Paper Citation Record · LEDGER

Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2503.16734.

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

pith.paper-citation-record.v1
2503.16734 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T22:07:42.038221Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 4c82896c-10b4-47a0-918e-0b4aafa55f7a · inbound

RecoWorld: Building Simulated Environments for Agentic Recommender Systems cites this paper.

RecoWorld: Building Simulated Environments for Agentic Recommender Systems Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T17:56:38.786978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 335effd0-c58b-45b1-8773-219a1ddc6801 · inbound

TRACE: A Conversational Framework for Sustainable Tourism Recommendation with Agentic Counterfactual Explanations cites this paper.

TRACE: A Conversational Framework for Sustainable Tourism Recommendation with Agentic Counterfactual Explanations Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-10T14:40:32.707859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 00def110-0162-4fff-b7bc-e0dcb9d87f94 · inbound

MEG-RAG: Quantifying Multi-modal Evidence Grounding for Evidence Selection in RAG cites this paper.

MEG-RAG: Quantifying Multi-modal Evidence Grounding for Evidence Selection in RAG Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:56:12.177338Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c7d23993-ee4f-40d3-b1a2-4c9b5740c659 · inbound

Factorized Latent Reasoning for LLM-based Recommendation cites this paper.

Factorized Latent Reasoning for LLM-based Recommendation Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-12T09:21:25.793005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cfdd95a7-e8fc-45db-a81d-dc5a308b883b · inbound

Purifying Multimodal Retrieval: Fragment-Level Evidence Selection for RAG cites this paper.

Purifying Multimodal Retrieval: Fragment-Level Evidence Selection for RAG Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-12T10:11:28.110259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 32d111d8-e8db-45ec-b401-184e70fbe060 · inbound

Fair Agents: Balancing Multistakeholder Alignment in Multi-Agent Personalization Systems cites this paper.

Fair Agents: Balancing Multistakeholder Alignment in Multi-Agent Personalization Systems Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:35:40.953202Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d434c5d9-2684-433e-a6ff-33c5dcb44242 · inbound

Skill-CMIB: Multimodal Agent Skill for Consistent Action via Conditional Multimodal Information Bottleneck cites this paper.

Skill-CMIB: Multimodal Agent Skill for Consistent Action via Conditional Multimodal Information Bottleneck Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 95

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T08:01:28.202507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 326ec5f8-daa8-46f8-bfaf-296000cdc477 · inbound

OLIVIA: Online Learning via Inference-time Action Adaptation for Decision Making in LLM ReAct Agents cites this paper.

OLIVIA: Online Learning via Inference-time Action Adaptation for Decision Making in LLM ReAct Agents Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 100

Resolution: metadata mismatch; arxiv_id, observed 2026-05-13T02:27:07.221788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7b39863a-f738-4636-b733-5e73b40a17da · inbound

RecRM-Bench: Benchmarking Multidimensional Reward Modeling for Agentic Recommender Systems cites this paper.

RecRM-Bench: Benchmarking Multidimensional Reward Modeling for Agentic Recommender Systems Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-13T05:07:17.496339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 1719341a-ef87-41cb-8c98-9812995fcc8b · inbound

F-GRPO: Factorized Group-Relative Policy Optimization for Unified Candidate Generation and Ranking cites this paper.

F-GRPO: Factorized Group-Relative Policy Optimization for Unified Candidate Generation and Ranking Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-14T19:52:52.358216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a6826159-a71e-4792-81df-475bba00b3e5 · inbound

SmartWalkCoach: An AI Companion for End-to-End Walking Guidance, Motivation, and Reflection cites this paper.

SmartWalkCoach: An AI Companion for End-to-End Walking Guidance, Motivation, and Reflection Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 40

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T20:45:03.275665Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f5d34ab0-ae3f-483d-8373-bce7adc51295 · inbound

RecoAtlas: From Semantic Plausibility to Set-Level Utility in LLM Recommendation Agents cites this paper.

RecoAtlas: From Semantic Plausibility to Set-Level Utility in LLM Recommendation Agents Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-20T22:29:09.311662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a135567a-c9ea-4375-b713-7cb03e314083 · inbound

Do Recommendation Algorithms Work When Users Are LLM Agents? A Case Study on Moltbook cites this paper.

Do Recommendation Algorithms Work When Users Are LLM Agents? A Case Study on Moltbook Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-06-30T16:24:57.377156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 848212e0-8452-4101-af09-cabf25cd5f92 · inbound

Do Recommendation Algorithms Work When Users Are LLM Agents? A Case Study on Moltbook cites this paper.

Do Recommendation Algorithms Work When Users Are LLM Agents? A Case Study on Moltbook Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 28

Resolution: unresolved; no resolver link, observed 2026-07-13T07:14:21.482287Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7916742b-f54b-48aa-8547-379bbd7f6c3b · inbound

Beyond Item Order: Temporal Gap Tokenization for Generative Recommendation with Semantic IDs cites this paper.

Beyond Item Order: Temporal Gap Tokenization for Generative Recommendation with Semantic IDs Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-11T23:02:18.007239Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation de24e927-d170-4cd1-8bcb-9848ae75c9f1 · inbound

Autonomous Information Seeking: A Roadmap for Agentic Recommender Systems cites this paper.

Autonomous Information Seeking: A Roadmap for Agentic Recommender Systems Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 75

Resolution: unresolved; no resolver link, observed 2026-07-11T19:14:13.105401Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e20767b8-5b8a-4fa4-8312-cce478c7d747 · inbound

Harness Handbook: Making Evolving Agent Harnesses Readable,Navigable, and Editable cites this paper.

Harness Handbook: Making Evolving Agent Harnesses Readable,Navigable, and Editable Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T05:40:33.703390Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 336d7cae-21e2-460b-9114-13c3f1ab7b12 · inbound

Three-Body Alignment: Aligning Chess Agent with Human Reasoning through Reranked Rationale cites this paper.

Three-Body Alignment: Aligning Chess Agent with Human Reasoning through Reranked Rationale Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-01T06:10:10.859399Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e5bb53bb-de0b-443c-a726-79d86b5d94fa · inbound

A Position Paper on Recommender Systems in the Era of Autonomous Agents cites this paper.

A Position Paper on Recommender Systems in the Era of Autonomous Agents Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-01T20:37:15.441480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00d221a3-45b2-4756-94b0-8a96ff3bc536 · inbound

A Self-Triggered Agentic Push Recommendation System cites this paper.

A Self-Triggered Agentic Push Recommendation System Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T17:56:23.637340Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9e9a32d8-801a-4106-80f1-a2fcb03e24bd · inbound

Attacking and Defending Multi-Agent Collaborative Filtering Systems Through Connectivity cites this paper.

Attacking and Defending Multi-Agent Collaborative Filtering Systems Through Connectivity Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-05T22:07:42.038221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.