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Paper Citation Record · LEDGER

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search

As of 22 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 0 inbound Pith citation observations for arXiv:2607.24417.

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

pith.paper-citation-record.v1
2607.24417 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-31T15:30:45.003762Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+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

45 of 45 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved45
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3cb5cd37-2981-49e7-920c-1977512f42a9 · outbound

This paper cites Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1 , pages =.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Proceedings of the 32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.1 , pages =

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.334458Z digest=sha256:fb0e589d26b910d43fe52a5fdda85883260aa0872e6471a63a09bca26326d90f

Observation c365e536-5219-40b2-b06d-79c43d5a4f67 · outbound

This paper cites 2024 , eprint=.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search 2024 , eprint=

Reference 2

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no resolver link, observed 2026-07-31T15:30:43.374201Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.374201Z digest=sha256:2b1b811130256928f28c0c7d0d1cf120d163e00bf38bf01badba7e968b50f9c1

Observation 2a04c5ea-50a9-4a91-a027-637e6836e326 · outbound

This paper cites Chi and Quoc V.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Chi and Quoc V

Reference 3

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source=arxiv_source observed=2026-07-31T15:30:43.407164Z digest=sha256:97cab89732a10091d5592f362a1abc213d7f554bc8bf8886b23ed341a3783c26

Observation 903f0d23-6d13-4dd9-b014-913f5ecf0e5a · outbound

This paper cites Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval , pages =.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval , pages =

Reference 4

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source=arxiv_source observed=2026-07-31T15:30:43.445704Z digest=sha256:9cb1755dc99cf937af674fc6b8d1f25c8ec0956abaed250aeb06d2b843fcddeb

Observation 69caee27-e8b0-4aaf-8927-9b1154364ff6 · outbound

This paper cites Passage Re-ranking with BERT.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Passage Re-ranking with BERT

Reference 5

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no resolver link, observed 2026-07-31T15:30:43.454783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.454783Z digest=sha256:b56ad86ed3ca07853c8db3fd0d705bc9ab68df9c66aa81f12f5adc20d38b7cf9

Observation fd323852-9cf2-46d0-aa75-6176ea6b3c9a · outbound

This paper cites Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining , pages =.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining , pages =

Reference 6

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no resolver link, observed 2026-07-31T15:30:43.495716Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.495716Z digest=sha256:0e2182d19b47efab6cf427e57734bac78c9b99e17af0a86f1e6f7de1700774f8

Observation 27f4e0ad-0b7a-40dc-9d6f-4b1518c46764 · outbound

This paper cites Let s Verify Step by Step , url =.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Let s Verify Step by Step , url =

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.531622Z digest=sha256:e669e57fa5035385be7f118363607eff21a1d7a128fcc50a668f3512346f3109

Observation 49832dba-20cd-4744-bebd-1ba82e8a82a9 · outbound

This paper cites an unresolved cited work.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Unresolved cited work

Reference 8

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.568232Z digest=sha256:b53850b86a551a9c1de398e41e7ffa05cbf6cc198a9bfdc4c7a2b0d2a6f50f91

Observation f0f9a25b-9d46-4037-878d-acd6a579f0e7 · outbound

This paper cites Manning and Stefano Ermon and Chelsea Finn , editor =.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Manning and Stefano Ermon and Chelsea Finn , editor =

Reference 9

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.598467Z digest=sha256:9044c1333c84add86e2bdc3097a75c03f2a1c2e749e9516e9b85be2b0634ecd6

Observation 4ef16e48-5744-4bc6-82f1-8b3eb1566181 · outbound

This paper cites an unresolved cited work.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Unresolved cited work

Reference 10

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.636866Z digest=sha256:e8ee8fb162c4d79f2b7b0a7b5f13b69949a0e94626d380581278e537551f77fe

Observation 6aa091cb-9c9a-4d9a-9e81-b18778c3a151 · outbound

This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 11

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.680457Z digest=sha256:c1dd38286cd045365986fd8435b8af7d57c668a158b71c97773dc6c96a7d5db1

Observation 1c5203c7-f4c4-4c24-bb0b-35e3f4021720 · outbound

This paper cites Math-Shepherd: Verify and Reinforce LLM s Step-by-step without Human Annotations.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Math-Shepherd: Verify and Reinforce LLM s Step-by-step without Human Annotations

Reference 12

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no resolver link, observed 2026-07-31T15:30:43.719420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.719420Z digest=sha256:901b6b4b764e9bd2886b08d70622f8e28c1d2fb64b1436cf2f6bb6ce778090c6

