Paper Citation Record · LEDGER

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models

As of 9 August 2026, this Paper Citation Record lists 38 of 38 outbound references and 0 inbound Pith citation observations for arXiv:2507.04432.

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

pith.paper-citation-record.v1
2507.04432 v1

Coverage vector

measured 38 of 38 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:53:38.841164Z

measured 38 of 38 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

38 of 38 outbound references displayed

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verified fuzzy5
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 7fb5c449-2fba-44dd-ac84-27b3f7b1fdc2 · outbound

This paper cites an unresolved cited work.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Unresolved cited work

Reference 1

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Observation 19b51740-dc87-446c-8231-2f53abc06bc5 · outbound

This paper cites ACM BCB’25, October 2025, Philadelphia, Pennsylvania, USA P.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models ACM BCB’25, October 2025, Philadelphia, Pennsylvania, USA P

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:53:42.937507Z

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Observation f6c9e376-6e3e-490a-ab19-c88d2f4fa706 · outbound

This paper cites Predictive accuracy achieved with incremental active learning using both underconfident and overconfident examples.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Predictive accuracy achieved with incremental active learning using both underconfident and overconfident examples

Reference 4

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Observation 8d2310bb-789f-492f-ad2f-d1986a6c3b9b · outbound

This paper cites Selection of overconfident examples is distinguishing feature in better performing active learning trial.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Selection of overconfident examples is distinguishing feature in better performing active learning trial

Reference 5

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This paper cites Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Does Fine-Tuning LLMs on New Knowledge Encourage Hallucinations?

Reference 6

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Observation 027f41fe-8e62-48b2-9cd3-6a1a8e3ff68d · outbound

This paper cites In 2024 47th MIPRO ICT and Electronics Convention (MIPRO).

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models In 2024 47th MIPRO ICT and Electronics Convention (MIPRO)

Reference 7

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Observation fbbd912e-3e3e-4df8-97cd-056293bca243 · outbound

This paper cites LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models LLMs Know More Than They Show: On the Intrinsic Representation of LLM Hallucinations

Reference 8

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Observation 52cce5bf-603b-4372-b73b-49f620c0054d · outbound

This paper cites Active Learning for Robust and Representative LLM Generation in Safety-Critical Scenarios.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Active Learning for Robust and Representative LLM Generation in Safety-Critical Scenarios

Reference 12

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This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 13

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Observation 86b97626-154f-4e07-a4b0-f6a7837c73ae · outbound

This paper cites Neurocomputing 503, 7 (Sep 2022), 92-108.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Neurocomputing 503, 7 (Sep 2022), 92-108

Reference 15

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Observation 885bd4e0-9cb8-4b96-8a03-6fd0ef7a961e · outbound

This paper cites Annu Rev Physiol 10, 85 (Feb 2023), 71-91.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Annu Rev Physiol 10, 85 (Feb 2023), 71-91

Reference 20

Resolution: verified exact; doi, observed 2026-08-06T19:53:40.218029Z

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Observation c09c8d8e-1c98-4971-83c2-89b418a9e212 · outbound

This paper cites J Inform Electr Electron Eng 4, 3 (Nov 2023), 1-3.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models J Inform Electr Electron Eng 4, 3 (Nov 2023), 1-3

Reference 21

Resolution: verified exact; doi, observed 2026-08-06T19:53:39.956451Z

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Observation fb990ff5-f763-4427-80a6-9a76d8fbd920 · outbound

This paper cites In Proceedings of the 18th BioNLP Workshop and Shared Task.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models In Proceedings of the 18th BioNLP Workshop and Shared Task

Reference 22

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Observation 047025cc-6e46-4f0f-ba7c-c068725bc855 · outbound

This paper cites Nucleic Acids Res, 43, D1 (Jan 2015), D204-12.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Nucleic Acids Res, 43, D1 (Jan 2015), D204-12

Reference 24

Resolution: verified exact; doi, observed 2026-08-06T19:53:39.493543Z

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Observation 28631c3e-b94d-4902-92c7-2f8f95f47e0c · outbound

This paper cites Nucleic Acids Res, 48, D1 (Jan 2020), D489-97.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Nucleic Acids Res, 48, D1 (Jan 2020), D489-97

Reference 25

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Observation 873284f2-c22b-4a4a-82e7-77eb2a324256 · outbound

This paper cites Database, 2019, (June 2019), baz068.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Database, 2019, (June 2019), baz068

Reference 26

Resolution: verified exact; doi, observed 2026-08-06T19:53:39.333779Z

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Observation 4357242c-03a9-47f9-b73c-ab30f0241b2b · outbound

This paper cites Mol Syst Biol, 19, 5 (May 2023), e11325.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Mol Syst Biol, 19, 5 (May 2023), e11325

Reference 27

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Observation a7107925-66e7-4d5e-939b-6ac8c480cc71 · outbound

This paper cites A Primer on the Inner Workings of Transformer-based Language Models.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models A Primer on the Inner Workings of Transformer-based Language Models

