35 lines
2 KiB
Markdown
35 lines
2 KiB
Markdown
---
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type: source
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title: "A Survey on Personalized and Pluralistic Preference Alignment in Large Language Models"
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author: "Various (arXiv 2504.07070)"
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url: https://arxiv.org/abs/2504.07070
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date: 2025-04-01
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domain: ai-alignment
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secondary_domains: []
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format: paper
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status: unprocessed
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priority: medium
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tags: [pluralistic-alignment, personalization, survey, taxonomy, RLHF, DPO]
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---
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## Content
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Survey presenting taxonomy of preference alignment techniques:
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- Training-time methods (RLHF variants, DPO variants, mixture approaches)
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- Inference-time methods (steering, prompting, retrieval)
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- User-modeling methods (profile-based, clustering, prototype-based)
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Abstract only accessible via WebFetch. Full paper needed for comprehensive extraction.
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## Agent Notes
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**Why this matters:** First comprehensive survey of the personalized/pluralistic alignment subfield. Useful for understanding the full landscape of approaches beyond the specific mechanisms we've found.
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**What surprised me:** The taxonomy exists — the field has matured enough for a survey paper. This confirms the "impossibility to engineering" transition.
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**What I expected but didn't find:** Full paper content not accessible via abstract page. Need to fetch the HTML version.
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**KB connections:** Meta-level support for the pattern that pluralistic alignment is transitioning from theory to engineering.
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**Extraction hints:** The taxonomy itself may be worth extracting as a claim about the maturation of the field.
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**Context:** April 2025 preprint. Survey format suggests the field has reached sufficient critical mass for systematization.
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## Curator Notes (structured handoff for extractor)
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PRIMARY CONNECTION: pluralistic alignment must accommodate irreducibly diverse values simultaneously rather than converging on a single aligned state
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WHY ARCHIVED: Survey confirming the field has matured enough for systematization — evidence that the impossibility-to-engineering transition is real
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EXTRACTION HINT: Need to fetch full paper for comprehensive extraction. The taxonomy structure itself is the main contribution.
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