Observation 46e6efa6-e40f-4d41-91ff-9f5cbd2d2cae · outbound

This paper cites Improve Mathematical Reasoning in Language Models by Automated Process Supervision.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Improve Mathematical Reasoning in Language Models by Automated Process Supervision

Reference 13

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no resolver link, observed 2026-07-31T15:30:43.752184Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.752184Z digest=sha256:95248ec05f5fe4d3fe9252504309dafee1268eb564aeeecff3891dfd43a6af63

Observation 5074e0ea-7a4d-4691-9f96-7453f58aca49 · outbound

This paper cites Qwen2.5 Technical Report.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Qwen2.5 Technical Report

Reference 14

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.794439Z digest=sha256:9d3e02271f1a6971663cf0560410ae385c8dffc3a8f17c8ffa78539e4116fd15

Observation 770113d1-349e-4f48-be21-6bccb88ec87a · outbound

This paper cites 2025 , eprint=.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search 2025 , eprint=

Reference 15

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no resolver link, observed 2026-07-31T15:30:43.835434Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.835434Z digest=sha256:b5d30101b1982903bb50d0f982b19691946655b6195836a0a815716a0bcf7e6d

Observation 2e5b469d-7676-49a4-b606-4a33f4850fe3 · outbound

This paper cites Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Large Language Models are Effective Text Rankers with Pairwise Ranking Prompting

Reference 16

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.873212Z digest=sha256:021f28667f3a5b1146ecfc444cebd0e92ba1521cd22363ed1730519cdfb9b330

Observation e5202f0b-ff0b-4db5-96bf-724966b9656d · outbound

This paper cites Solving math word problems with process- and outcome-based feedback.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Solving math word problems with process- and outcome-based feedback

Reference 17

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.908924Z digest=sha256:e0285b5adb68d52360b332c292722afeb6f82bf404b973be7daa0f6b2e33c304

Observation 42bc5be8-eca2-420d-9cdb-c0ad8787567f · outbound

This paper cites Proceedings of the 42nd International Conference on Machine Learning , articleno =.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Proceedings of the 42nd International Conference on Machine Learning , articleno =

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:43.945629Z digest=sha256:0c832ae21918f827f027f356226b0f219182846f1c710382d2afd2e02dac6777

Observation 6c5c40bb-1287-4df1-9c04-27fc53e9bd56 · outbound

This paper cites Proximal Policy Optimization Algorithms.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Proximal Policy Optimization Algorithms

Reference 19

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no resolver link, observed 2026-07-31T15:30:43.976747Z

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source=arxiv_source observed=2026-07-31T15:30:43.976747Z digest=sha256:6fa188f4fd4cb993e8b51161eab1256c39c0544893e067b1d7c8a3a748f246d7

Observation d62dd556-9f0d-44a6-be09-4ac0af711ad7 · outbound

This paper cites Document Ranking with a Pretrained Sequence-to-Sequence Model.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Document Ranking with a Pretrained Sequence-to-Sequence Model

Reference 20

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no resolver link, observed 2026-07-31T15:30:44.050911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.050911Z digest=sha256:05cee415aa22d4f330a4dbcf7ce6a2f942dd3d35086f36fd964ce72d796de032

Observation e0785579-8e5f-4817-9f44-231f7d80f073 · outbound

This paper cites Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval , pages =.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval , pages =

Reference 21

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no resolver link, observed 2026-07-31T15:30:44.086611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.086611Z digest=sha256:5bd3f665f3fd8f2d644bd83c85eb2f04f7312c38b0b0124130fa29380da54cf9

Observation 1aace8d5-3a27-436f-9b5b-5ac58331694e · outbound

This paper cites Zero-Shot Listwise Document Reranking with a Large Language Model.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Zero-Shot Listwise Document Reranking with a Large Language Model

Reference 22

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.123360Z digest=sha256:42d0a669f2ae30efc3a4ab9ad2f8343941634a6617ce68851182afb0dc6be087

Observation 6eca9c53-481f-4d87-aa28-f2957f852e7b · outbound

This paper cites RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search RankZephyr: Effective and Robust Zero-Shot Listwise Reranking is a Breeze!

