Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-05T22:58:50.285582Z
Paper Citation Record · LEDGER
AURA: Affordance-Understanding and Risk-aware Alignment Technique for Large Language Models
As of 7 August 2026, this Paper Citation Record lists 4 of 4 outbound references and 0 inbound Pith citation observations for arXiv:2508.06124.
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 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
4 of 4 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved4
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation f55eaf23-b8f5-4587-8d6a-d6dca882a93c · outbound
This paper cites R-PRM: Reasoning-Driven Process Reward Modeling.
AURA: Affordance-Understanding and Risk-aware Alignment Technique for Large Language Models R-PRM: Reasoning-Driven Process Reward Modeling
Reference 2
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:58:50.079618Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e0312c8b-6a8a-4d40-8800-37cb59664f0f · outbound
This paper cites PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models.
AURA: Affordance-Understanding and Risk-aware Alignment Technique for Large Language Models PRMBench: A Fine-grained and Challenging Benchmark for Process-Level Reward Models
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:58:50.210843Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 283fd66d-35df-44a8-adf0-b197b90a45af · outbound
This paper cites Calibrate Before Use: Improving Few-Shot Performance of Language Models.
AURA: Affordance-Understanding and Risk-aware Alignment Technique for Large Language Models Calibrate Before Use: Improving Few-Shot Performance of Language Models
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:58:50.285582Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a1b42452-0fdc-42ee-af57-006b3dd497e1 · outbound
This paper cites Error Typing for Smarter Rewards: Improving Process Reward Models with Error-Aware Hierarchical Supervision.
AURA: Affordance-Understanding and Risk-aware Alignment Technique for Large Language Models Error Typing for Smarter Rewards: Improving Process Reward Models with Error-Aware Hierarchical Supervision
Reference 2025
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T22:58:49.973078Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.