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Paper Citation Record · LEDGER

Learning from Online User Feedback for Shopping Agents

As of 17 August 2026, this Paper Citation Record lists 32 of 32 outbound references and 0 inbound Pith citation observations for arXiv:2608.11604.

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

pith.paper-citation-record.v1
2608.11604 v1

Coverage vector

measured 32 of 32 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:38:07.585126Z

measured 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

32 of 32 outbound references displayed

  • verified exact2
  • verified fuzzy4
  • unresolved25
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f4759258-f5d9-4df3-b92e-45e9bedf0baf · outbound

This paper cites Bert4rec: Sequential rec- ommendation with bidirectional encoder representations from transformer.

Learning from Online User Feedback for Shopping Agents Bert4rec: Sequential rec- ommendation with bidirectional encoder representations from transformer

Reference 1

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unresolved
no resolver link, observed 2026-08-16T00:38:07.472426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.472426Z digest=sha256:2787bc1fc18dbd3389f5bb70ae545000ef0c4fad3a8c4229b4b7af9bcb3d5099

Observation f77ad579-ddd8-4507-aa65-be93eeecf538 · outbound

This paper cites an unresolved cited work.

Learning from Online User Feedback for Shopping Agents Unresolved cited work

Reference 2

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raw_fallback, observed 2026-08-16T00:38:08.584090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T00:38:07.476508Z digest=sha256:a211c624ed92d47be67dbb53c1383e356e425d364fd1d53d9eddcfca063e027e

Observation fe4619ee-47a3-4515-8ccb-d305ee0011c6 · outbound

This paper cites BPR: Bayesian Personalized Ranking from Implicit Feedback.

Learning from Online User Feedback for Shopping Agents BPR: Bayesian Personalized Ranking from Implicit Feedback

Reference 3

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no resolver link, observed 2026-08-16T00:38:07.480194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.480194Z digest=sha256:064b1357fe7654e45dd3e71a7815b426a529f0c6618f017af25294cc29a96516

Observation 3bc51d1d-222f-4e86-bce5-4cd7f98b1dbc · outbound

This paper cites S3-rec: Self-supervised learning for sequential recommendation with mutual information maximization.

Learning from Online User Feedback for Shopping Agents S3-rec: Self-supervised learning for sequential recommendation with mutual information maximization

Reference 4

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.484121Z digest=sha256:374be29d66e7f3f24b6ee54b2f033ee375bf54bfe2674bc1833a6f06ba2da2de

Observation bf63aa3f-9890-4c3c-bea4-c321ea1c45cd · outbound

This paper cites LLaSA: Large Language and E-Commerce Shopping Assistant.

Learning from Online User Feedback for Shopping Agents LLaSA: Large Language and E-Commerce Shopping Assistant

Reference 5

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no resolver link, observed 2026-08-16T00:38:07.487634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.487634Z digest=sha256:0e32fe2a3f128d548336237d5429295e60bfb300bc8d11c8e7e53e3ccc07700e

Observation ccf909c6-b8c2-409a-8576-d41f27091aca · outbound

This paper cites A shopping agent for addressing subjective product needs.

Learning from Online User Feedback for Shopping Agents A shopping agent for addressing subjective product needs

Reference 6

Resolution
metadata mismatch
raw_fallback, observed 2026-08-16T00:38:08.378294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T00:38:07.491457Z digest=sha256:7c7e1c6b7daf880e5283b803d1e04d8adda8488b8fa9e533478b67ef35f1bc45

Observation fc95dea3-8284-4eed-9c43-db1a51a25e16 · outbound

This paper cites Language model alignment for conversational shop- ping at amazon.

Learning from Online User Feedback for Shopping Agents Language model alignment for conversational shop- ping at amazon

Reference 7

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no resolver link, observed 2026-08-16T00:38:07.495002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.495002Z digest=sha256:e0890625344c19bee5836f956b21f01e3b4a3004ac12f054ccd25161dee0f38c

Observation 00501b2d-0f5e-4990-9a56-3d02c5c3c7df · outbound

This paper cites In Ee-Peng Lim, Marianne Winslett, Mark Sanderson, Ada Wai-Chee Fu, Jimeng Sun, J.

