Paper Citation Record · LEDGER

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models

As of 5 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2605.25342.

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

pith.paper-citation-record.v1
2605.25342 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-29T23:03:18.154426Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

41 of 41 outbound references displayed

verified exact2
verified fuzzy0
unresolved39
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 23182391-a704-4761-91ef-055a57c9425b · outbound

This paper cites Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback

Reference 1

Resolution: verified exact; local_arxiv, observed 2026-06-29T23:04:00.833449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ea67aa5f-da9a-423d-8be9-63c02efcc2c8 · outbound

This paper cites Multi- objective reinforcement learning with max-min criterion: A game-theoretic approach.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Multi- objective reinforcement learning with max-min criterion: A game-theoretic approach

Reference 2

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8e505a9-36fb-490b-8153-0167465dd275 · outbound

This paper cites When large language models meet personalization: Perspectives of challenges and opportunities.World wide web, 27(4):42, 2024.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models When large language models meet personalization: Perspectives of challenges and opportunities.World wide web, 27(4):42, 2024

Reference 3

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 77feb40c-c5db-43e5-9060-44d36a3e107a · outbound

This paper cites Pad: Personalized alignment of llms at decoding-time.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Pad: Personalized alignment of llms at decoding-time

Reference 4

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db5817e0-8d98-45e1-9510-93c79a83e9e1 · outbound

This paper cites Towards next-generation intelligent assistants leveraging llm techniques.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Towards next-generation intelligent assistants leveraging llm techniques

Reference 5

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a0b1b2c-1cf3-4cff-bc08-aae032c3a8cb · outbound

This paper cites Linear alignment: A closed-form solution for aligning human preferences without tuning and feedback.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Linear alignment: A closed-form solution for aligning human preferences without tuning and feedback

Reference 6

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd2b6e97-8f54-4160-a1f1-64677367f597 · outbound

This paper cites A survey on personalized alignment—the missing piece for large language models in real-world applications.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models A survey on personalized alignment—the missing piece for large language models in real-world applications

Reference 7

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e436202b-7159-4c64-aac0-b601fce570b2 · outbound

This paper cites Context steering: Controllable personalization at inference time.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Context steering: Controllable personalization at inference time

Reference 8

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b55515b9-bfbd-4e91-b71f-496438a29924 · outbound

This paper cites One-shot safety alignment for large language models via optimal dualization.Advances in Neural Information Processing Systems, 37:84350–84383, 2024.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models One-shot safety alignment for large language models via optimal dualization.Advances in Neural Information Processing Systems, 37:84350–84383, 2024

Reference 9

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d4508041-0a2c-4509-939b-f1da60ed2874 · outbound

This paper cites Aligner: Efficient alignment by learning to correct.Advances in Neural Information Processing Systems, 37:90853–90890, 2024.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Aligner: Efficient alignment by learning to correct.Advances in Neural Information Processing Systems, 37:90853–90890, 2024

Reference 10

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5540920-01a9-4848-81e7-a082e6233157 · outbound

This paper cites A survey on large language models for code generation.ACM Transactions on Software Engineering and Methodology, 35 (2):1–72, 2026.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models A survey on large language models for code generation.ACM Transactions on Software Engineering and Methodology, 35 (2):1–72, 2026

Reference 11

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 828fef3e-bb58-4e30-a87d-3d5c4014b3b0 · outbound

This paper cites Aligning to thousands of preferences via system message generalization.Advances in Neural Information Processing Systems, 37:73783–73829, 2024.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Aligning to thousands of preferences via system message generalization.Advances in Neural Information Processing Systems, 37:73783–73829, 2024

Reference 12

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1944f722-a13e-4a38-8595-a0a2afe55422 · outbound

This paper cites Deep reinforcement learning for multiobjective opti- mization.IEEE transactions on cybernetics, 51(6):3103–3114, 2020.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Deep reinforcement learning for multiobjective opti- mization.IEEE transactions on cybernetics, 51(6):3103–3114, 2020

Reference 13

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e178646a-bce6-48c1-a2ad-3277b71bce80 · outbound

This paper cites Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Security

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-06-29T23:04:00.830728Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 999ad0a5-f3b3-4afa-a821-ddd8b35bc792 · outbound

This paper cites Parm: Multi- objective test-time alignment via preference-aware autoregressive reward model.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Parm: Multi- objective test-time alignment via preference-aware autoregressive reward model

Reference 15

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4e26782f-5dde-47f4-81d6-182f92d28c74 · outbound

This paper cites The unlocking spell on base llms: Rethinking alignment via in-context learning.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models The unlocking spell on base llms: Rethinking alignment via in-context learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66c23b57-78c1-40be-990b-cfff3971e534 · outbound

This paper cites Decoding-time realignment of language models.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Decoding-time realignment of language models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed20863a-3cce-4399-b829-cb52318c2919 · outbound

This paper cites Follow-the-regularized-leader and mirror descent: Equivalence theorems and l1 regularization.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Follow-the-regularized-leader and mirror descent: Equivalence theorems and l1 regularization

Reference 18

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee59ce01-bc3b-4918-b4d1-9764dc6b101e · outbound

This paper cites Chatgpt and large language models in academia: opportunities and challenges.BioData mining, 16(1):20, 2023.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Chatgpt and large language models in academia: opportunities and challenges.BioData mining, 16(1):20, 2023

Reference 19

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85e2e05b-174e-4383-84ce-f2cc18686e5d · outbound

