Pith. sign in

Paper Citation Record · LEDGER

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems

As of 7 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 7 inbound Pith citation observations for arXiv:2505.19623.

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

pith.paper-citation-record.v1
2505.19623 v2

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:14:11.072009Z

measured 47 of 47 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 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:31:36.626072Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T22:29:09.297151Z

Reference resolution

40 of 40 outbound references displayed

  • verified exact2
  • verified fuzzy12
  • unresolved25
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation fa1d88be-00a8-46b9-b5e8-b6afe9fe5b5d · outbound

This paper cites Towards Next-Generation LLM-based Recommender Systems: A Survey and Beyond.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Towards Next-Generation LLM-based Recommender Systems: A Survey and Beyond

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:08.242844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:08.242844Z digest=sha256:8b4d9a0633c12077196c8f5d30894553dea753fff9f9493bc0ecc9ea63c7319b

Observation 5e2c44a4-0824-4836-88f7-0010c47dfa41 · outbound

This paper cites A Large-scale Dataset with Behavior, Attributes, and Content of Mobile Short-video Platform.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems A Large-scale Dataset with Behavior, Attributes, and Content of Mobile Short-video Platform

Reference 2

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:14:11.430285Z

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.

source=pdf_text observed=2026-08-07T14:14:08.308390Z digest=sha256:238024b16950d657f6a2282f3e47956841896629266978280b92a0ec203662bd

Observation e9933503-fafb-45a7-9877-d165a40bb0b4 · outbound

This paper cites A survey of graph neural networks for recommender systems: Challenges, methods, and directions.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems A survey of graph neural networks for recommender systems: Challenges, methods, and directions

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:14:12.580097Z

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.

source=pdf_text observed=2026-08-07T14:14:08.389963Z digest=sha256:28f24b1974e7861e10ad0019d470efecf8ae7eb87d771389882051638e2ff666

Observation b1052e1b-02c1-45e5-b842-a74c8b27fc7c · outbound

This paper cites Learning fine- grained user interests for micro-video recommendation.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Learning fine- grained user interests for micro-video recommendation

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:14:12.516136Z

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.

source=pdf_text observed=2026-08-07T14:14:08.485422Z digest=sha256:38b03d4af5408cac6f2f4b3afac91e96f26705b53ea422b321d22daa9a5d00a1

Observation daf91dce-7741-41f1-a2dd-0bffea46f214 · outbound

This paper cites Matrix factorization techniques for recom- mender systems.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Matrix factorization techniques for recom- mender systems

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:08.568587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:08.568587Z digest=sha256:0d494d00708ff432aad02f227eaa4056e972245502fef3842ade068e93c84d38

Observation 2fa05877-ac5e-4628-8026-e5fe7af9243b · outbound

This paper cites Collaborative filtering recom- mender systems.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Collaborative filtering recom- mender systems

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:14:12.440307Z

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.

source=pdf_text observed=2026-08-07T14:14:08.682543Z digest=sha256:9b5bf68a54d103fa22dd552d6e69b2689194a39aa3fd4c0e710111dae860d0f0

Observation 44d1c2af-3e40-474e-afd0-06937b8b9edc · outbound

This paper cites Neural collaborative filtering.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Neural collaborative filtering

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:08.780524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:08.780524Z digest=sha256:f683649ed58a5a7585b4af073eadf547b0a9429e5888936f06d933fe2573dfaa

Observation d9c8e0df-8e0c-47db-b276-35688d03be73 · outbound

This paper cites Lightgcn: Simplifying and powering graph convolution network for recommendation.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Lightgcn: Simplifying and powering graph convolution network for recommendation

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:08.872725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:08.872725Z digest=sha256:f808a43020680b112efa094b4be412cf757819150f634c84bb4ba4e075c2d426

Observation c7476dfe-5211-48f7-99a5-65d69fb966d2 · outbound

This paper cites Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Chat-REC: Towards Interactive and Explainable LLMs-Augmented Recommender System

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:08.960694Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:08.960694Z digest=sha256:b3149ef5c2429d69f358895e13cf2d9f00db28649d1bd8de3320542dca77c888

Observation ab8a4f26-85b6-4157-a8fd-270f7916d2a8 · outbound

This paper cites A survey on large language models for recommendation.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems A survey on large language models for recommendation

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:09.081381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:09.081381Z digest=sha256:a98f3ba1389224e9353f1bf926709fb1c415ef9c44925efd49f3136020f14775

Observation 5727d0f1-971a-47db-8235-9274a41ab441 · outbound

This paper cites A Survey on LLM-powered Agents for Recommender Systems.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems A Survey on LLM-powered Agents for Recommender Systems

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:09.180499Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:09.180499Z digest=sha256:5581e7d29c82617482456c2f4bc8283c49bb9e5a73a861381b78056095816bc6