Learning from Online User Feedback for Shopping Agents In Ee-Peng Lim, Marianne Winslett, Mark Sanderson, Ada Wai-Chee Fu, Jimeng Sun, J

Reference 8

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no resolver link, observed 2026-08-16T00:38:07.498385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.498385Z digest=sha256:27d07c3efc7d83c9269f9cb36f0ffb19f3ed834361e82978f63ec0b705e3d1b0

Observation 92a2d589-6127-4eb7-8533-0fa16971d508 · outbound

This paper cites R2ec: Towards large recommender models with reasoning.CoRR, abs/2505.16994, 2025.

Learning from Online User Feedback for Shopping Agents R2ec: Towards large recommender models with reasoning.CoRR, abs/2505.16994, 2025

Reference 9

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verified exact
raw_fallback, observed 2026-08-16T00:38:08.172989Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T00:38:07.501750Z digest=sha256:a5c36aa4d000162fb606f0f5496e6d5076fb6df74905fbee1592b2fa74b7ec3d

Observation f49bb029-e590-4678-98b5-e2d5c7662bcc · outbound

This paper cites Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation.

Learning from Online User Feedback for Shopping Agents Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation

Reference 10

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no resolver link, observed 2026-08-16T00:38:07.504889Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.504889Z digest=sha256:b5bc1a4c1af2a8e3bdf9b3c56e7e76324187b1572dfad6cdadb4f6406e9faba2

Observation f44f0bad-b49f-402a-9db1-a07c2165111f · outbound

This paper cites Let me do it for you: Towards llm empowered recommendation via tool learning.

Learning from Online User Feedback for Shopping Agents Let me do it for you: Towards llm empowered recommendation via tool learning

Reference 11

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source=pdf_text observed=2026-08-16T00:38:07.508790Z digest=sha256:fb2bea79bdb249b10077101226c38300165662b7566a59fde68349d3a3f50bdd

Observation 2690fed4-a763-40d0-8e50-206953ae9daf · outbound

This paper cites A Multi-Agent Conversational Recommender System.

Learning from Online User Feedback for Shopping Agents A Multi-Agent Conversational Recommender System

Reference 12

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no resolver link, observed 2026-08-16T00:38:07.513439Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.513439Z digest=sha256:2efbc8e0c02a1440c63724d4e883adf3512058524d282c6641479d5c849015d1

Observation d1897610-084b-4bf4-a11b-2c6b0acfb66e · outbound

This paper cites Macrec: A multi-agent collaboration framework for recommendation.

Learning from Online User Feedback for Shopping Agents Macrec: A multi-agent collaboration framework for recommendation

Reference 13

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no resolver link, observed 2026-08-16T00:38:07.517414Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.517414Z digest=sha256:2082b542edafcbe9eb4679aacf34f841cebfd204c46c20f7554bb27647cc0147

Observation 074bf6e3-31b2-4312-af43-6cecb7173cbc · outbound

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

Learning from Online User Feedback for Shopping Agents Reason4Rec: Deliberative User Preference Alignment of Large Language Models for Recommendation

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-16T00:38:07.520666Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.520666Z digest=sha256:846c29dba2d34df76219831d67ca214425a194278dc568fec6b7e62f590afac5

Observation eee97971-7eb6-447d-afcd-e2ee3ee2cee8 · outbound

This paper cites Recthinker: An agentic framework for tool-augmented reasoning in recommendation.CoRR, abs/2603.09843, 2026.

Learning from Online User Feedback for Shopping Agents Recthinker: An agentic framework for tool-augmented reasoning in recommendation.CoRR, abs/2603.09843, 2026

Reference 15

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verified exact
doi, observed 2026-08-16T00:38:07.691562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T00:38:07.524600Z digest=sha256:74f023ced93b25ff4035c6eb7c931044395116826e60ed172fcfd092df01ebd7

Observation 99816873-ccd5-4fc8-8a00-f86e12fbda30 · outbound

This paper cites Agentcf++: Memory-enhanced llm-based agents for popularity-aware cross-domain recommendations.

