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Paper Citation Record · LEDGER

The Cost of Training NLP Models: A Concise Overview

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2004.08900.

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

pith.paper-citation-record.v1
2004.08900 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:02:00.102551Z

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

115
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 51cc121f-5b44-4011-a82a-24d065a5cb77 · inbound

MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning cites this paper.

MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning The Cost of Training NLP Models: A Concise Overview

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-15T07:31:08.333752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-15T07:31:08.266737Z digest=sha256:10cbe506fe58adc36098e71bbb7c35348d851c3586433b84ef8e8a55519b100d

Observation 2e7e8c93-0ad0-4efb-a9c7-d2dd199e27eb · inbound

TAPT: Test-Time Adversarial Prompt Tuning for Robust Inference in Vision-Language Models cites this paper.

TAPT: Test-Time Adversarial Prompt Tuning for Robust Inference in Vision-Language Models The Cost of Training NLP Models: A Concise Overview

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-12T16:52:27.737116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T16:52:27.737116Z digest=sha256:a00934a5492803fb3f25f89ae2a1df95a3aa9af84c47767debb7f079a68c1bf4

Observation ede47404-2e40-48f9-90c8-64dd8c215e22 · inbound

Cloud Platforms for Developing Generative AI Solutions: A Scoping Review of Tools and Services cites this paper.

Cloud Platforms for Developing Generative AI Solutions: A Scoping Review of Tools and Services The Cost of Training NLP Models: A Concise Overview

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-11T20:06:53.373149Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:06:53.373149Z digest=sha256:220afea6099d53c849709bc76bd4042e07754bb35bddfa8fc5a02d8b26c5e7ed

Observation 31ca552d-c2e8-460a-b9ac-d77ba8d3e495 · inbound

Towards Understanding Systems Trade-offs in Retrieval-Augmented Generation Model Inference cites this paper.

Towards Understanding Systems Trade-offs in Retrieval-Augmented Generation Model Inference The Cost of Training NLP Models: A Concise Overview

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-11T14:35:23.439541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T14:35:23.439541Z digest=sha256:3108621b80e7424b7971ebc0ba446a53932d05e8e1a695b606601667541797ec

Observation 868fafc5-e5be-437d-94f1-39a31ae693a8 · inbound

DADA: Dual Averaging with Distance Adaptation cites this paper.

DADA: Dual Averaging with Distance Adaptation The Cost of Training NLP Models: A Concise Overview

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-23T04:55:24.886760Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-23T04:54:12.210472Z digest=sha256:7899eb6f13e993f19c42847dbf14c36607896b2a96642d0877ae2640e59ff583

Observation 32becdb3-cf51-4728-8ae6-718acd5704bc · 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 The Cost of Training NLP Models: A Concise Overview

Reference 26

Resolution
metadata mismatch
arxiv_id, observed 2026-05-23T01:05:16.516916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-05-23T01:03:26.037233Z digest=sha256:583fa426f25870f50cf78e90f3d1d2cb586d75fa9198c68e1c16d34fa0e38a2e

Observation b5ac643a-3791-44d8-872e-ba3cc7ec2ddb · inbound

QUPID: Quantified Understanding for Enhanced Performance, Insights, and Decisions in Korean Search Engines cites this paper.

QUPID: Quantified Understanding for Enhanced Performance, Insights, and Decisions in Korean Search Engines The Cost of Training NLP Models: A Concise Overview

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-15T22:22:45.788270Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:22:45.788270Z digest=sha256:d63f01a5ea406536ba5f17f91b6860e34b29d32262c8914cb747e241d8acfdc7

Observation f8eff1b3-e612-4aba-8e72-316a59496d27 · inbound

Empirical Evaluation of Large Language Models in Automated Program Repair cites this paper.

