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Paper Citation Record · LEDGER

STAR: A Simple Training-free Approach for Recommendations using Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.16458.

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

pith.paper-citation-record.v1
2410.16458 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:29:40.712090Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T03:55:56.354074Z

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 1cdb6a71-b397-44b4-950c-bafcb806b5e5 · inbound

VRAgent-R1: Boosting Video Recommendation with MLLM-based Agents via Reinforcement Learning cites this paper.

VRAgent-R1: Boosting Video Recommendation with MLLM-based Agents via Reinforcement Learning STAR: A Simple Training-free Approach for Recommendations using Large Language Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T20:29:40.712090Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:29:40.712090Z digest=sha256:d2476c261064019d2716fcabe5f192dd4a9e68b357e9ddc5635d5d2e99b4ceb0

Observation fa963140-fa53-4e63-9cd8-796ae4d7ab75 · inbound

RRCM: Ranking-Driven Retrieval over Collaborative and Meta Memories for LLM Recommendation cites this paper.

RRCM: Ranking-Driven Retrieval over Collaborative and Meta Memories for LLM Recommendation STAR: A Simple Training-free Approach for Recommendations using Large Language Models

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:10:53.918389Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T02:36:35.809350Z digest=sha256:9a3bd9719f60e1d2c46100d457a85623070f85c29c4875022aabe30b5ebe87ca

Observation 1d83786e-a341-4f57-9908-cabbfb7815d7 · inbound

RcLLM: Accelerating Generative Recommendation via Beyond-Prefix KV Caching cites this paper.

RcLLM: Accelerating Generative Recommendation via Beyond-Prefix KV Caching STAR: A Simple Training-free Approach for Recommendations using Large Language Models

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:55:56.356332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T02:07:29.141193Z digest=sha256:cdc5181d8cc8a6906c082c02db8a03191b96ca37f260273c73b079b24ead09dc

Observation c85ef1c9-fb64-4388-a646-5d4f082a822f · inbound

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation cites this paper.

LBR: Towards Mitigating Length Bias in Large Language Models for Recommendation STAR: A Simple Training-free Approach for Recommendations using Large Language Models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-07-11T20:29:43.700229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-11T20:29:43.700229Z digest=sha256:308818e670714e169f57e80a24381e61b1f38d3dbeb31f81809076493b218eca