Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Bridging Items and Language: A Transition Paradigm for Large Language Model-Based Recommendation
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2310.06491.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-16T11:07:58.551836Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T22:23:31.451289Z
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 1a40355a-8362-42fa-9753-50c0b366cfe3 · inbound
MVIGER: Multi-View Variational Integration of Complementary Knowledge for Generative Recommender cites this paper.
MVIGER: Multi-View Variational Integration of Complementary Knowledge for Generative Recommender Bridging Items and Language: A Transition Paradigm for Large Language Model-Based Recommendation
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T22:23:31.454431Z
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.
Observation a056eec4-2f90-4f9e-b39d-b1938c85f303 · inbound
Semantic Convergence: Harmonizing Recommender Systems via Two-Stage Alignment and Behavioral Semantic Tokenization cites this paper.
Semantic Convergence: Harmonizing Recommender Systems via Two-Stage Alignment and Behavioral Semantic Tokenization Bridging Items and Language: A Transition Paradigm for Large Language Model-Based Recommendation
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T12:53:22.233729Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 252d7a36-9912-4d20-b404-fd7c8a05960f · inbound
A Survey of Foundation Model-Powered Recommender Systems: From Feature-Based, Generative to Agentic Paradigms cites this paper.
A Survey of Foundation Model-Powered Recommender Systems: From Feature-Based, Generative to Agentic Paradigms Bridging Items and Language: A Transition Paradigm for Large Language Model-Based Recommendation
Reference 111
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T11:07:58.551836Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b137e60e-425a-42f6-8ee0-02adc3eb5e5b · inbound
An Integrated Framework for Contextual Personalized LLM-Based Food Recommendation cites this paper.
An Integrated Framework for Contextual Personalized LLM-Based Food Recommendation Bridging Items and Language: A Transition Paradigm for Large Language Model-Based Recommendation
Reference 114
- Resolution
- unresolved
- no resolver link, observed 2026-08-16T10:16:09.249675Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 08977a78-b282-4bbe-afd1-4956be3d4d87 · 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 Bridging Items and Language: A Transition Paradigm for Large Language Model-Based Recommendation
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T20:32:07.897246Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.