Observation 010c1c7b-9a4a-4c7a-b1ea-072fdfc1578e · outbound

This paper cites Feature-based recommendation system.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Feature-based recommendation system

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:14:12.327275Z

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.

source=pdf_text observed=2026-08-07T14:14:09.277990Z digest=sha256:d4dd08b1d791c25e3b405cc5637cdfd5f4b950515fcd7d999d48dd0ae3eb8dfd

Observation 4443e640-6096-459a-bcbf-ab2e78454bfe · outbound

This paper cites AgentSociety Challenge: Designing LLM Agents for User Modeling and Recommendation on Web Platforms.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems AgentSociety Challenge: Designing LLM Agents for User Modeling and Recommendation on Web Platforms

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:09.342441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:09.342441Z digest=sha256:1c43a25cf2dca516b287474f19c02e76b48476fa904bb0c7d44346c1d39f740d

Observation 66637594-8eb4-441f-872c-840813ae97da · outbound

This paper cites Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Towards Agentic Recommender Systems in the Era of Multimodal Large Language Models

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:09.416079Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:09.416079Z digest=sha256:9f055bb41daa8db3461ba02308b0258da3233d36f5d4c07f069249dfff6c351b

Observation dbe59a5a-2608-4197-a9bd-31bdcfd2a005 · outbound

This paper cites On generative agents in recommendation.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems On generative agents in recommendation

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:14:12.237472Z

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.

source=pdf_text observed=2026-08-07T14:14:09.499972Z digest=sha256:2d12ee261b44b692a455554ca3e16a040a4bb92ee7b37a6005301d6232a5ec52

Observation bdac464b-a917-4493-83bb-96882718c033 · outbound

This paper cites Rah! recsys–assistant–human: A human-centered recommendation framework with llm agents.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Rah! recsys–assistant–human: A human-centered recommendation framework with llm agents

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:14:12.154563Z

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.

source=pdf_text observed=2026-08-07T14:14:09.619064Z digest=sha256:7a822dc822ca57fd874e7384b79ac412db4763ea765bc665da08e3e0bcb6bc49

Observation 554134c1-d464-4b45-bc65-c6f94a44c126 · outbound

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

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Agentcf: Collaborative learning with autonomous language agents for recommender systems

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:14:12.070430Z

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.

source=pdf_text observed=2026-08-07T14:14:09.712561Z digest=sha256:5086e8ad782795a63e161ce49f0a9e82b6618bd33bef3f45eb1e39cc08ba7cd6

Observation 78e4315d-9d65-468c-8b2f-64289cf7b956 · outbound

This paper cites Understanding the planning of LLM agents: A survey.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Understanding the planning of LLM agents: A survey

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:09.833983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:09.833983Z digest=sha256:6e843d93a483848dde4caa61e08f6340c9b7cf5ca16c6bf4ae6c03a77a255878

Observation 5b6a355f-fbac-412f-be5e-23547326763f · outbound

This paper cites Generative agents: Interactive simulacra of human behavior.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Generative agents: Interactive simulacra of human behavior

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:14:11.974480Z

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.

source=pdf_text observed=2026-08-07T14:14:09.936691Z digest=sha256:77800e8359565dbe3f268b772201cc5e21a7f23de3f618058d4322837e8ab1ba

Observation f79d1168-1fd3-4756-bd7f-b13738ff54aa · outbound

This paper cites Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:10.027580Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:10.027580Z digest=sha256:9ccac8b17ae3497507fb5bb35c6ff1360a54768f785c9a6758738216ad1a0820

Observation 1759b2df-81c1-45e8-bcec-7576cae84de1 · outbound

This paper cites Synergy-of-Thoughts: Eliciting Efficient Reasoning in Hybrid Language Models.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Synergy-of-Thoughts: Eliciting Efficient Reasoning in Hybrid Language Models

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:10.080248Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:10.080248Z digest=sha256:d4501218e8d57a78bed866e8b7db6f0d9c8f292574bdcb7166c7ffac898e6b4b

Observation e00d0f9d-fc6f-4219-a12f-73d1f654852f · outbound

This paper cites A survey on large language model based autonomous agents.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems A survey on large language model based autonomous agents

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:10.110481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:10.110481Z digest=sha256:14dd03ffb97e23f69c6658954c99ee216c16ee285740a5d8d52e9f9f65e0e649

Observation 2989cca9-d610-46ca-87ed-0ef92ea951f6 · outbound

This paper cites The rise and potential of large language model based agents: A survey.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems The rise and potential of large language model based agents: A survey

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:14:11.890462Z

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.

source=pdf_text observed=2026-08-07T14:14:10.153325Z digest=sha256:e48dec7582d2c377b0dea03ff1f7147780d7b34e1178d8923f3d862b506f59dd

