Paper Citation Record · LEDGER

APeB: Benchmarking Personalization Ability of Large Language Model Agents

As of 7 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 1 inbound Pith citation observation for arXiv:2607.03162.

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

pith.paper-citation-record.v1
2607.03162 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T04:26:24.074391Z

measured 32 of 32 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T12:23:46.965989Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

31 of 31 outbound references displayed

verified exact0
verified fuzzy0
unresolved31
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f36e8105-ebcc-453b-9b13-0eabe99137a5 · outbound

This paper cites Hista and Numca: Estimate State Value Effectively for LLM Reinforcement Learning.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Hista and Numca: Estimate State Value Effectively for LLM Reinforcement Learning

Reference 1

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 82467b3c-8746-4b56-9e2f-a0cfbe2f45bc · outbound

This paper cites OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment.

APeB: Benchmarking Personalization Ability of Large Language Model Agents OneRec: Unifying Retrieve and Rank with Generative Recommender and Iterative Preference Alignment

Reference 2

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e4ddd04b-98c0-4221-9dd9-661dacaa5f52 · outbound

This paper cites an unresolved cited work.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Unresolved cited work

Reference 3

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0ae9dc4-c6f5-400d-bf6c-0498be3942ea · outbound

This paper cites an unresolved cited work.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Unresolved cited work

Reference 4

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23bab859-6e60-4d9b-9bc1-0f29078fc8a3 · outbound

This paper cites Evaluating Very Long-Term Conversational Memory of LLM Agents.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Evaluating Very Long-Term Conversational Memory of LLM Agents

Reference 5

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fe437d5-2378-4e4e-8939-38be177fe612 · outbound

This paper cites MemGPT: Towards LLMs as Operating Systems.

APeB: Benchmarking Personalization Ability of Large Language Model Agents MemGPT: Towards LLMs as Operating Systems

Reference 6

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9703bdcf-4097-4a01-b2d1-b5e031f38faa · outbound

This paper cites Shopping Queries Dataset: A Large-Scale ESCI Benchmark for Improving Product Search.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Shopping Queries Dataset: A Large-Scale ESCI Benchmark for Improving Product Search

Reference 7

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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

This paper cites AgentRecBench: Benchmarking LLM Agent-based Personalized Recommender Systems.

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.

Observation 6a4074b9-f1d4-4929-b17c-4e110ef3efb6 · outbound

This paper cites InProceedings of the 32nd ACM Inter- national Conference on Information and Knowledge Management, CIKM ’23, page 5407–5411.

APeB: Benchmarking Personalization Ability of Large Language Model Agents InProceedings of the 32nd ACM Inter- national Conference on Information and Knowledge Management, CIKM ’23, page 5407–5411

Reference 9

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d744202d-e589-4a13-9129-7edb23f2e9bd · outbound

This paper cites On Information Self-Locking in Reinforcement Learning for Active Reasoning of LLM agents.

APeB: Benchmarking Personalization Ability of Large Language Model Agents On Information Self-Locking in Reinforcement Learning for Active Reasoning of LLM agents

Reference 10

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd2006ad-cfd9-47f9-8ea6-ba608f3d0766 · outbound

This paper cites When deployed as a ReAct agent, we reduce the reasoning budget to 1024 tokens to ensure practical efficiency.

APeB: Benchmarking Personalization Ability of Large Language Model Agents When deployed as a ReAct agent, we reduce the reasoning budget to 1024 tokens to ensure practical efficiency

Reference 11

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 02fe168b-b982-41e7-a661-0882697e85ed · outbound

This paper cites an unresolved cited work.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Unresolved cited work

Reference 12

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83566e84-d942-4d06-8646-2b7f453c6631 · outbound

This paper cites an unresolved cited work.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Unresolved cited work

Reference 13

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee245c44-f833-4507-9207-ab1174b7cc09 · outbound

This paper cites Other settings remain default.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Other settings remain default

Reference 14

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a1a3dd3-c22d-4ff6-8ef8-5f5ee4f966ae · outbound

This paper cites an unresolved cited work.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Unresolved cited work