Reference 23

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source=arxiv_source observed=2026-07-31T15:30:44.162845Z digest=sha256:909691a2b6cfa5f193bc024cfeed43d6007f69d8a6a404cd38062104b6b4752a

Observation f612a84d-5aad-4312-b7de-c734fd9a55e8 · outbound

This paper cites Is C hat GPT Good at Search? Investigating Large Language Models as Re-Ranking Agents.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Is C hat GPT Good at Search? Investigating Large Language Models as Re-Ranking Agents

Reference 24

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no resolver link, observed 2026-07-31T15:30:44.200395Z

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source=arxiv_source observed=2026-07-31T15:30:44.200395Z digest=sha256:49e6f3189b32716ceaeb4263eb24862e8d4ddca11f0bff6dc2d56d39a0aa9f28

Observation 1291f33f-07a8-4db8-992e-1d1dd8424d75 · outbound

This paper cites Process Reinforcement through Implicit Rewards.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Process Reinforcement through Implicit Rewards

Reference 25

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source=arxiv_source observed=2026-07-31T15:30:44.240740Z digest=sha256:ce403379973d448bcb14604e0da9d62ba180617b08f95a12cc3a5022bb71fe2f

Observation f5b8d4b2-39d3-4c4c-9a34-0e9ca2256286 · outbound

This paper cites 2026 , eprint=.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search 2026 , eprint=

Reference 26

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.277445Z digest=sha256:24385940017720146b1acb905b2f4e4796760088d425c7d07c59c6aeca0ccd45

Observation 96390bda-bb8e-44db-bd28-d41a802deddb · outbound

This paper cites Large Language Models for Relevance Judgment in Product Search.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Large Language Models for Relevance Judgment in Product Search

Reference 27

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source=arxiv_source observed=2026-07-31T15:30:44.315820Z digest=sha256:591bf1fd1ca97cdf54d244571b144418295cd8020df7b0f82eec05578b713ed3

Observation 1a91ef55-f358-4a58-905b-cb82b8d767cb · outbound

This paper cites Towards Boosting LLM s-driven Relevance Modeling with Progressive Retrieved Behavior-augmented Prompting.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Towards Boosting LLM s-driven Relevance Modeling with Progressive Retrieved Behavior-augmented Prompting

Reference 28

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.357066Z digest=sha256:a47aa286337fd28e81e4232f0f0862d0483aa1aff6cf3903825969c98dca4d5f

Observation 0b03c40d-454a-4ae3-81f5-c005ffbc9793 · outbound

This paper cites 2025 , eprint=.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search 2025 , eprint=

Reference 29

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no resolver link, observed 2026-07-31T15:30:44.393563Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.393563Z digest=sha256:a27cba6be07c55c8966fb3dea1a9305acc3641e1f98727d30679681493394106

Observation 2c579c49-850a-4154-9c01-b2652d5b026f · outbound

This paper cites Large Language Models are Zero-Shot Reasoners , booktitle =.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Large Language Models are Zero-Shot Reasoners , booktitle =

Reference 30

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.408757Z digest=sha256:7383647d88b1e918995c9b42d0e4fda9b2440b5bd8304218f1f92872c9d22458

Observation 52bde7cd-546e-4813-bc9f-425d157811fa · outbound

This paper cites ReprBERT: Distilling.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search ReprBERT: Distilling

Reference 31

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.444663Z digest=sha256:b0b63b26aa1226ad9fb96b86e7c0f2c66a682de1b1bac32ff008c34ade7ab3c8

Observation 838aa10e-f76e-48d2-9183-d3b0b1fb3e33 · outbound

This paper cites Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining , pages =.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining , pages =

Reference 32

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.480562Z digest=sha256:068fc9aac8ba403accc4084eb322c3573770d81d226fcb225789449358cd7245

Observation 143b594b-7eed-4a40-bd2f-551646d365c4 · outbound

This paper cites Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , pages =.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining , pages =

Reference 33

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source=arxiv_source observed=2026-07-31T15:30:44.536570Z digest=sha256:b7495e6e59700d6943a2ee5152abef152e446712c962fcdad018470103a4f6ec

Observation 81a20ceb-d33e-4398-af34-f7cb7f498a87 · outbound

This paper cites ACM Trans.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search ACM Trans

Reference 34

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source=arxiv_source observed=2026-07-31T15:30:44.612073Z digest=sha256:ce6e582193141354ae425bbf6a9c2869211c33d5bdf7a9680c38ddb90019998f

Observation 640273de-346b-4dde-9e2f-1c9d4f05fbab · outbound

This paper cites Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Beyond Yes and No: Improving Zero-Shot LLM Rankers via Scoring Fine-Grained Relevance Labels

Reference 35

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.647780Z digest=sha256:0d695cefba902226d9d56fe9b5ab80201f9d9bb571515a542ed07eee93a4a888