Empirical Evaluation of Large Language Models in Automated Program Repair The Cost of Training NLP Models: A Concise Overview

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T00:42:04.244106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:42:04.244106Z digest=sha256:959582037031283c717cb665843949030788e66b2bdbcfaea8b655992b0025d9

Observation 058e6369-1db3-4c0c-8ae7-0fa3aaaac638 · inbound

GNN-CNN: An Efficient Hybrid Model of Convolutional and Graph Neural Networks for Text Representation cites this paper.

GNN-CNN: An Efficient Hybrid Model of Convolutional and Graph Neural Networks for Text Representation The Cost of Training NLP Models: A Concise Overview

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-06T18:50:08.475355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:50:08.475355Z digest=sha256:7fef9aa7ac709ddda054e444b7fc2fa213b1d4d622672d1e04a3796a369c828f

Observation c71116f5-2cd0-4fbf-9957-ef0213b41407 · inbound

Enhancing Optimizer Stability: Momentum Adaptation of The NGN Step-size cites this paper.

Enhancing Optimizer Stability: Momentum Adaptation of The NGN Step-size The Cost of Training NLP Models: A Concise Overview

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-16T04:02:00.102551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:02:00.102551Z digest=sha256:a84e55a69feb17dce73593f5521bdbbc0845e43ad7ba31e2c964beace9382048

Observation c0bb041c-8990-4428-baf7-3788aebaa84d · inbound

SLM-Bench: A Comprehensive Benchmark of Small Language Models on Environmental Impacts--Extended Version cites this paper.

SLM-Bench: A Comprehensive Benchmark of Small Language Models on Environmental Impacts--Extended Version The Cost of Training NLP Models: A Concise Overview

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-05T17:57:18.554935Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-05T17:57:18.554935Z digest=sha256:d07e9953b175091c40b70102ff84732c1559a89c9a625ffb5fb563d25c7619b0

Observation dd41b570-6c05-4f0d-9c3c-eba2179dc77c · inbound

A Meta Reinforcement Learning Approach to Goals-Based Wealth Management cites this paper.

A Meta Reinforcement Learning Approach to Goals-Based Wealth Management The Cost of Training NLP Models: A Concise Overview

Reference 278

Resolution
verified exact
arxiv_id, observed 2026-05-08T18:44:01.362620Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-05-08T18:42:50.962120Z digest=sha256:e9d060baee6f4b967da3fee232acafd7522f9f2e490d1c403704f0a09f84400a

Observation a7282dea-01d8-43be-b4da-75b44a3a8ca7 · inbound

Rec-Distill: An Industrial Distillation Pipeline for Large-Scale Recommendation Models cites this paper.

Rec-Distill: An Industrial Distillation Pipeline for Large-Scale Recommendation Models The Cost of Training NLP Models: A Concise Overview

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-06-29T15:13:32.263241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=pdf_text observed=2026-06-29T05:27:15.111684Z digest=sha256:537eb3c6b0c71bd4393d12855701c257edb6ee3dec40ea010dbb06401f9d6844

Observation 10257109-a9df-4153-b93e-5099e51628d9 · inbound

Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models cites this paper.

Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models The Cost of Training NLP Models: A Concise Overview

Reference 142

Resolution
verified exact
arxiv_id, observed 2026-07-03T00:27:29.573111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-27T17:13:46.335347Z digest=sha256:335c489a797d5ce43212e0e4a47f9d34334bc015af6e1e18aca93b7ba29584f3

Observation d304d835-8439-4c07-a847-ed9c62b28e30 · inbound

Data Provenance for Image Auto-Regressive Generation cites this paper.

Data Provenance for Image Auto-Regressive Generation The Cost of Training NLP Models: A Concise Overview

Reference 121

Resolution
verified exact
arxiv_id, observed 2026-06-30T10:44:37.328290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

source=arxiv_source observed=2026-06-30T10:28:59.577056Z digest=sha256:e00f23458b09ff2f583efc08c7b4f5d07b95e7af575d76be38cf8855fd8d67df