Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-07T16:30:12.393364Z
Paper Citation Record · LEDGER
From Insight to Action: A Novel Framework for Interpretability-Guided Data Selection in Large Language Models
As of 13 August 2026, this Paper Citation Record lists 6 of 6 outbound references and 0 inbound Pith citation observations for arXiv:2604.25167.
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
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
6 of 6 outbound references displayed
- verified exact1
- verified fuzzy2
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch3
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation b020dda5-7b02-489c-92b5-f8c31d106c95 · outbound
This paper cites Alexander Bukharin, Shiyang Li, Zhengyang Wang, Jingfeng Yang, Bing Yin, Xian Li, Chao Zhang, Tuo Zhao, and Haoming Jiang.
From Insight to Action: A Novel Framework for Interpretability-Guided Data Selection in Large Language Models Alexander Bukharin, Shiyang Li, Zhengyang Wang, Jingfeng Yang, Bing Yin, Xian Li, Chao Zhang, Tuo Zhao, and Haoming Jiang
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T02:08:41.347547Z
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 57816a5c-3e5f-4bc0-9091-47f1add4f881 · outbound
This paper cites InThe Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11.
From Insight to Action: A Novel Framework for Interpretability-Guided Data Selection in Large Language Models InThe Twelfth International Conference on Learning Representations, ICLR 2024, Vienna, Austria, May 7-11
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-27T02:08:41.345182Z
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 fb9d67a8-6e0e-4061-9034-78f511bbe1ed · outbound
This paper cites Sparse Autoencoders Find Highly Interpretable Features in Language Models.
From Insight to Action: A Novel Framework for Interpretability-Guided Data Selection in Large Language Models Sparse Autoencoders Find Highly Interpretable Features in Language Models
Reference 3
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-11T23:41:16.550386Z
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 62c964c9-748f-4202-8572-53581624f0f7 · outbound
This paper cites Toy Models of Superposition.
From Insight to Action: A Novel Framework for Interpretability-Guided Data Selection in Large Language Models Toy Models of Superposition
Reference 4
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-11T23:41:16.512347Z
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 0bb13f92-c504-4340-b63d-ae88f9108c1b · outbound
This paper cites From Curated Data to Scalable Models: Continual Pre-training of Dense and MoE Large Language Models for Tibetan.
From Insight to Action: A Novel Framework for Interpretability-Guided Data Selection in Large Language Models From Curated Data to Scalable Models: Continual Pre-training of Dense and MoE Large Language Models for Tibetan
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T02:55:21.478518Z
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 a8772479-fd0b-48dd-a1cc-189e5553aebc · outbound
This paper cites Rethinking Data Selection at Scale: Random Selection is Almost All You Need.
From Insight to Action: A Novel Framework for Interpretability-Guided Data Selection in Large Language Models Rethinking Data Selection at Scale: Random Selection is Almost All You Need
Reference 6
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T23:41:16.578231Z
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.
Pith citing papers
No inbound Pith citation observations are available.