Learning from Online User Feedback for Shopping Agents Agentcf++: Memory-enhanced llm-based agents for popularity-aware cross-domain recommendations

Reference 16

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no resolver link, observed 2026-08-16T00:38:07.527872Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.527872Z digest=sha256:2f59e9d1e547edc21e5a389ad8c5b7a14eab306feb4a7c497de6d9cd95721bd1

Observation 8625505f-8b0f-4866-845d-3fc4eef43155 · outbound

This paper cites User behavior simulation with large language model-based agents.

Learning from Online User Feedback for Shopping Agents User behavior simulation with large language model-based agents

Reference 17

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no resolver link, observed 2026-08-16T00:38:07.531000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.531000Z digest=sha256:7b06b8cdd10a6686b9e34c16322780680dbe1248a1c7ae7ea3f24d330037e254

Observation e47c87a4-1416-4b8b-924e-a8ed988bcd58 · outbound

This paper cites SimUSER: Simulating User Behavior with Large Language Models for Recommender System Evaluation.

Learning from Online User Feedback for Shopping Agents SimUSER: Simulating User Behavior with Large Language Models for Recommender System Evaluation

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.534439Z digest=sha256:9d5fcf43e081afc9e94885510ab87ba50c5c45a19d35a8ad87c761b2032f09ea

Observation 149fee2c-831c-4b00-8036-eab471acad70 · outbound

This paper cites A llm-based controllable, scalable, human-involved user simulator framework for conversational recommender systems.

Learning from Online User Feedback for Shopping Agents A llm-based controllable, scalable, human-involved user simulator framework for conversational recommender systems

Reference 19

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.538122Z digest=sha256:0443a5f156e72d8b4c1fe60fbca1da289373ad8096c039ca18ca01995c947a6c

Observation b678ae9f-7d2f-450e-8a13-d78122357226 · outbound

This paper cites Agentcf: Collaborative learning with autonomous language agents for recommender systems.

Learning from Online User Feedback for Shopping Agents Agentcf: Collaborative learning with autonomous language agents for recommender systems

Reference 20

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no resolver link, observed 2026-08-16T00:38:07.541435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.541435Z digest=sha256:69269888cd14f0d58de81e55d758ee483db7dbb27d4b9c83fd91bae3d76d79a9

Observation 19c1879d-130d-4a15-9017-f98deba75fb7 · outbound

This paper cites Recmind: Large language model powered agent for recommendation.

Learning from Online User Feedback for Shopping Agents Recmind: Large language model powered agent for recommendation

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T00:38:08.573722Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T00:38:07.544391Z digest=sha256:487c48a6b3d4b12aa31a81286d30e0011118d4c7a23883f5d03a932ff1549fe7

Observation e6f55a26-648b-43d8-9656-d28aacf142aa · outbound

This paper cites Personax: A recommendation agent- oriented user modeling framework for long behavior sequence.

Learning from Online User Feedback for Shopping Agents Personax: A recommendation agent- oriented user modeling framework for long behavior sequence

Reference 22

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verified fuzzy
raw_fallback, observed 2026-08-16T00:38:08.563092Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T00:38:07.547517Z digest=sha256:9ad5da2e46d4dbeef86ff50b4790b24411433b8c4df0d552de61f93c0523219f

Observation f2ffc806-27d0-49bc-84a3-9ba81eee6aa5 · outbound

This paper cites Recommender ai agent: Integrating large language models for interactive recommendations.ACMTrans.Inf.

Learning from Online User Feedback for Shopping Agents Recommender ai agent: Integrating large language models for interactive recommendations.ACMTrans.Inf

Reference 23

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.550744Z digest=sha256:f667c3dbf06aea68a20394d1a2ab5a8943821e54f5b85af6dd936560ca57122d

Observation 7ca18182-26ff-430f-ada1-d4359d53767a · outbound

This paper cites Christiano, Jan Leike, Tom B.

