Paper Citation Record · LEDGER

Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2402.09236.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2402.09236 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:16:27.515413Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-03T08:57:48.292468Z

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 bcb15f67-7389-4aca-8ab3-51e29ba628e7 · inbound

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis cites this paper.

Learning General Causal Structures with Hidden Dynamic Process for Climate Analysis Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-10T17:16:27.515413Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b755262-ecfa-4bd7-9139-2b77d761420b · inbound

Incorporating Hierarchical Semantics in Sparse Autoencoder Architectures cites this paper.

Incorporating Hierarchical Semantics in Sparse Autoencoder Architectures Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T11:56:15.231952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b02bcf2b-2ec5-4931-8abb-400919617120 · inbound

Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solution cites this paper.

Trustworthy AI Suffers from Invariance Conflicts and Causality is The Solution Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models

Reference 42

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T00:15:09.118070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 8dd56e7f-1e0a-46a7-bcd6-610c783096e6 · inbound

Causal Scaffolding for Physical Reasoning: A Benchmark for Causally-Informed Physical World Understanding in VLMs cites this paper.

Causal Scaffolding for Physical Reasoning: A Benchmark for Causally-Informed Physical World Understanding in VLMs Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-07-02T15:57:06.731270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 16759b87-7ab8-414f-85f8-cdff1d982717 · inbound

Breaking the Solver Bottleneck: Training Task Generators at the Learnable Frontier cites this paper.

Breaking the Solver Bottleneck: Training Task Generators at the Learnable Frontier Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models

Reference 120

Resolution: verified exact; arxiv_id, observed 2026-07-03T08:57:48.293879Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation bcd79dfb-3736-493b-bd71-7fd4c7b2d742 · inbound

Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling cites this paper.

Learning Task-Sufficient World Models by Synergizing Agentic Exploration and Structured Modeling Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models

Reference 31

Resolution: unresolved; no resolver link, observed 2026-07-11T19:24:48.899301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.