Reference 15

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0b5f57f5-b7a9-4c14-a9c2-72b37d70e785 · outbound

This paper cites an unresolved cited work.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Unresolved cited work

Reference 16

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ae6a88bf-ad5b-4827-b12b-ab25d31e87cb · outbound

This paper cites an unresolved cited work.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Unresolved cited work

Reference 17

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 804419e2-f97d-4cad-9114-d15778ea9631 · outbound

This paper cites an unresolved cited work.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Unresolved cited work

Reference 18

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation af34c766-3996-4e72-9a12-d564117b16c8 · outbound

This paper cites C.1 Additional Model-Family Results Table 12 provides the appendix position for ad- ditional model-family runs that extend the main result structure in Table 2.

APeB: Benchmarking Personalization Ability of Large Language Model Agents C.1 Additional Model-Family Results Table 12 provides the appendix position for ad- ditional model-family runs that extend the main result structure in Table 2

Reference 19

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 50888c3a-8dc1-4725-80be-b78e64e60342 · outbound

This paper cites an unresolved cited work.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Unresolved cited work

Reference 20

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 42e6caf7-abbb-497f-95c6-5b7d942c66e5 · outbound

This paper cites an unresolved cited work.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Unresolved cited work

Reference 21

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45956be4-39b0-48cf-8636-eba32a53c715 · outbound

This paper cites an unresolved cited work.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Unresolved cited work

Reference 22

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation df3744d4-9bc5-4f43-9ebc-ab64e8f1d27c · outbound

This paper cites an unresolved cited work.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Unresolved cited work

Reference 23

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 930c8fbc-51e1-4c0e-87ea-edd621d0f41c · outbound

This paper cites As these contents exceed prompt- length limits, they are organized in a fixed schema and stored in a retrieval database, which the agent queries via this tool (see Ap- pendix C.6).

APeB: Benchmarking Personalization Ability of Large Language Model Agents As these contents exceed prompt- length limits, they are organized in a fixed schema and stored in a retrieval database, which the agent queries via this tool (see Ap- pendix C.6)

Reference 24

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 58cbdbd9-c662-4141-9a8c-7892486423f7 · outbound

This paper cites Each query returns the top-3 relevant text chunks.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Each query returns the top-3 relevant text chunks

Reference 25

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4ba69e3-966f-459f-9a3f-e6d03790f285 · outbound

This paper cites an unresolved cited work.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Unresolved cited work

Reference 26

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f32c4f06-009a-4e8d-818e-3b9e29ddc103 · outbound

This paper cites an unresolved cited work.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Unresolved cited work

Reference 27

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c25bb309-75a1-45b9-98fa-d02135ea57ce · outbound

This paper cites In Table 20, we report Hit@1 results when vary- ing the retrieval backend.

APeB: Benchmarking Personalization Ability of Large Language Model Agents In Table 20, we report Hit@1 results when vary- ing the retrieval backend

Reference 28

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a7523657-838c-4f87-8c85-21dd24cf5ff8 · outbound

This paper cites Please distinguish them and list them out clearly.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Please distinguish them and list them out clearly

Reference 29

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 709ec71a-8bd0-4e43-bdfa-5f1f98bbda6b · outbound

This paper cites Notice that common features are not necessarily to be ranked higher, because details always matter to the user.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Notice that common features are not necessarily to be ranked higher, because details always matter to the user

Reference 30

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1297b855-bcdc-47a8-b425-42b412c2f67f · outbound

This paper cites Finally, you should output a rank for all candidates based on how much it is suitable for the user.

APeB: Benchmarking Personalization Ability of Large Language Model Agents Finally, you should output a rank for all candidates based on how much it is suitable for the user

Reference 31

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

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 64dd2e59-95a1-412f-8b1c-f914f1366a7a · inbound

Fewer Clarifications, Better Code: Benchmarking Cross-Session Personalized Ambiguity Adaptation in Coding Assistants cites this paper.

Fewer Clarifications, Better Code: Benchmarking Cross-Session Personalized Ambiguity Adaptation in Coding Assistants APeB: Benchmarking Personalization Ability of Large Language Model Agents

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-01T12:23:46.965989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.