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Paper Citation Record · LEDGER

A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 12 inbound Pith citation observations for arXiv:2308.08434.

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

pith.paper-citation-record.v1
2308.08434 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 12 of 12 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 12 of 12 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T13:33:57.516200Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T16:18:37.609491Z

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 59565860-f3af-4263-9174-17e41599b2a3 · inbound

Reason4Rec: Deliberative User Preference Alignment of Large Language Models for Recommendation cites this paper.

Reason4Rec: Deliberative User Preference Alignment of Large Language Models for Recommendation A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-09T13:33:57.516200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:33:57.516200Z digest=sha256:ea6ee13a83dd5ec2b080b2b3bf748bd94679570baf8cb0b606b75ad55d6608c0

Observation 9dc31415-1fe1-46c0-98db-4cd5f57185de · inbound

Large Language Model as Universal Retriever in Industrial-Scale Recommender System cites this paper.

Large Language Model as Universal Retriever in Industrial-Scale Recommender System A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-09T10:09:47.286828Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T10:09:47.286828Z digest=sha256:0d4294d084f4ae425975e72d71b4c0e2203f9f783f3e327ae8a6f433facfd91b

Observation 67e4ca65-3742-4a5d-8382-d248bb2ca759 · inbound

Bridging Jensen Gap for Max-Min Group Fairness Optimization in Recommendation cites this paper.

Bridging Jensen Gap for Max-Min Group Fairness Optimization in Recommendation A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-07T22:00:38.214447Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T22:00:38.214447Z digest=sha256:a934f7d03bd2b261022241d9d532126cad9bb8b9f5790f75474c20aef3ee9aab

Observation 7aa5c74d-bef5-4eba-ae6a-f4bb6d8a77ca · inbound

Bridging the Gap: Self-Optimized Fine-Tuning for LLM-based Recommender Systems cites this paper.

Bridging the Gap: Self-Optimized Fine-Tuning for LLM-based Recommender Systems A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T13:52:20.379270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:52:20.379270Z digest=sha256:29f7ceb0d5c86c22494c254524b545d66fce3377fbb130265c01922c89c03041

Observation 78fc9f32-ae17-4afe-a54a-91fb3d0b8abd · inbound

GORACS: Group-level Optimal Transport-guided Coreset Selection for LLM-based Recommender Systems cites this paper.

GORACS: Group-level Optimal Transport-guided Coreset Selection for LLM-based Recommender Systems A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T10:56:21.667746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:56:21.667746Z digest=sha256:7feb0de063e7adaff109c5e058ae9abbb9b9422f1d9454379dace2dacedcf76d

Observation 958ecb6c-9c7f-4ccc-9e71-0eaec8316b34 · inbound

CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systems cites this paper.

CoVE: Compressed Vocabulary Expansion Makes Better LLM-based Recommender Systems A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-06T23:04:13.878697Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:04:13.878697Z digest=sha256:a6e61c31f0794f7623d92e0ef47c7abd22a56562391b8cfe6af530829aec47ab

Observation e98a83cd-3bbf-4c31-a809-afe28dd48033 · inbound

Enhancing Temporal Sensitivity of Large Language Model for Recommendation with Counterfactual Tuning cites this paper.

Enhancing Temporal Sensitivity of Large Language Model for Recommendation with Counterfactual Tuning A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T20:32:05.221986Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:32:05.221986Z digest=sha256:cb4a07a766f4cedd5c36184e077652c5378998345b7c3de7f9035f8828aa320e

Observation 67dfb98d-8b2a-40d4-9384-fbeef0cac58f · inbound

BiFair: A Fairness-aware Training Framework for LLM-enhanced Recommender Systems via Bi-level Optimization cites this paper.

BiFair: A Fairness-aware Training Framework for LLM-enhanced Recommender Systems via Bi-level Optimization A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T19:59:14.277775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T19:59:14.277775Z digest=sha256:b2ee8c96714481b3d1f91bda5cba03a1f2b1459fa9877eece50b5177764a9360

Observation 7ee0fdb5-60bb-4d7c-9704-ab7c771308bf · inbound

Not Just What, But When: Integrating Irregular Intervals to LLM for Sequential Recommendation cites this paper.

Not Just What, But When: Integrating Irregular Intervals to LLM for Sequential Recommendation A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T11:02:13.293233Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:02:13.293233Z digest=sha256:9367cc183b205e570a63b38f32ad7a1a2fd07da0597230324bf7b05ab80a6003

Observation db38e47e-7810-4c59-8bf7-8a560f4a23e0 · inbound

Pre-trained LLMs Meet Sequential Recommenders: Efficient User-Centric Knowledge Distillation cites this paper.

Pre-trained LLMs Meet Sequential Recommenders: Efficient User-Centric Knowledge Distillation A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-11T15:16:07.430350Z

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=2026-05-09T20:26:02.884219Z digest=sha256:6f3fbe4ee5ff9a39b45614afa3b684ec0436acc84388dec75781d9a3edf07bd0

Observation 64ec1865-cc97-4f4b-b4c2-660803e8ffe1 · inbound

CFALR: Collaborative Filtering-Augmented Large Language Model for Personalized Fashion Outfit Recommendation cites this paper.

CFALR: Collaborative Filtering-Augmented Large Language Model for Personalized Fashion Outfit Recommendation A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-07-03T16:18:37.610839Z

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=2026-06-27T05:56:51.623324Z digest=sha256:07da2a0338fa943965c5a7e89de848de66e33c122c841220ebc49633da4a302e

Observation 5655b7e2-1fc8-4b57-aa2f-2fd020a0f964 · inbound

GrocLM: Grocery Category Recommendation in E-Commerce with Large Language Models cites this paper.

GrocLM: Grocery Category Recommendation in E-Commerce with Large Language Models A Bi-Step Grounding Paradigm for Large Language Models in Recommendation Systems

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-02T12:15:44.758613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T12:15:44.758613Z digest=sha256:cfd0b96ca2fd23e45946a80a5cf230bd463f24dc792c5d90ffa9c16a18e88dff