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Paper Citation Record · LEDGER

Formal Aspects of Language Modeling

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2311.04329.

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

pith.paper-citation-record.v1
2311.04329 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 2026-08-08T06:32:00.761636+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:35:36.636923Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T06:55:29.343758Z

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 689faa0a-7d72-4aad-89cc-74f3402e9f42 · inbound

Circuit Stability Characterizes Language Model Generalization cites this paper.

Circuit Stability Characterizes Language Model Generalization Formal Aspects of Language Modeling

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T12:35:36.636923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T12:35:36.636923Z digest=sha256:e9e48f54fc0dfd143f8c929061ded11ad5beec21a6790af8ce147418dbb5a2d6

Observation 91054e9d-f796-4485-b76b-907ababec0f0 · inbound

Unraveling Syntax: Language Modeling and the Substructure of Grammars cites this paper.

Unraveling Syntax: Language Modeling and the Substructure of Grammars Formal Aspects of Language Modeling

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-04T12:47:19.452910Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T12:47:19.452910Z digest=sha256:f117f95a7c1bec915ace403f7a1cad7a6336f15116c6f2a92b151008dceb53f9

Observation 4c0adca2-17b1-4b80-94c0-87b0841b0c08 · inbound

A fine-grained look at causal effects in causal spaces cites this paper.

A fine-grained look at causal effects in causal spaces Formal Aspects of Language Modeling

Reference 2

Resolution
verified exact
arxiv_id, observed 2026-05-16T22:58:39.140497Z

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=2026-05-16T22:54:13.807169Z digest=sha256:4cd56e8bf10bd650d058987e71975945741bff28c095fce8ff3d14a8c2226635

Observation b1c14e0a-9a9d-4228-b1ff-07d2bf4a7395 · inbound

Autoregressive Language Models are Secretly Energy-Based Models: Insights into the Lookahead Capabilities of Next-Token Prediction cites this paper.

Autoregressive Language Models are Secretly Energy-Based Models: Insights into the Lookahead Capabilities of Next-Token Prediction Formal Aspects of Language Modeling

Reference 13

Resolution
verified exact
arxiv_id, observed 2026-05-16T21:28:33.509249Z

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=2026-05-16T21:28:20.658539Z digest=sha256:f1288882cdcc054adad7d9521ad5149306f781b3da860bfae01b8f5318f1632e

Observation dc7c0c28-23f1-44d8-863f-e04b93606289 · inbound

Autoregressive Language Models are Secretly Energy-Based Models: Insights into the Lookahead Capabilities of Next-Token Prediction cites this paper.

Autoregressive Language Models are Secretly Energy-Based Models: Insights into the Lookahead Capabilities of Next-Token Prediction Formal Aspects of Language Modeling

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-03T15:55:45.828476Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T15:55:45.828476Z digest=sha256:97a751cea42ba19759c63939df661621ab17f17a5d04d15d566b2029f40eb6af

Observation 63724674-78ff-4c06-b195-bd2c03f9c596 · inbound

Bridging the Gap Between Latent and Explicit Reasoning with Looped Transformers cites this paper.

Bridging the Gap Between Latent and Explicit Reasoning with Looped Transformers Formal Aspects of Language Modeling

Reference 69

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T06:55:29.345903Z

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=2026-07-01T06:51:41.784250Z digest=sha256:86104f0fb80e6aabb654540afb21d21b13ecec1b7b808d7f6fea21bf9193d3c7