Observation 78cee53c-3903-440a-a1fd-72a376e62cdd · outbound

This paper cites AgentSquare: Automatic LLM Agent Search in Modular Design Space.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems AgentSquare: Automatic LLM Agent Search in Modular Design Space

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:10.207509Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:10.207509Z digest=sha256:124d7d625db5f5eee6193db8fb865d395545e330dcc498d2a177430f482c3fc8

Observation 98b46f58-9f50-48ff-9706-aa42d2c946d2 · outbound

This paper cites Cognitive architec- tures for language agents.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Cognitive architec- tures for language agents

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:10.253012Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:10.253012Z digest=sha256:e25fa7e0c624508ed2e6e65358333b1119873be25fa39a671315d3d02ba448dd

Observation a4d90311-fdc6-4829-9728-63c2ba7ef544 · outbound

This paper cites Chain-of-thought prompting elicits reasoning in large language models.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Chain-of-thought prompting elicits reasoning in large language models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:10.301462Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:10.301462Z digest=sha256:2b4633d3e65f77d468a641b2d1ebe3c6b4feddb4a29107bb0b36bb1c97b3f13b

Observation c2432a9f-bf51-4886-bc50-fdee8a236ec4 · outbound

This paper cites RecMind: Large Language Model Powered Agent For Recommendation.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems RecMind: Large Language Model Powered Agent For Recommendation

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:10.358483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:10.358483Z digest=sha256:b183cb23bd8e1fe989667851f0ecf5f1f3a75359309d64e1eb6a2a243cdff657

Observation 58a9d1c8-fd16-4853-b431-de887f99f87a · outbound

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

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Macrec: A multi-agent collaboration framework for recommendation

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:14:11.802341Z

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.

source=pdf_text observed=2026-08-07T14:14:10.434269Z digest=sha256:9b2dd71a26290c98696f23f9646cd07361046fcce3d1ecfe37260062e0a1f4eb

Observation 3e868da4-0160-4d77-ba55-5fa2831dda78 · outbound

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

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Let me do it for you: Towards llm empowered recommendation via tool learning

Reference 29

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:14:11.680566Z

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.

source=pdf_text observed=2026-08-07T14:14:10.483546Z digest=sha256:f1206f35e4619747a43e483fa3e78cfa6908a4f9f560ce7abc5ac926eda58958

Observation a0533185-82bc-44b9-952a-af2472311409 · outbound

This paper cites Agentic Feedback Loop Modeling Improves Recommendation and User Simulation.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Agentic Feedback Loop Modeling Improves Recommendation and User Simulation

Reference 30

Resolution
verified exact
local_arxiv, observed 2026-08-07T14:14:11.242099Z

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.

source=pdf_text observed=2026-08-07T14:14:10.525771Z digest=sha256:2a81d8f87b1a1cf4dda4f6c06313933dd5739d97ad442549916a482e637fcdf9

Observation 7e05fc4b-c028-42c9-a736-2c599e071c89 · outbound

This paper cites Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Recommender AI Agent: Integrating Large Language Models for Interactive Recommendations

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:10.583453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:10.583453Z digest=sha256:f76de250b9c481d187b35e0a2e977cf149374bbee3f613e0e24fe807209beeaa

Observation 4c953b29-f8b9-45f5-a763-9179bbe57fd8 · outbound

This paper cites Leveraging Large Language Models in Conversational Recommender Systems.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Leveraging Large Language Models in Conversational Recommender Systems

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:10.659565Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:10.659565Z digest=sha256:d23800e0ae065f4b68333ede1229f583a8927a609519cc2e4e9709a1fc843cf3

Observation d64a9865-6680-4fb7-b6dc-0eef2cfe9ded · outbound

This paper cites Tree of thoughts: Deliberate problem solving with large language models.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Tree of thoughts: Deliberate problem solving with large language models

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:14:11.568004Z

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.

source=pdf_text observed=2026-08-07T14:14:10.704990Z digest=sha256:2b2521a75c3be469d365beb83435b722eef4299d9e49c085c7fab5388619b4d0

Observation 10bfd2f4-e755-40ea-a31b-d8eb3f3562e1 · outbound

This paper cites MetaAgents: Large Language Model Based Agents for Decision-Making on Teaming.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems MetaAgents: Large Language Model Based Agents for Decision-Making on Teaming

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:10.759097Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:10.759097Z digest=sha256:3af425610a849ab2ed76fc9d218b8a79fd0d42450ea1ca453d0196e46881e53a

Observation 485f3b14-9563-4a26-aa4d-458718e11efe · outbound

This paper cites Voyager: An Open-Ended Embodied Agent with Large Language Models.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Voyager: An Open-Ended Embodied Agent with Large Language Models

