Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T05:18:07.242518Z
Paper Citation Record · LEDGER
As of 19 August 2026, this Paper Citation Record lists 76 of 76 outbound references and 4 inbound Pith citation observations for arXiv:2505.00038.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-16T05:18:07.242518Z
One-hop event checks from named stored sources.
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Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:25:08.496563Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-28T19:32:35.359433Z
76 of 76 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation a98c2ece-3ca7-449a-a27c-bbcde79be6f2 · outbound
HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation https://docs.cohere.com/v2/docs/command-r-plus
Reference 1
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Phi-3 Technical Report: A Highly Capable Language Model Locally on Your Phone
Reference 3
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Observation 98e9f582-0280-44de-958b-f6d9db311586 · outbound
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Reference 4
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Observation af7a827c-ddbe-41f7-ab5f-3cbdbf5cfc54 · outbound
HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Afzoon, U
Reference 5
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Reference 8
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Reference 9
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Del Vicario, G
Reference 10
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Reference 11
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Observation 74c36e15-5aa1-44e5-89d4-9c346a6c70d8 · outbound
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Reference 12
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Scaling Synthetic Data Creation with 1,000,000,000 Personas
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Reference 14
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Goldstein-Stewart, K
Reference 15
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Deliberative Alignment: Reasoning Enables Safer Language Models
Reference 16
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Observation aa5b5be2-346c-49fd-b7c7-50f4a4067397 · outbound
HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 17
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Observation e12a88fe-cab6-4272-8f76-32f7fda1e861 · outbound
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Reference 18
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Reference 19
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Huang, W
Reference 20
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Hwang, B
Reference 21
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Mistral 7B
Reference 22
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback
Reference 23
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Reference 24
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation BIG5-CHAT: Shaping LLM Personalities Through Training on Human-Grounded Data
Reference 25
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Observation 9efe1862-2929-4dba-adc2-89275a337944 · outbound
HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Unresolved cited work
Reference 26
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Unresolved cited work
Reference 27
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Patel, D
Reference 28
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Observation 5a8b7a25-1f0a-4f5c-9c83-3597aa6dc2d2 · outbound
HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Rafailov, A
Reference 29
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Observation 9a4d7ce5-57ed-4347-a2ad-2fffe601deb7 · outbound
HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Ramesh Kashyap, D
Reference 30
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Röttger, H
Reference 31
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Sahoo, P
Reference 32
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation LaMP: When Large Language Models Meet Personalization
Reference 33
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Santurkar, E
Reference 34
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Aligning Language Models with Demonstrated Feedback
Reference 35
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Observation c905ef1d-e523-45e7-b8f8-863fcbae2106 · outbound
HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation A StrongREJECT for Empty Jailbreaks
Reference 36
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Observation 8aed5afd-048f-401f-a378-1a4d80924e3d · outbound
HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation Stiennon, L
Reference 37
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Reference 38
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Reference 39
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation LLaMA: Open and Efficient Foundation Language Models
Reference 40
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Reference 41
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Reference 42
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Reference 43
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Reference 44
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Reference 45
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Reference 46
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Reference 47
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Reference 48
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Reference 49
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Reference 50
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Reference 53
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Reference 54
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Reference 55
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Reference 56
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Reference 57
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Reference 58
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Reference 59
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Reference 60
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Reference 61
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Reference 62
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Reference 63
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Reference 64
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Reference 65
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Reference 66
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Reference 67
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Reference 68
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Reference 69
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Reference 70
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Reference 71
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Reference 72
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Reference 73
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Reference 74
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Reference 75
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HyPerAlign: Interpretable Personalized LLM Alignment via Hypothesis Generation As always
Reference 76
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Reference 2008
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Observation a6af79ba-cefc-4cb0-8f53-4984a4224a18 · outbound
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Reference 2022
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Reference 2025
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Reference 14
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Reference 18
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Reference 7
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