Pith. sign in

Paper Citation Record · LEDGER

AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems

As of 14 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 2026-08-14T06:32:32.682623+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=sha256:4a3be5383bbc81e5a189dd5ca17d0f61f2e48fa43b9e662b9181654b43e8179e

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:14:08.308390Z digest=sha256:2a3b1acd6dab3ef576803761b8746ce3f3b563a406283178d4a2a352e92dc1d3

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:14:08.389963Z digest=sha256:0a3c5a1fe5afcd40c32379c200c1b3d0ec3d2d4c40bb28b02ddff32532209f04

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:14:08.485422Z digest=sha256:96cf9499bfa85b8520b585fefce0651ca8418981aea182d3a6a62c658055a22c

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=sha256:59d533a2527a52d2456072773753a10fda0258f3ed3fe85b927c9cceaac49a46

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:14:08.682543Z digest=sha256:1508324a2d25ca26841614fbc6e63c2fe5572cab2b4c802b3e26160f1ec8ee3e

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=sha256:84a69dff5bd1c07769c107440e6b75efcad3d77adc21af1447bb2917c1f91122

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=sha256:3adea03cf2e9a475dc4b1a3056ec2511bbeccce2896cbda9d0363adf245002d1

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:cf545b8d72a265f803643d3b53b8007dc4cae3d9d3e20ffa503418e15c25c6b3

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=sha256:883a77f1e8b0961d333abdabdcb7f5e5ef34cee4ecdaed7ee6701b21c866f242

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=sha256:9847cc19ba04562e3ccd2050ba853d5a5877cc54d46ac2de30b1cb2392eb27a3

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:14:09.277990Z digest=sha256:8bf43e183dd37f9a7abab5184de51c5725e6912ed49043ca265c6eda92979be4

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=sha256:04ddf8b07722267cec5ee41cfb7881c0f6c2d41c6fde9f004ce1770bae2e709e

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=sha256:8aab02b49b3ead36b4deeea9eee50fdc188c96d09797e33ee91914649efd39d2

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:14:09.499972Z digest=sha256:e408d1ca5911515e88f4095c6057350eb9b45b124d54f3382b027e7d2fffffd7

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:14:09.619064Z digest=sha256:68d39d13269ef48c6d4b0f06ba2e5f24e8082c78e9d52fb1115151f498823385

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:14:09.712561Z digest=sha256:935aad621686fab3c62bf8cf70f4e4adda173cdef48259d66450427dd48d5886

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=sha256:1a7e6631d29ee6541aa2cb67d6c85bf49b0dff33ab32ebbb9c197e0d21198821

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:14:09.936691Z digest=sha256:8c2b2c776087f06b8e859f3a734e1bd1959a90d158ad721e262bbc858832afad

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=sha256:8075879e0484b5dff233edaa4b31fea99f41a3c4ecdcfbfeb117af808d0800f5

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=sha256:77b56ba58e1b50db2aca0f2eadc622f3091016d8cc0c175aae08bb523aae428a

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=sha256:29505e330aefbfa5c75ab19a7363bd780b3c0ad8dfc26e0e92cb96fee81b950f

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:14:10.153325Z digest=sha256:2493f2949230f37bdaaf90fe9a9439f41378f65c4198e06f2d5c49aa1a58ae91

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:c16514b2c93ba7d039a8f1b4cb08f72948858b79c1aad1e3866268e304759f8e

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=sha256:1a7e2dea67274e9f6433531ef97f26d7e156cc7626480d5889c6272745d1a3ed

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=sha256:02a96bc45abe0d7d152e7a3f6fb7f569429318d19a1ecf95f3af928de3323c34

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:eea37167f9a81b0bb9f09f7400d8bdffd07d09fd7a9f40cc82cee9ebe69cf76c

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:14:10.434269Z digest=sha256:be6f09b3a6200369156ced8f4a6dc338503b03a5ee7493519b0e709b22604dea

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:14:10.483546Z digest=sha256:6ba042cb75e36808cca7d0a78375a7e9620adc5a49edae01e86dca534913ed8b

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:14:10.525771Z digest=sha256:5f2e28a4dfc909d2e41adfbe7c2f20f7d2746f8341a88ed055eef658433743e4

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=sha256:795d6809925e9119f3a3ed72bf177479fb7e3ec88f57b154e8cdfd8000a81241

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:b1aa9a075a5ed32f7804e628345474d373dce1856493a41f4932d2b38f7e8e85

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-08-07T14:14:10.704990Z digest=sha256:c8bab4c7050dd1773978a78ccdad6a8fbb67b274f20dfedd9447a9f5e1bc64ba

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:e06fdaecfab43ada5f7900df83245f96c65060aa84395745c8a5140ff22eae7d

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=sha256:702a8dd18e1887feb12abf115ed83677b4d5c3df973f575eeb6c704754c5350e

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:da06872ddf6d5aa027e85ccd15bbbf30d53e7d33d3ac8ee3e2b3842d32bb3a9a

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=sha256:1f5a194bd7db7ca01afa2a39e0ab6648102f8d7a4a70185412840c7e1df91216

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=sha256:9fe0a5def973a4a43ae832e84958f57f204a7368c5c920a1d7c2aed4ff8fcb5c

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=sha256:426a6e6fc56137c17499407dd955ec1870cc3a1e6aa6f53f7d75e08a684fc32d

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:f866d198d92b4a3f4d6b92546ce8a20b379154030a73ba8194064098df0eaa97

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=sha256:298e4b07d89969b6714df82cdd329455afec30ce7e5aa7c603545b845310c8f0

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=sha256:6b3ef8fc287947109cbb33897c1b8de6c0c62ec5b2e680dd32a013c201576f81

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-13T05:04:08.454422Z digest=sha256:f3fd9a14abb50adc299a8045b57753fb95ec2a89d121bde0cfc67c7da96c0927

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 2026-08-14T06:32:32.682623+00:00.

source=pdf_text observed=2026-05-20T22:27:16.974169Z digest=sha256:0d6c0edf6ac9863b325f1ec37f7ebae52d874d10f3d38581173abb5a02160bb5

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=sha256:2e053e04ec2221f7ed2a6e47ec64546ff71dd254d53acd1da461cc0f3e0a4a27

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:f63669b12954b7446841b8ee5b52b69e6b80f7481ed8ece3f679faa7232e0e66

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:b90d90afbb95ec74eb104a9df00754c30409c1075cded5882152ef02dab1c22f