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Paper Citation Record · LEDGER

Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2406.14900.

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

pith.paper-citation-record.v1
2406.14900 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T13:33:57.524747Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T04:34:35.239653Z

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 2650b1a7-653d-455e-9d73-8ee70c02c92a · 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 Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-09T13:33:57.524747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T13:33:57.524747Z digest=sha256:9027914b49b90e1fb45e46ac087d0cd2169ea0b5409d3b3c9e10aac52c3b52a7

Observation 2d2e01cc-2413-4878-88e4-44ea8530eb37 · inbound

Break the Optimization Barrier of LLM-Enhanced Recommenders: A Theoretical Analysis and Practical Framework cites this paper.

Break the Optimization Barrier of LLM-Enhanced Recommenders: A Theoretical Analysis and Practical Framework Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation

Reference 11

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T14:11:04.644310Z

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=arxiv_source observed=2026-05-09T23:20:33.252898Z digest=sha256:d675852dc94bda4f4fab4cba08b255d4442db14ec377f433333087aa16157f4d

Observation 964ba8ef-7a0c-4f52-9c34-269467363e33 · inbound

Objective Shaping with Hard Negatives: Windowed Partial AUC Optimization for RL-based LLM Recommenders cites this paper.

Objective Shaping with Hard Negatives: Windowed Partial AUC Optimization for RL-based LLM Recommenders Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:06:13.396003Z

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=2026-05-08T10:15:03.085089Z digest=sha256:78f58dd869173c8921e094611f846c41dff68ce3c08f2e5086e5afcfe3b55669

Observation a6b03f0b-920c-4ac9-86d7-f94cc67d8197 · 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 Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation

Reference 28

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:10:53.913178Z

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=2026-05-11T02:36:35.809350Z digest=sha256:9003636b1c82715636e66225004dfc89b525510dff46b66317a70f0c88de44c0

Observation 296f85a4-9d0e-417f-9ef8-ed8a90ba882d · inbound

Goal-Conditioned Supervised Learning for LLM Fine-Tuning cites this paper.

Goal-Conditioned Supervised Learning for LLM Fine-Tuning Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation

Reference 23

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:39:10.087839Z

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=2026-05-20T22:37:46.345159Z digest=sha256:3b015fdeab069316e4e7f48c8044c642351a6ffad7ba9fcaa3ad4ba71b2b8245

Observation 68256a4f-22f4-424b-865b-8b34e5305d2e · inbound

Reinforced Preference Optimization for Reasoning-Augmented Recommendations cites this paper.

Reinforced Preference Optimization for Reasoning-Augmented Recommendations Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-22T04:34:35.247882Z

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=2026-05-22T04:34:28.214871Z digest=sha256:4176807f78e3e3f78202cf3c0b71ad3522988b3a17778a96f873fdc3bfc8ed81

Observation bafbdaaa-4cbd-4aba-bb05-1f08c0ed30c2 · 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 Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation

Reference 5

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:b5fc22761eb128a97440189cb5fd2e1607a79bbe29e9cc37cfb0c28bdc9483e7

Observation ecede006-1879-4d95-977a-062da45a856e · inbound

Beyond Fixed Depths and Widths: Optimizing Textual Decoding Tries in LLM-based Generative Recommendation cites this paper.

Beyond Fixed Depths and Widths: Optimizing Textual Decoding Tries in LLM-based Generative Recommendation Decoding Matters: Addressing Amplification Bias and Homogeneity Issue for LLM-based Recommendation

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-01T20:27:57.478305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T20:27:57.478305Z digest=sha256:6e97c09cad05c7f6dece59b8c8b15e6ba50c36048625f2a15e10f37ab0d47cd5