no resolver link, observed 2026-06-28T15:59:02.057914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T15:59:02.057914Z digest=sha256:79140aa2142a5cf4d56f9387a09e3ea3f2b24dafa71b796a8e53e443428591d4

Observation 37a9455c-e35e-494a-9cfb-3cf31a82a175 · outbound

This paper cites ORPO: Monolithic Preference Optimization without Reference Model.

Semantic Retrieval for Product Search in E-Commerce ORPO: Monolithic Preference Optimization without Reference Model

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-07-01T21:56:15.914811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-28T15:59:02.057914Z digest=sha256:28bcc802404538584b43150a9c7f5253d9039a9963014689e89eda4369c36121

Observation 3bb8f68c-a2b9-4cc7-9f55-0f797ea7edb1 · outbound

This paper cites InProceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 6769–6781.

Semantic Retrieval for Product Search in E-Commerce InProceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 6769–6781

Reference 3

Resolution
unresolved
no resolver link, observed 2026-06-28T15:59:02.057914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T15:59:02.057914Z digest=sha256:f569ccc7eb226e0d92c0453a2ea5282da66eb2b50fb67949db4a471aefb805cd

Observation ec63825f-f91f-4592-a251-33c7a176f7b4 · outbound

This paper cites NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models.

Semantic Retrieval for Product Search in E-Commerce NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models

Reference 4

Resolution
metadata mismatch
local_arxiv, observed 2026-07-01T21:56:15.911836Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-28T15:59:02.057914Z digest=sha256:3c4f6442871b87f80abed9c55251808206cf29bb07472b548558be2696f7724d

Observation f6f3d90b-7314-4bbb-acc4-d2d2068973d1 · outbound

This paper cites From Semantic Retrieval to Pairwise Ranking: Applying Deep Learning in E-commerce Search.

Semantic Retrieval for Product Search in E-Commerce From Semantic Retrieval to Pairwise Ranking: Applying Deep Learning in E-commerce Search

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-07-01T21:56:15.914371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-28T15:59:02.057914Z digest=sha256:b278b8b98fe39dc4c07b2b565d65eb4cf97dabef5b14637b550e4cbb3fb5b19a

Observation 50322e78-2d54-481b-ae93-bf368deb1479 · outbound

This paper cites Generative Representational Instruction Tuning.

Semantic Retrieval for Product Search in E-Commerce Generative Representational Instruction Tuning

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T21:56:15.917478Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-28T15:59:02.057914Z digest=sha256:643d8405a730a9014f1f98d9b2372806c3a278c5a9ff27da23f78504e778f5c0

Observation a2633759-29b0-45c6-94f9-c3e0b664c9da · outbound

This paper cites Large Dual Encoders Are Generalizable Retrievers.

Semantic Retrieval for Product Search in E-Commerce Large Dual Encoders Are Generalizable Retrievers

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T21:56:15.920210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-28T15:59:02.057914Z digest=sha256:c02f50c5c77b85a24cc21f970f0e4b3b6eb827edb5752289cf624bc581847a91

Observation b4534118-8653-499c-b95e-33181a99407a · outbound

This paper cites InProceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.

Semantic Retrieval for Product Search in E-Commerce InProceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Reference 8

Resolution
unresolved
no resolver link, observed 2026-06-28T15:59:02.057914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T15:59:02.057914Z digest=sha256:36711b1b9e096d4bd03813f5c66e6063470821d99de07dc66fed8bb48ca76f06

Observation 34ee48bd-1b2a-478b-a102-4c9053e9b141 · outbound

This paper cites Chandan K.

Semantic Retrieval for Product Search in E-Commerce Chandan K

Reference 9

Resolution
unresolved
no resolver link, observed 2026-06-28T15:59:02.057914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T15:59:02.057914Z digest=sha256:34ed47e1e497a30ac15ee5339aa99771252e0d08288d937a8dd4789fadba8f12

Observation 844952fb-3558-41ac-ad71-6e3e003f0faa · outbound

This paper cites InProceedings of the 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 3982–3992.

Semantic Retrieval for Product Search in E-Commerce InProceedings of the 2019 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 3982–3992

Reference 10

Resolution
unresolved
no resolver link, observed 2026-06-28T15:59:02.057914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T15:59:02.057914Z digest=sha256:3912c4207f463c45b182def556caf3bbc11c83d6876a359ba441153b2766d22f

Observation 3ab0a439-b4fe-43c1-a067-120e8bfc5a48 · outbound

This paper cites https: //qwenlm.github.io/blog/qwen3-embedding/.

Semantic Retrieval for Product Search in E-Commerce https: //qwenlm.github.io/blog/qwen3-embedding/

Reference 11

Resolution
unresolved
no resolver link, observed 2026-06-28T15:59:02.057914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T15:59:02.057914Z digest=sha256:afb885e8446573ca82cc3557be07f9f213b2d30d9195943b44aadbaafcafb37d

Observation 4a5852b5-25e5-4ef4-a099-cb41e7a9b942 · outbound

This paper cites Improving Text Embeddings with Large Language Models.

Semantic Retrieval for Product Search in E-Commerce Improving Text Embeddings with Large Language Models

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T21:56:15.922664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-06-28T15:59:02.057914Z digest=sha256:c34de31bc3df188311aa9b2520281c4f47b53bd84ec65c77bdae54c9d8cabda2

Observation cba6dedb-438e-413f-85d3-5379ed28ccc3 · outbound

This paper cites InProceedings of the Web Conference 2021, pages 2890–2899.

Semantic Retrieval for Product Search in E-Commerce InProceedings of the Web Conference 2021, pages 2890–2899

Reference 13

Resolution
unresolved
no resolver link, observed 2026-06-28T15:59:02.057914Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-06-28T15:59:02.057914Z digest=sha256:ea78d8c293ea1817776f946c0b7b0c7cc56c536ae8797884557c599cfd3c6b1b

Pith citing papers

No inbound Pith citation observations are available.