This paper cites Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744, 2022

Reference 20

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dfc45e31-3fbb-42fd-b322-f7d52c1588a6 · outbound

This paper cites The max-min formulation of multi-objective reinforcement learning: from theory to a model-free algorithm.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models The max-min formulation of multi-objective reinforcement learning: from theory to a model-free algorithm

Reference 21

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5f16fb2-7073-413c-92a2-03fca4a18a10 · outbound

This paper cites Personal- izing reinforcement learning from human feedback with variational preference learning.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Personal- izing reinforcement learning from human feedback with variational preference learning

Reference 22

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cb80587-033f-4763-9917-649535c7e1d3 · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Direct preference optimization: Your language model is secretly a reward model

Reference 23

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ebaf6a94-b507-47e5-b426-2605bd2919ff · outbound

This paper cites From $r$ to $q^*$: Your language model is secretly a q-function.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models From $r$ to $q^*$: Your language model is secretly a q-function

Reference 24

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 372dd6fe-b3f3-4766-8289-532b3a2f75e5 · outbound

This paper cites Rewarded soups: towards pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards.Advances in Neural Information Processing Systems, 36:71095–71134, 2023.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Rewarded soups: towards pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards.Advances in Neural Information Processing Systems, 36:71095–71134, 2023

Reference 25

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 66fbd311-ad2c-40e1-ba79-11ebb59b78fe · outbound

This paper cites Decoding-time language model alignment with multiple objectives.Advances in Neural Information Processing Systems, 37:48875–48920, 2024.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Decoding-time language model alignment with multiple objectives.Advances in Neural Information Processing Systems, 37:48875–48920, 2024

Reference 26

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation caa27965-761c-4ca3-976c-f0d0adc9cc18 · outbound

This paper cites Robust multi-objective controlled decoding of large language models.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Robust multi-objective controlled decoding of large language models

Reference 27

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 14c6ecb8-101c-47b2-8566-c15de24cdb5f · outbound

This paper cites Llms as writing assistants: Exploring perspectives on sense of ownership and reasoning.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Llms as writing assistants: Exploring perspectives on sense of ownership and reasoning

Reference 28

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 37ace087-fdf9-46cb-8adc-549e0af72f1d · outbound

This paper cites Genarm: Reward guided generation with autoregressive reward model for test-time alignment.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Genarm: Reward guided generation with autoregressive reward model for test-time alignment

Reference 29

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f81be5a8-ad75-4dde-b47a-533fd21c46e2 · outbound

This paper cites Metaaligner: Towards generalizable multi-objective alignment of language models.Advances in Neural Information Processing Systems, 37:34453–34486, 2024.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Metaaligner: Towards generalizable multi-objective alignment of language models.Advances in Neural Information Processing Systems, 37:34453–34486, 2024

Reference 30

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea303828-1877-4bdb-bb87-83e4007a83c2 · outbound

This paper cites Rewards-in-context: Multi-objective alignment of foundation models with dynamic preference adjustment.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Rewards-in-context: Multi-objective alignment of foundation models with dynamic preference adjustment

Reference 31

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 971ad244-8ea9-4013-afaf-2295f4e8598f · outbound

This paper cites Amulet: Realignment during test time for personalized preference adaptation of llms.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Amulet: Realignment during test time for personalized preference adaptation of llms

Reference 32

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 95266e71-8b40-4dd7-9455-bd0885ae7de3 · outbound

This paper cites Personalization of large language models: A survey.Transactions on Machine Learning Research, 2025.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Personalization of large language models: A survey.Transactions on Machine Learning Research, 2025

Reference 33

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 219d9b57-9456-4687-a3a4-cba93bdf8c03 · outbound

This paper cites Do llms recognize your preferences? evaluating personalized preference following in llms.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Do llms recognize your preferences? evaluating personalized preference following in llms

Reference 34

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9dd7212-9ad5-4172-8ed3-e6e9f06f7901 · outbound

This paper cites Panacea: Pareto alignment via preference adaptation for llms.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Panacea: Pareto alignment via preference adaptation for llms

Reference 35

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 346a009a-e842-4206-933b-17a98ea72fb6 · outbound

This paper cites Beyond one-preference-fits-all alignment: Multi-objective direct preference optimization.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Beyond one-preference-fits-all alignment: Multi-objective direct preference optimization

Reference 36

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 53bdb7f3-a148-4621-8d86-121e23c57da1 · outbound

This paper cites On-the-fly preference alignment via principle-guided decoding.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models On-the-fly preference alignment via principle-guided decoding

Reference 37

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff2969cc-a412-422c-a016-bfd4d796e21e · outbound

This paper cites an unresolved cited work.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Unresolved cited work

Reference 38

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6fb5ff97-c6d1-492e-83fd-ea8489a5709c · outbound

This paper cites The bench kid line ride sit.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models The bench kid line ride sit

Reference 39

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3655321-f5c7-46c0-8f39-a0c342909b12 · outbound

This paper cites an unresolved cited work.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Unresolved cited work

Reference 40

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6a73762f-de76-4601-8f8f-35d0cebc37d8 · outbound

This paper cites an unresolved cited work.

MATO: Multi-objective Personalized Alignment with Test-time Optimization for Large Language Models Unresolved cited work

Reference 41

Resolution: unresolved; no resolver link, observed 2026-06-29T23:03:18.154426Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.