Observation f13f4ec0-6b0a-4c03-8c6f-27972e5cd1b6 · outbound

This paper cites Le and Sergey Levine and Yi Ma , editor =.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Le and Sergey Levine and Yi Ma , editor =

Reference 36

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source=arxiv_source observed=2026-07-31T15:30:44.680738Z digest=sha256:43b8c6b6c87f6b01749daba67f7e4c53ea9336b4777a0e0f8d7999a599c83e3f

Observation cccf7b3d-afdf-4895-95df-53c82702cab4 · outbound

This paper cites Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning

Reference 37

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no resolver link, observed 2026-07-31T15:30:44.721023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.721023Z digest=sha256:78a622ad5eb13709c2169e0189dc96018d100541899f725b50b9586568c5bc7e

Observation aa6b5a2e-6f01-4620-b9fa-ef9fd941a24c · outbound

This paper cites Distilling the Knowledge in a Neural Network.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Distilling the Knowledge in a Neural Network

Reference 38

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no resolver link, observed 2026-07-31T15:30:44.758604Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.758604Z digest=sha256:70503e8d8b4d31015ea0590c2fe484448430d97c214a0399aa683c3d41408763

Observation 1b7f57af-ff8a-4f7f-a82a-53ecf3ed3d42 · outbound

This paper cites Pretrained Transformers for Text Ranking: BERT and Beyond.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Pretrained Transformers for Text Ranking: BERT and Beyond

Reference 39

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unresolved
no resolver link, observed 2026-07-31T15:30:44.794659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.794659Z digest=sha256:518159d240cda86c5b69e342917bd167762c1602ce4c80152952be97bb06767c

Observation 992c8c90-91dd-4681-aba9-a62ffcefe89c · outbound

This paper cites Le and Ed H.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Le and Ed H

Reference 40

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unresolved
no resolver link, observed 2026-07-31T15:30:44.826741Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.826741Z digest=sha256:03b3a7fdd44c7e9a2df7e2c380c85c21537af12b20b18aba6f3abc083038927e

Observation 558704f7-3e54-41f2-a790-f72a774abbd0 · outbound

This paper cites 2022 , eprint=.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search 2022 , eprint=

Reference 41

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unresolved
no resolver link, observed 2026-07-31T15:30:44.867048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.867048Z digest=sha256:2fade3b8b08d9d0ab70f28175eba42b88714bc7a02e0e1789371311281f4e5da

Observation 28e54473-3532-4f7f-b525-1e21dd8b2781 · outbound

This paper cites Rationale-Guided Distillation for E -Commerce Relevance Classification: Bridging Large Language Models and Lightweight Cross-Encoders.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Rationale-Guided Distillation for E -Commerce Relevance Classification: Bridging Large Language Models and Lightweight Cross-Encoders

Reference 42

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no resolver link, observed 2026-07-31T15:30:44.901760Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-07-31T15:30:44.901760Z digest=sha256:d3cd5b689163378e1ad3f8bcd5876bad7637e262a47da507280568a4100dd765

Observation 11f772e8-ff96-43b6-a475-35f1fa4818b6 · outbound

This paper cites HybridFlow: A Flexible and Efficient RLHF Framework , url=.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search HybridFlow: A Flexible and Efficient RLHF Framework , url=

Reference 43

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no resolver link, observed 2026-07-31T15:30:44.940210Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-07-31T15:30:44.940210Z digest=sha256:347eb46de49b1d52ed8d0dec03169896f09ad39cf9918aa533a351960e883429

Observation ccd8ac57-eba1-4766-8c60-0d32951afe8c · outbound

This paper cites L lama F actory: Unified Efficient Fine-Tuning of 100+ Language Models.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search L lama F actory: Unified Efficient Fine-Tuning of 100+ Language Models

Reference 44

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unresolved
no resolver link, observed 2026-07-31T15:30:44.960898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:44.960898Z digest=sha256:29a266d4c043946cd5e29caba16ae82a9c4fff24eef640df9919845bd2937808

Observation b010fb1d-5e51-49de-ade3-60a757802a8c · outbound

This paper cites Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval , pages =.

CORE: A Unified Cascaded Ordinal Relevance Estimation Framework for E-commerce Search Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval , pages =

Reference 45

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unresolved
no resolver link, observed 2026-07-31T15:30:45.003762Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-31T15:30:45.003762Z digest=sha256:7d66dc97b6923463cb52d3c2dc12aea07b88c49d0b4ee317bfc227d327c952ec

Pith citing papers

No inbound Pith citation observations are available.