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:10.805440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:10.805440Z digest=sha256:8aff67db776ae66245132f48149798e3650526822c3169aeaa3f08983715ede9

Observation 8a5cd1e3-5b97-46ff-9310-77f618f39e68 · outbound

This paper cites React: Synergizing reasoning and acting in language models.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems React: Synergizing reasoning and acting in language models

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:10.857598Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:10.857598Z digest=sha256:a5841b73de0809cf4741e35cde7de34b3189aa2a611e41bd903429c36e18ac46

Observation 684d7074-8474-4090-9fcb-68c996109396 · outbound

This paper cites Mind2web: Towards a generalist agent for the web.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Mind2web: Towards a generalist agent for the web

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:10.909266Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:10.909266Z digest=sha256:9d8d70a84abea1dcd23de2719aad95673b0fac882f0dbf1fa709b006f9fc6ed9

Observation 6412b850-2851-4aed-8459-edce033bb0a3 · outbound

This paper cites Large Language Model based Multi-Agents: A Survey of Progress and Challenges.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems Large Language Model based Multi-Agents: A Survey of Progress and Challenges

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:10.950274Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:10.950274Z digest=sha256:ae2d0e84a1c4aff3c2a47f3e9952216390061f9f90af24a6ece3818215421bd9

Observation 9068d0da-b4d7-4ccb-bf14-e7ee678d260b · outbound

This paper cites MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T14:14:10.999269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:10.999269Z digest=sha256:4911ad6c14638b0e3e9db58d1ad2decf26bf936f55b9b694a671b2300c95ba18

Observation 402f55dd-efd0-40e9-acfe-2f4b8e1a49da · outbound

This paper cites AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors.

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors

Reference 40

Resolution
malformed identifier
no resolver link, observed 2026-08-07T14:14:11.072009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:14:11.072009Z digest=sha256:8545d0c9e39fa8d0b97ee8e521e15bc24720db8eed3d306f276ab45f1ec52a7c

Pith citing papers

Observation 469d1a14-96ff-4fde-96de-464d916e8a85 · inbound

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

Reason-to-Recommend: Using Interaction-of-Thought Reasoning to Enhance LLM Recommendation AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T10:31:36.626072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:31:36.626072Z digest=sha256:6416c04b5baf540c1ce190c7e8a019e55371b431df9dda5fa6f31ddd61b484f8

Observation 6ef27738-b07a-4b3b-a5f3-252b7439d904 · inbound

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

RecoWorld: Building Simulated Environments for Agentic Recommender Systems AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-04T17:56:38.832953Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T17:56:38.832953Z digest=sha256:9dcda1d8285b67b8abe3538402d16e3d84a189b3e6299273413f4fd879e9068a

Observation 762ae0d3-e784-4f3c-a049-337021a54254 · inbound

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

RecRM-Bench: Benchmarking Multidimensional Reward Modeling for Agentic Recommender Systems AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-13T05:07:17.493813Z

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.

source=pdf_text observed=2026-05-13T05:04:08.454422Z digest=sha256:6c9ed3e6c6bcf2bb5f3a396bc75b66adac8e727b9f061fbcc45378d9f887d42f

Observation 7e622604-674d-43ef-960e-dea32979f491 · 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 AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-20T22:29:09.299227Z

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.

source=pdf_text observed=2026-05-20T22:27:16.974169Z digest=sha256:0e8dd78a156b5af3d7b8f76bba9513618c8e48cb9747774b5395c673ce10613a

Observation a710db35-3b65-4fe4-8fa9-81fe76eb1971 · inbound

APeB: Benchmarking Personalization Ability of Large Language Model Agents cites this paper.

APeB: Benchmarking Personalization Ability of Large Language Model Agents AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems

Reference 8

Resolution
unresolved
no resolver link, observed 2026-07-12T04:26:24.074391Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T04:26:24.074391Z digest=sha256:5f691f193ec8301cbd52437582686c0a4b466349451e378a5452f18a191d164f

Observation 529d8338-9028-43f4-94e0-d1fa9e98302e · inbound

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

Autonomous Information Seeking: A Roadmap for Agentic Recommender Systems AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems

Reference 140

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-11T19:14:13.105401Z digest=sha256:aaab7b6c7f0298cc12a06e6f1c2bb967f97bca1b56fefdfb9fac9c0c1507cc09

Observation 2eaa5503-accf-40d0-baa6-04bfe0564fff · inbound

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

Attacking and Defending Multi-Agent Collaborative Filtering Systems Through Connectivity AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-05T22:07:42.181996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T22:07:42.181996Z digest=sha256:23cc5479d2aef6aac5259eaa2a61a6cbee24f7eb3e2d2d102680e147f838e3e2