Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Base Models Beat Aligned Models at Randomness and Creativity
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2505.00047.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:56:18.386633Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T05:47:41.530108Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation fe47ffdc-66f5-4879-8e9c-6fde23034d61 · inbound
Effective Reinforcement Learning for Reasoning in Language Models cites this paper.
Effective Reinforcement Learning for Reasoning in Language Models Base Models Beat Aligned Models at Randomness and Creativity
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:56:18.386633Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ea4ef6c8-cf92-4d34-bb53-3365c52bbbdf · inbound
Get Experience from Practice: LLM Agents with Record & Replay cites this paper.
Get Experience from Practice: LLM Agents with Record & Replay Base Models Beat Aligned Models at Randomness and Creativity
Reference 86
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:44:30.481737Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 296f2663-eb36-48ae-a6cf-d0242145ba0e · inbound
When Two LLMs Debate, Both Think They'll Win cites this paper.
When Two LLMs Debate, Both Think They'll Win Base Models Beat Aligned Models at Randomness and Creativity
Reference 2025
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:24:14.491454Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fb8110d9-8cdc-4c85-9942-4308c53275ce · inbound
Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity cites this paper.
Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity Base Models Beat Aligned Models at Randomness and Creativity
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T13:23:15.773796Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 57d53a2d-d128-49d7-ab88-e7d34ea5cd93 · inbound
The Homogenization Problem in LLMs: Towards Meaningful Diversity in AI Safety cites this paper.
The Homogenization Problem in LLMs: Towards Meaningful Diversity in AI Safety Base Models Beat Aligned Models at Randomness and Creativity
Reference 136
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T17:53:11.558569Z
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 a8eef223-f0d5-4742-9e28-2f34c4023cbd · inbound
The Homogenization Problem in LLMs: Towards Meaningful Diversity in AI Safety cites this paper.
The Homogenization Problem in LLMs: Towards Meaningful Diversity in AI Safety Base Models Beat Aligned Models at Randomness and Creativity
Reference 136
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T17:10:24.907523Z
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 b30a9207-71b9-4601-8061-bc8ed59fc562 · inbound
The Homogenization Problem in LLMs: Towards Meaningful Diversity in AI Safety cites this paper.
The Homogenization Problem in LLMs: Towards Meaningful Diversity in AI Safety Base Models Beat Aligned Models at Randomness and Creativity
Reference 135
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T13:00:29.007410Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 49a342f1-b9c3-4977-a900-f41c057ad8b7 · inbound
Annotations Mitigate Post-Training Mode Collapse cites this paper.
Annotations Mitigate Post-Training Mode Collapse Base Models Beat Aligned Models at Randomness and Creativity
Reference 28
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T06:46:51.955719Z
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 0300a2d2-00e0-47f8-9b65-ece74a6a8a09 · inbound
Unlocking LLM Creativity in Science through Analogical Reasoning cites this paper.
Unlocking LLM Creativity in Science through Analogical Reasoning Base Models Beat Aligned Models at Randomness and Creativity
Reference 49
- Resolution
- verified exact
- arxiv_id, observed 2026-05-13T01:57:05.581311Z
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 39fd9c9e-b1a0-4e81-bff1-995a15f55501 · inbound
Activation Steering for Synthetic Data Generation: The Role of Diversity in Downstream Safety Detection cites this paper.
Activation Steering for Synthetic Data Generation: The Role of Diversity in Downstream Safety Detection Base Models Beat Aligned Models at Randomness and Creativity
Reference 54
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T14:03:29.893389Z
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 de69a4aa-ae4d-456e-8aaa-8f36c070ffaa · inbound
Fine-Tuning Improves Information Conveyance in Language Models cites this paper.
Fine-Tuning Improves Information Conveyance in Language Models Base Models Beat Aligned Models at Randomness and Creativity
Reference 37
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:02:46.661372Z
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 bc7304dd-2a27-4115-bbbc-685510b96852 · inbound
IDEAFix: Evaluation Framework for Creative Defixation Prompting in LLMs cites this paper.
IDEAFix: Evaluation Framework for Creative Defixation Prompting in LLMs Base Models Beat Aligned Models at Randomness and Creativity
Reference 14
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-28T18:42:28.914736Z
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 7f4428ae-3bee-415a-8112-d117cae3e0b6 · inbound
AI Coding Agents in Social Science: Methodologically Diverse, Empirically Consistent, Interpretively Vulnerable cites this paper.
AI Coding Agents in Social Science: Methodologically Diverse, Empirically Consistent, Interpretively Vulnerable Base Models Beat Aligned Models at Randomness and Creativity
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T05:47:41.531784Z
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 f4f3649f-2ab9-4ae9-8eec-fc1902e19516 · inbound
Towards Physical Intuitions for Alignment Dynamics: A Case Study With Randomness Crystallization cites this paper.
Towards Physical Intuitions for Alignment Dynamics: A Case Study With Randomness Crystallization Base Models Beat Aligned Models at Randomness and Creativity
Reference 2
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-30T06:44:19.138941Z
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.