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Paper Citation Record · LEDGER

Compositionality decomposed: how do neural networks generalise?

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 9 inbound Pith citation observations for arXiv:1908.08351.

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

pith.paper-citation-record.v1
1908.08351 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 9 of 9 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 9 of 9 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:46:20.039545Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

16
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2e34ce35-aec4-47eb-971a-77dcc699b65f · inbound

Scaling Laws for Autoregressive Generative Modeling cites this paper.

Scaling Laws for Autoregressive Generative Modeling Compositionality decomposed: how do neural networks generalise?

Reference 6

Resolution
metadata mismatch
arxiv_id, observed 2026-05-13T07:49:43.791768Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-13T07:49:43.711653Z digest=sha256:abf9db772b25567bd43fb7f436f6b2e770d4f0db7ec47d5334ea9de5c5814b61

Observation 8625ebd1-f5bc-4f9c-89c3-e3931e8f22c8 · inbound

Scaling Laws for Transfer cites this paper.

Scaling Laws for Transfer Compositionality decomposed: how do neural networks generalise?

Reference 88

Resolution
verified exact
arxiv_id, observed 2026-05-18T00:58:13.748846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-18T00:58:13.116663Z digest=sha256:43c311f3272fbb6ec6a8fc156e3506393ff92ed7112b5f86f6a088ed95811596

Observation 9f24867c-1319-4c0b-81e4-1f0d5250dc87 · inbound

A General Language Assistant as a Laboratory for Alignment cites this paper.

A General Language Assistant as a Laboratory for Alignment Compositionality decomposed: how do neural networks generalise?

Reference 119

Resolution
verified exact
arxiv_id, observed 2026-05-11T14:22:59.430828Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-11T14:22:57.925354Z digest=sha256:979b64e5686c31c3da8c2e9326461223e0f5a17d7aa65b7a5d9142101fe8cebb

Observation eccf46ae-63c6-42d4-baf2-7cb9a927b7e7 · inbound

Language Models (Mostly) Know What They Know cites this paper.

Language Models (Mostly) Know What They Know Compositionality decomposed: how do neural networks generalise?

Reference 177

Resolution
verified exact
arxiv_id, observed 2026-05-10T15:42:47.857626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-10T15:42:47.274448Z digest=sha256:8f907e1654e72fe13fea919e5cf9a52d2b8a27a8bb36eafcc12960cc3f30f388

Observation 4cb4ddf4-8e1d-4f87-b71d-d26ae45d547f · inbound

Behavioural vs. Representational Systematicity in End-to-End Models: An Opinionated Survey cites this paper.

Behavioural vs. Representational Systematicity in End-to-End Models: An Opinionated Survey Compositionality decomposed: how do neural networks generalise?

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T10:46:20.039545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:46:20.039545Z digest=sha256:af71308227cbf29b28b066ec94454b0b923462fa514397d8a8b73bab5cc2102b

Observation 95d4bbd3-ac72-4c31-a93a-b74df2182d54 · inbound

Towards a Comparative Framework for Compositional AI Models cites this paper.

Towards a Comparative Framework for Compositional AI Models Compositionality decomposed: how do neural networks generalise?

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-06T22:13:43.728217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T22:13:43.728217Z digest=sha256:f01a184ad52c0355fb93ded1238c315a2c1bff88812fd1f13535645a318fe8e6

Observation 940b2c36-7cf7-4c8b-a3c3-a42b151f81e7 · inbound

How Do Language Models Compose Functions? cites this paper.

How Do Language Models Compose Functions? Compositionality decomposed: how do neural networks generalise?

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-18T11:06:17.706729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-18T11:04:09.179536Z digest=sha256:915409359b4d00693f732b20a104803766f2b478fd1fb371b0e1df9050cb5453

Observation 753fe393-f9ad-4d82-b944-d0726376ad8c · inbound

From Mechanistic to Compositional Interpretability cites this paper.

From Mechanistic to Compositional Interpretability Compositionality decomposed: how do neural networks generalise?

Reference 42

Resolution
metadata mismatch
arxiv_id, observed 2026-05-12T02:46:18.395597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-12T02:42:26.173782Z digest=sha256:e380bd21b29106e6c775714dfb6aaafeacb798749edbd01b4c24108870866eef

Observation 2c9db9b7-c39c-45f5-8857-cea6319457b5 · inbound

Arithmetic Pedagogy for Language Models cites this paper.

Arithmetic Pedagogy for Language Models Compositionality decomposed: how do neural networks generalise?

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-02T07:46:46.561663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-06-28T06:37:37.832435Z digest=sha256:b182586ee7e323c07bc10a1ffc5444dee711c7e3f71e234c3d1a448bfe6cb076