Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Improving the Robustness of Large Language Models via Consistency Alignment
As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2403.14221.
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 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T15:55:06.873942Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-21T22:00:41.522948Z
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 919ea228-6e2a-4058-81a0-a9d1e190473c · inbound
On Adversarial Robustness and Out-of-Distribution Robustness of Large Language Models cites this paper.
On Adversarial Robustness and Out-of-Distribution Robustness of Large Language Models Improving the Robustness of Large Language Models via Consistency Alignment
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T15:55:06.873942Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 00119747-31e3-4066-a90f-627a6d5c8051 · inbound
Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions cites this paper.
Evaluating and Improving Robustness in Large Language Models: A Survey and Future Directions Improving the Robustness of Large Language Models via Consistency Alignment
Reference 215
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:42:31.627373Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation af1d8331-e1a9-4f73-bece-57c69c6fff80 · inbound
Investigating the Robustness of Retrieval-Augmented Generation at the Query Level cites this paper.
Investigating the Robustness of Retrieval-Augmented Generation at the Query Level Improving the Robustness of Large Language Models via Consistency Alignment
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:55:55.033734Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0dbf7937-5f67-436f-8e1b-26b1eb946950 · inbound
Position: AI Evaluations Should be Grounded on a Theory of Capability cites this paper.
Position: AI Evaluations Should be Grounded on a Theory of Capability Improving the Robustness of Large Language Models via Consistency Alignment
Reference 54
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T22:00:41.525300Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.
Observation 765b3ac1-6af8-4a9e-af4c-5905e3f146b0 · inbound
Certifiable Safe RLHF: Semantic Grounding and Fixed Penalty Constraint Optimization for Safer LLM Alignment cites this paper.
Certifiable Safe RLHF: Semantic Grounding and Fixed Penalty Constraint Optimization for Safer LLM Alignment Improving the Robustness of Large Language Models via Consistency Alignment
Reference 54
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T12:27:28.743448Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.