Paper Citation Record · LEDGER

MOA: Multi-Objective Alignment for Role-Playing Agents

As of 7 August 2026, this Paper Citation Record lists 10 of 10 outbound references and 3 inbound Pith citation observations for arXiv:2512.09756.

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

pith.paper-citation-record.v1
2512.09756 v2

Coverage vector

measured 10 of 10 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-16T23:15:47.967612Z

measured 13 of 13 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 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T14:37:22.098880Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-06-29T21:53:59.312224Z

Reference resolution

10 of 10 outbound references displayed

verified exact3
verified fuzzy2
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch5

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 518ad879-a5f5-4e0e-a8ad-598f8972b151 · outbound

This paper cites Reasoning Does Not Necessarily Improve Role-Playing Ability.

MOA: Multi-Objective Alignment for Role-Playing Agents Reasoning Does Not Necessarily Improve Role-Playing Ability

Reference 1

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T23:18:40.161607Z

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 359fa106-2e39-41c9-aa5f-905b4c4cf27d · outbound

This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

MOA: Multi-Objective Alignment for Role-Playing Agents Understanding R1-Zero-Like Training: A Critical Perspective

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T23:18:40.156822Z

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 42089be4-838a-4128-9a55-5f8c9d5237fb · outbound

This paper cites Large Language Models are Superpositions of All Characters: Attaining Arbitrary Role-play via Self-Alignment.

MOA: Multi-Objective Alignment for Role-Playing Agents Large Language Models are Superpositions of All Characters: Attaining Arbitrary Role-play via Self-Alignment

Reference 3

Resolution: verified exact; arxiv_id, observed 2026-05-16T23:18:40.182054Z

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 4a370a78-f928-45fd-aae5-9ffd15140fd8 · outbound

This paper cites PersonaGym: Evaluating Persona Agents and LLMs.

MOA: Multi-Objective Alignment for Role-Playing Agents PersonaGym: Evaluating Persona Agents and LLMs

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T23:18:40.177597Z

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 55fa22d1-e2aa-436f-8b49-a2a4e1f10afd · outbound

This paper cites Character-LLM: A Trainable Agent for Role-Playing.

MOA: Multi-Objective Alignment for Role-Playing Agents Character-LLM: A Trainable Agent for Role-Playing

Reference 5

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T23:18:40.152667Z

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 d8f481df-406a-44b2-8ce7-2945308d9dbc · outbound

This paper cites Kimi k1.5: Scaling Reinforcement Learning with LLMs.

MOA: Multi-Objective Alignment for Role-Playing Agents Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-16T23:18:40.165466Z

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 dcda259f-a4ab-4125-aa8d-6007c46bcc83 · outbound

This paper cites Qwen3 Technical Report.

MOA: Multi-Objective Alignment for Role-Playing Agents Qwen3 Technical Report

Reference 7

Resolution: metadata mismatch; local_arxiv, observed 2026-05-16T23:18:40.173658Z

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 1e660e78-f7e9-4b13-bfb7-8f6b9f82472e · outbound

This paper cites TTRL: Test-Time Reinforcement Learning.

MOA: Multi-Objective Alignment for Role-Playing Agents TTRL: Test-Time Reinforcement Learning

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-05-16T23:18:40.169647Z

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 7db3c2a6-e463-4d96-b04c-0de4607971a7 · outbound

This paper cites Given a group of G rollouts and D dimensions, the rollouts will be optimized for D iterations.

MOA: Multi-Objective Alignment for Role-Playing Agents Given a group of G rollouts and D dimensions, the rollouts will be optimized for D iterations

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:21:22.590248Z

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 0c06977a-0542-43e4-b0f1-006aa9be1e74 · outbound

This paper cites Answer") ver- sus refusal situations (.

MOA: Multi-Objective Alignment for Role-Playing Agents Answer") ver- sus refusal situations (

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-16T23:21:22.587208Z

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.

Pith citing papers

Observation a32bee59-d90b-4db0-8f5e-2f37d82fcb78 · inbound

CustomerSim: Benchmarking and Aligning Multimodal Language Models as Retail User Simulators cites this paper.

CustomerSim: Benchmarking and Aligning Multimodal Language Models as Retail User Simulators MOA: Multi-Objective Alignment for Role-Playing Agents

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-12T08:41:24.114272Z

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 40c37221-35a8-44ce-ad23-c62e8c8801f8 · inbound

CustomerSim: Benchmarking and Aligning Multimodal Language Models as Retail User Simulators cites this paper.

CustomerSim: Benchmarking and Aligning Multimodal Language Models as Retail User Simulators MOA: Multi-Objective Alignment for Role-Playing Agents

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T14:37:22.098880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3337eea-4bc7-4bb8-82b6-4682792ee3b0 · inbound

CRPO: Character-centric Group Relative Policy Optimization for Role-aware Reasoning in Role-playing Agents cites this paper.

CRPO: Character-centric Group Relative Policy Optimization for Role-aware Reasoning in Role-playing Agents MOA: Multi-Objective Alignment for Role-Playing Agents

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-06-29T21:53:59.313474Z

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.