Pith. sign in

Paper Citation Record · LEDGER

Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model

As of 4 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2404.04167.

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

pith.paper-citation-record.v1
2404.04167 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T07:31:31.905663Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T23:42:49.507726Z

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 d3f26f39-f6a6-4a3c-818a-4695c5cb1058 · inbound

Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices cites this paper.

Will LLMs Scaling Hit the Wall? Breaking Barriers via Distributed Resources on Massive Edge Devices Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model

Reference 149

Resolution
verified exact
arxiv_id, observed 2026-05-23T01:05:16.321054Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-23T01:03:26.037233Z digest=sha256:ed1bb8d72ed8fc074ca2b15db4b138f051401790c249bb526ec7b80ea43d66b9

Observation 5e2fd9ed-40b1-4398-9a89-e2af331044e9 · inbound

EvalMORAAL: Interpretable Chain-of-Thought and LLM-as-Judge Evaluation for Moral Alignment in Large Language Models cites this paper.

EvalMORAAL: Interpretable Chain-of-Thought and LLM-as-Judge Evaluation for Moral Alignment in Large Language Models Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-05-21T20:40:36.167028Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-21T20:38:23.433621Z digest=sha256:ecab1c8490beb22791714cfac964eb054a2f00b2e640fda8383a11359fd6a9ba

Observation 6c82a744-062e-4ffe-8445-7d0daa394892 · inbound

Scaling Latent Reasoning via Looped Language Models cites this paper.

Scaling Latent Reasoning via Looped Language Models Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-05-15T07:43:11.888797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=pdf_text observed=2026-05-15T07:43:11.620446Z digest=sha256:bc57c9263d0b0ccd65cf1187a096bab6f10ddc114bf4379989f6144068113de8

Observation 17abc45a-3f00-4a13-947b-2e4695930bcc · inbound

Scaling Latent Reasoning via Looped Language Models cites this paper.

Scaling Latent Reasoning via Looped Language Models Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-04T07:31:31.905663Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T07:31:31.905663Z digest=sha256:43c53259a15ff212ab6d5994bc4b304c1784159e2a537d1af0f0195003e0cb87

Observation 00ab22a5-f777-4d28-8335-3caaed7894f3 · inbound

Sample-Efficient Post-Training for LEGO Spatial-Physics Reasoning cites this paper.

Sample-Efficient Post-Training for LEGO Spatial-Physics Reasoning Chinese Tiny LLM: Pretraining a Chinese-Centric Large Language Model

Reference 56

Resolution
metadata mismatch
arxiv_id, observed 2026-06-28T23:42:49.509029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

source=arxiv_source observed=2026-06-28T23:38:38.127345Z digest=sha256:c63af0e9e8f527f8c92a697653fbb102bd20394cbfb07ea6b42aa576fca54ada