Learning from Online User Feedback for Shopping Agents Christiano, Jan Leike, Tom B

Reference 25

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no resolver link, observed 2026-08-16T00:38:07.557409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.557409Z digest=sha256:9198fea3c3b096a203d698c7d69985d83dc657d7c542a06ff63444e7f2a3ad57

Observation 59e889c3-191a-4c53-833f-737d1a93bf0a · outbound

This paper cites Manning, Stefano Ermon, and Chelsea Finn.

Learning from Online User Feedback for Shopping Agents Manning, Stefano Ermon, and Chelsea Finn

Reference 26

Resolution
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no resolver link, observed 2026-08-16T00:38:07.560691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.560691Z digest=sha256:c6f3a4272b33d1f2b56c0a004359e8b44ea324f7cc3923e2b18d9638e08a6068

Observation c728cda4-83e8-449f-9814-2b5f668e0f3e · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

Learning from Online User Feedback for Shopping Agents DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 27

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no resolver link, observed 2026-08-16T00:38:07.564004Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.564004Z digest=sha256:e709c93017c7166c405015d51d3072b683182ef85a51f4e37a727f9d519e3092

Observation 00de486e-5583-4252-8d8f-942ff0d6a378 · outbound

This paper cites On-policy distillation of language models: Learning from self-generated mistakes.

Learning from Online User Feedback for Shopping Agents On-policy distillation of language models: Learning from self-generated mistakes

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T00:38:08.541385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T00:38:07.567302Z digest=sha256:30a9ce24136a2d8cab59916cee7bcbfd330d5d99b00bef04b1cc7393a11888c1

Observation 57eb09ca-f036-4955-9c2f-b69f3fe68ce7 · outbound

This paper cites A Survey on Knowledge Distillation of Large Language Models.

Learning from Online User Feedback for Shopping Agents A Survey on Knowledge Distillation of Large Language Models

Reference 29

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no resolver link, observed 2026-08-16T00:38:07.570503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.570503Z digest=sha256:e903d163ae5c6e6ca0c7a41218337ea95bfe13e39ea7878f2913e0d5b382ca69

Observation 5c6fc283-a67e-4387-a194-08c8d81ae6fb · outbound

This paper cites Minillm: Knowledge distillation of large language models.

Learning from Online User Feedback for Shopping Agents Minillm: Knowledge distillation of large language models

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-16T00:38:08.529417Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=pdf_text observed=2026-08-16T00:38:07.574797Z digest=sha256:1649b403bcc53407670170467c18cd483cfc0fd59daeacd3a9c83ba037edf9c2

Observation 61e79c54-e954-439c-892b-9ad692bd0dfd · outbound

This paper cites Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models.

Learning from Online User Feedback for Shopping Agents Self-Distilled Reasoner: On-Policy Self-Distillation for Large Language Models

Reference 31

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no resolver link, observed 2026-08-16T00:38:07.578156Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.578156Z digest=sha256:e5baff045058c6e85dbf7e3a29628cd8ffe8e63424c3587a9c0704429e345e1a

Observation 105b8ee6-e40c-4ee9-bd50-cd75f0a88261 · outbound

This paper cites Qwen3 Technical Report.

Learning from Online User Feedback for Shopping Agents Qwen3 Technical Report

Reference 32

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no resolver link, observed 2026-08-16T00:38:07.581950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.581950Z digest=sha256:e519fbf346d34c69908b151d18dc1b9249cb29995270a4d1dc358341cce0c34e

Observation 5bd4da44-beb7-49dd-8e62-944da58adc81 · outbound

This paper cites DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models.

Learning from Online User Feedback for Shopping Agents DeepSeek-V3.2: Pushing the Frontier of Open Large Language Models

Reference 33

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no resolver link, observed 2026-08-16T00:38:07.585126Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T00:38:07.585126Z digest=sha256:7923d5252e5bc8216df6a25705363f4e934958c18267d6481b258cf9856e1d11

Pith citing papers

No inbound Pith citation observations are available.