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Paper Citation Record · LEDGER

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

As of 9 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 2 inbound Pith citation observations for arXiv:2507.20984.

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

pith.paper-citation-record.v1
2507.20984 v2

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T13:09:56.610980Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T18:16:47.369984Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T14:59:55.788621Z

Reference resolution

12 of 12 outbound references displayed

  • verified exact1
  • verified fuzzy1
  • unresolved10
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 9c922657-fd85-4dd6-8518-cb63d99e1387 · outbound

This paper cites SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model.

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment SmolLM2: When Smol Goes Big -- Data-Centric Training of a Small Language Model

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-06T13:09:55.577974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:09:55.577974Z digest=sha256:f144d4289b5967df3c732a2db5689cf237e3beb0262ceab23c8e72faa7110710

Observation ec59bf5e-67eb-4442-861d-02a04b265f89 · outbound

This paper cites Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities.

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T13:09:55.738748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:09:55.738748Z digest=sha256:808d326490a3b2971d4016fcacaf3352bf2ea571547ba58785aa0da0ff7055e2

Observation e7292b77-5141-422e-9dd0-84e79643ca6a · outbound

This paper cites Goddard, S.

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment Goddard, S

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T13:09:57.217153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T13:09:55.872304Z digest=sha256:b6d5b2850b80c23026501ba489e3d0342c45064d5fd16734522c4c3cd0216c44

Observation cc0da658-0df1-4508-91b4-f4c7193bd992 · outbound

This paper cites Reformulation for Pretraining Data Augmentation.

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment Reformulation for Pretraining Data Augmentation

Reference 7

Resolution
verified exact
local_arxiv, observed 2026-08-06T13:09:57.041674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-06T13:09:56.052083Z digest=sha256:37f86d569ef088fffff4b0ae1f588ba9c7178f55d1012b555b8334da572b6dd4

Observation 666f6e5c-1bf2-4ed1-9c4c-7b6fbf0bc772 · outbound

This paper cites OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models.

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment OpenCoder: The Open Cookbook for Top-Tier Code Large Language Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T13:09:56.137168Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:09:56.137168Z digest=sha256:915d6c9f8f97b5669da23fddcdfe39c42450ba7ec0282f586f09ed0ea49d5c5d

Observation 4fd6ae67-f8d6-4267-a800-41b50186da1c · outbound

This paper cites an unresolved cited work.

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment Unresolved cited work

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T13:09:56.317093Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:09:56.317093Z digest=sha256:e380381748b5106f835f6918ed97136e461d83f3d897a67a334aac304f86cb85

Observation b99eb196-8825-478b-8738-269931b0f8f6 · outbound

This paper cites Scaling Synthetic Data Creation with 1,000,000,000 Personas.

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment Scaling Synthetic Data Creation with 1,000,000,000 Personas

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-06T13:09:56.451305Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:09:56.451305Z digest=sha256:c0baec71e8a23b1d28a13fd3eec571457b98e618f6e8cc58a1df0453014f9e6e

Observation 85ee922e-f1ab-4c36-b5dd-a71cce40314d · outbound

This paper cites ReLU$^2$ Wins: Discovering Efficient Activation Functions for Sparse LLMs.

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment ReLU$^2$ Wins: Discovering Efficient Activation Functions for Sparse LLMs

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T13:09:56.533540Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:09:56.533540Z digest=sha256:c73c676283694f30b2d22b3b59d455ead0fdf77b1e904d2e8ebb7fed360b5a3f

Observation c31fc7ee-cb1a-4ff3-9d2d-56d5cfbfcc24 · outbound

This paper cites MegaMath: Pushing the Limits of Open Math Corpora.

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment MegaMath: Pushing the Limits of Open Math Corpora

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T13:09:56.610980Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:09:56.610980Z digest=sha256:56b1a56591d4ab790e952753a8ea75c86a33e1aae96b0978a4a7f93796ae2ef3

Observation 1e4c73b8-b45e-40e2-a3e9-76cfbf404916 · outbound

This paper cites SWAN-GPT: An Efficient and Scalable Approach for Long-Context Language Modeling.

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment SWAN-GPT: An Efficient and Scalable Approach for Long-Context Language Modeling

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-06T13:09:56.241596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:09:56.241596Z digest=sha256:191fc7853e42b175a1262b8e3eb57d83c98d7778c093fe7c83c1c166ab0892c9

Observation 78cd641d-a835-465f-8589-b46128316218 · outbound

This paper cites DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models.

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment DeepSeekMoE: Towards Ultimate Expert Specialization in Mixture-of-Experts Language Models

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T13:09:55.812799Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:09:55.812799Z digest=sha256:b06b23172e20f7dcae033960cbb722b23f97fa83b6c2c9a3571753efc6da1a4b

Observation 4cc14c29-5209-4a6c-bfd1-6d88a3d15613 · outbound

This paper cites Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models.

SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment Nemotron-H: A Family of Accurate and Efficient Hybrid Mamba-Transformer Models

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-06T13:09:55.632587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T13:09:55.632587Z digest=sha256:d1bcbf906df06b10d6f8e9a52b76378d85e5f1e5e1c9d754189410bd70c9940b

Pith citing papers

Observation 740a3344-b2e3-4619-9d2a-e84fccfbfb4c · inbound

SkipOPU: An FPGA-based Overlay Processor for Large Language Models with Dynamically Allocated Computation cites this paper.

SkipOPU: An FPGA-based Overlay Processor for Large Language Models with Dynamically Allocated Computation SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-02T18:16:47.369984Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T18:16:47.369984Z digest=sha256:4f06ece3bc8f9322029f49f7b7180342e78df00ae6061b11f8f82044d27326ff

Observation a25b0cab-cb9d-4697-91d5-b17c2af968b7 · inbound

Resource-Aware Neuro-Symbolic Reasoning for Local Small Language Models cites this paper.

Resource-Aware Neuro-Symbolic Reasoning for Local Small Language Models SmallThinker: A Family of Efficient Large Language Models Natively Trained for Local Deployment

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-07-04T14:59:55.790237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-26T01:58:15.020295Z digest=sha256:e1bab5ad99a4220f581120abc3595a1c869485bd35529021c7fea26ee14e4ced