Paper Citation Record · LEDGER

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text

As of 18 August 2026, this Paper Citation Record lists 15 of 15 outbound references and 0 inbound Pith citation observations for arXiv:2506.15833.

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

pith.paper-citation-record.v1
2506.15833 v1

Coverage vector

measured 15 of 15 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:53:56.483242Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

15 of 15 outbound references displayed

verified exact0
verified fuzzy9
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fcf898f4-09ed-4044-a7e9-9d7107e33ccf · outbound

This paper cites A bi-step grounding paradigm for large language models in recommendation systems.

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text A bi-step grounding paradigm for large language models in recommendation systems

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:58.634199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation aafd5e96-0764-4d22-a265-9520f8eb6cad · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text Direct preference optimization: Your language model is secretly a reward model

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:54.995884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 27f72de6-d020-4950-adcf-811ecb1f854f · outbound

This paper cites On Softmax Direct Preference Optimization for Recommendation.

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text On Softmax Direct Preference Optimization for Recommendation

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:55.075833Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9b677132-f849-459d-b8ba-e5191fa2dc22 · outbound

This paper cites Language models are few-shot learners.

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text Language models are few-shot learners

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:58.424670Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5de0289d-3b08-4ced-9c23-db042fe5de8f · outbound

This paper cites Tallrec: An effective and efficient tuning framework to align large language model with recommendation.

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text Tallrec: An effective and efficient tuning framework to align large language model with recommendation

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:58.186678Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 656e634a-d290-4ebf-882f-ca526570e669 · outbound

This paper cites Sprec: Self-play to debias llm-based recommendation.

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text Sprec: Self-play to debias llm-based recommendation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:57.933531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d4243e26-dda9-45d6-bf2e-85b89589fe99 · outbound

This paper cites RosePO: Aligning LLM-based Recommenders with Human Values.

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text RosePO: Aligning LLM-based Recommenders with Human Values

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:55.546384Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af612f0f-8672-4413-962a-6a5e56c11637 · outbound

This paper cites Llara: Large language-recommendation assistant.

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text Llara: Large language-recommendation assistant

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:57.690095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5852da57-f441-420c-9194-3c8ae48f0a80 · outbound

This paper cites GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation.

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text GPT4Rec: A Generative Framework for Personalized Recommendation and User Interests Interpretation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:55.761970Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6bd9bb0-e8ab-4b7f-9e31-f1f0c960c54c · outbound

This paper cites An empirical study of catastrophic forgetting in large language models during continual fine-tuning, 2025.

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text An empirical study of catastrophic forgetting in large language models during continual fine-tuning, 2025

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:57.446692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e9d1be6a-beba-4bb6-a5f5-4ee90e0c7e53 · outbound

This paper cites Do LLMs Memorize Recommendation Datasets? A Preliminary Study on MovieLens-1M.

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text Do LLMs Memorize Recommendation Datasets? A Preliminary Study on MovieLens-1M

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:56.017881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83196bb8-a5fb-4e91-be8c-5e94a2bf30d7 · outbound

This paper cites The Llama 3 Herd of Models.

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text The Llama 3 Herd of Models

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-06T23:53:56.126907Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1faac74f-de04-49e2-9e53-d8dec8001ddd · outbound

This paper cites Bandit based optimization of multiple objectives on a music streaming platform.

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text Bandit based optimization of multiple objectives on a music streaming platform

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:57.270035Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2c70a60e-f448-4954-a8ff-6b9d5ee41736 · outbound

This paper cites Self-attentive sequential recommendation.

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text Self-attentive sequential recommendation

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:57.024175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5c6c98ca-3c23-4ab3-b907-d05330c46b6f · outbound

This paper cites Multi-objective recommendation system utilizing a multi-population knowledge migration framework.

Architecture is All You Need: Improving LLM Recommenders by Dropping the Text Multi-objective recommendation system utilizing a multi-population knowledge migration framework

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:53:56.801249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

No inbound Pith citation observations are available.