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Paper Citation Record · LEDGER

Mission: Impossible Language Models

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2401.06416.

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

pith.paper-citation-record.v1
2401.06416 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:48:03.254783Z

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

1
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 9fd1dea6-3b15-4455-ae69-4c2fdd2094e9 · inbound

Beyond Human-Like Processing: Large Language Models Perform Equivalently on Forward and Backward Scientific Text cites this paper.

Beyond Human-Like Processing: Large Language Models Perform Equivalently on Forward and Backward Scientific Text Mission: Impossible Language Models

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-12T19:02:02.782745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T19:02:02.782745Z digest=sha256:2ee9cf65e04a734aab1ecd52af3956282b5907d6de61640d390c547801dc2123

Observation 0f341b96-1fa4-45ec-805a-4ceaba0aa2bd · inbound

Training Bilingual LMs with Data Constraints in the Targeted Language cites this paper.

Training Bilingual LMs with Data Constraints in the Targeted Language Mission: Impossible Language Models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-12T17:04:34.374922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T17:04:34.374922Z digest=sha256:e6a88c335edcd10b14c31b8d5b57f8dbe3705f0aff9808b0fbab6134e4921d8f

Observation 662e7857-0d13-498e-ad93-528a5f92c744 · inbound

Why do language models perform worse for morphologically complex languages? cites this paper.

Why do language models perform worse for morphologically complex languages? Mission: Impossible Language Models

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-12T15:29:49.444554Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T15:29:49.444554Z digest=sha256:dc708622123eb6cbb1d192d6b73c0937a7438db292a71fd6f8154422e003d10c

Observation 188d1188-47b3-4365-8483-e882c343d04a · inbound

Tree Transformers are an Ineffective Model of Syntactic Constituency cites this paper.

Tree Transformers are an Ineffective Model of Syntactic Constituency Mission: Impossible Language Models

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-12T12:43:26.124404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-12T12:43:26.124404Z digest=sha256:f8e605260d6043d90c024aaa32f2f7ccac669f1bd97d64dab5b1c5dcfabdb212

Observation 5cbbc3c9-49e4-4da0-b441-d37f4a99ddfc · inbound

Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models cites this paper.

Surveying the Effects of Quality, Diversity, and Complexity in Synthetic Data From Large Language Models Mission: Impossible Language Models

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-11T22:57:01.723763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:57:01.723763Z digest=sha256:c1b35892621230a778c482600500ebe60502a06b63186b37093cec0ba9748e4e

Observation e0626f47-a581-453b-a61f-d09b86731957 · inbound

Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens cites this paper.

Generative Multimodal Pretraining with Discrete Diffusion Timestep Tokens Mission: Impossible Language Models

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-16T11:48:03.254783Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T11:48:03.254783Z digest=sha256:b94dfb021fee3f63b93e0a9a0cd7771d7a5953557f9e07c8c8d4e4fc38d0bcfa

Observation 89600225-6c25-434d-a726-6362d2be766e · inbound

Probability Consistency in Large Language Models: Theoretical Foundations Meet Empirical Discrepancies cites this paper.

Probability Consistency in Large Language Models: Theoretical Foundations Meet Empirical Discrepancies Mission: Impossible Language Models

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-15T21:55:30.255464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T21:55:30.255464Z digest=sha256:cbf588517f0ad5bb01ca2ddb627067b2e3670511faff69073b71951e018b1db7

Observation 26dbe4ed-f434-47e7-9f17-8ffccf83c58d · inbound

Removing Noise, not Finding Gold: Quality Filtering for Large-Scale Pretraining cites this paper.

Removing Noise, not Finding Gold: Quality Filtering for Large-Scale Pretraining Mission: Impossible Language Models

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-04T13:24:15.278209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T13:24:15.278209Z digest=sha256:0dc9ae3172789948d04404cff353a47edc910329e3a64bf9d67c830857e62f8c

Observation 527bddb7-1b7f-498c-8cf7-f2517b082b9a · inbound

Finding Meaning in Embeddings: Concept Separation Curves cites this paper.

Finding Meaning in Embeddings: Concept Separation Curves Mission: Impossible Language Models

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-11T14:26:03.282182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-09T21:52:40.035720Z digest=sha256:c3e099c3731215c6eb9445b822007dc9f5dba572404fac97640c3882cecc2c19

Observation d20555ad-4ebd-487e-8f86-ee673586a3fd · inbound

A framework for analyzing concept representations in neural models cites this paper.

A framework for analyzing concept representations in neural models Mission: Impossible Language Models

Reference 243

Resolution
verified exact
arxiv_id, observed 2026-05-09T22:18:58.918696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-05-09T14:49:22.776209Z digest=sha256:e065c994f38a418b4fc2374e59f2dad97fa7a94b726f7e73a7f5c54725bdc3bc