Reference 28

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Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Decoupled Weight Decay Regularization

Reference 29

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Observation 6eabb3eb-d978-4d90-a8c2-c6b40e30f692 · outbound

This paper cites Active Learning Principles for In-Context Learning with Large Language Models.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Active Learning Principles for In-Context Learning with Large Language Models

Reference 31

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Observation 8be33b00-cffb-4176-a561-889b5f1d7739 · outbound

This paper cites A Survey of Uncertainty Estimation in LLMs: Theory Meets Practice.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models A Survey of Uncertainty Estimation in LLMs: Theory Meets Practice

Reference 32

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Observation b2e8909d-519a-4a26-96be-226aa2230ed9 · outbound

This paper cites Unlocking the Power of LLM Uncertainty for Active In-Context Example Selection.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Unlocking the Power of LLM Uncertainty for Active In-Context Example Selection

Reference 33

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Observation 29d41935-02b3-42be-9033-eac5f2a961f2 · outbound

This paper cites Label-Confidence-Aware Uncertainty Estimation in Natural Language Generation.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Label-Confidence-Aware Uncertainty Estimation in Natural Language Generation

Reference 34

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Observation aefcb902-e75e-490c-b9a3-fc737ce03fa1 · outbound

This paper cites Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Parameter-Efficient Fine-Tuning Methods for Pretrained Language Models: A Critical Review and Assessment

Reference 36

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This paper cites Appl Sci 15, 6 (Mar 2025),.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Appl Sci 15, 6 (Mar 2025),

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:53:41.750577Z

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Observation 85d84a5d-9ac3-4906-a92a-5c891fe9427f · outbound

This paper cites Nucleic Acids Res, 34, suppl_1 (Jan 2006), D319-21.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Nucleic Acids Res, 34, suppl_1 (Jan 2006), D319-21

Reference 2006

Resolution: verified exact; doi, observed 2026-08-06T19:53:39.736329Z

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Observation 5b8dc557-c13f-4c77-95c5-640d26eca12a · outbound

This paper cites Semin Immunol 26, 6 (Dec 2024), 486-496.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Semin Immunol 26, 6 (Dec 2024), 486-496

Reference 2014

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This paper cites In 2015 Proceedings of the IEEE international conference on computer vision (ICCV).

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models In 2015 Proceedings of the IEEE international conference on computer vision (ICCV)

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:36.193740Z

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Observation bab7d187-33eb-4374-ba1d-0ac11b7dd35a · outbound

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Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models PloS one 12, 12 (Dec 2017), e0190046

Reference 2017

Resolution: verified exact; doi, observed 2026-08-06T19:53:40.357759Z

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Observation 2c4166a7-99fc-40a6-83f5-704914f797a4 · outbound

This paper cites Tune: A Research Platform for Distributed Model Selection and Training.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Tune: A Research Platform for Distributed Model Selection and Training

Reference 2018

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This paper cites In Proceedings of the 2019 conference of the North American chapter of the association for computational linguistics: human language technologies, volume 1 (long and short papers).

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models In Proceedings of the 2019 conference of the North American chapter of the association for computational linguistics: human language technologies, volume 1 (long and short papers)

Reference 2019

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Observation aef2c8c3-e63d-4eff-9370-f861be80b125 · outbound

This paper cites In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-06T19:53:36.345019Z

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Observation 0e4a990f-cd54-4b7b-babf-5df2b6922032 · outbound

This paper cites JAIR 70 (Apr 2021), 1373-411.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models JAIR 70 (Apr 2021), 1373-411

Reference 2021

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This paper cites Will we run out of data? Limits of LLM scaling based on human-generated data.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Will we run out of data? Limits of LLM scaling based on human-generated data

Reference 2022

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This paper cites In Architecture and System Support for Transformer Models (ASSYST@ ISCA 2023).

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models In Architecture and System Support for Transformer Models (ASSYST@ ISCA 2023)

Reference 2023

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T19:53:42.275897Z

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Observation 54752b28-317c-4535-a13e-d7d7697decd0 · outbound

This paper cites In 2024 IEEE 21st International Conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT (HONET).

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models In 2024 IEEE 21st International Conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT (HONET)

Reference 2024

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Observation 4bcd16e6-424c-4586-bec2-064c82a39c75 · outbound

This paper cites Curr Rev Musculoskelet Med 18, 7 (Jul 2025), 1-21.

Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Curr Rev Musculoskelet Med 18, 7 (Jul 2025), 1-21

Reference 2025

Resolution: verified exact; doi, observed 2026-08-06T19:53:40.946393Z

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Observation ee7e313d-778d-46ca-9460-07cb846a65b1 · outbound

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Reconstructing Biological Pathways by Applying Selective Incremental Learning to (Very) Small Language Models Unresolved cited work

Reference 3087

Resolution: verified exact; raw_fallback, observed 2026-08-06T19:53:41.287040Z

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Pith citing papers

No inbound Pith citation observations are available.