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Paper Citation Record · LEDGER

Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs

As of 8 August 2026, this Paper Citation Record lists 14 of 14 outbound references and 0 inbound Pith citation observations for arXiv:2505.22937.

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

pith.paper-citation-record.v1
2505.22937 v1

Coverage vector

measured 14 of 14 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:00:19.948091Z

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

14 of 14 outbound references displayed

  • verified exact1
  • verified fuzzy0
  • unresolved13
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 32ea67e1-72d1-49fb-9399-10708895a6ec · outbound

This paper cites ALBERT: A Lite BERT for Self-supervised Learning of Language Representations.

Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T13:00:18.645319Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:00:18.645319Z digest=sha256:16891eb4b5e17c74ef5259103992d3751494b2e7ef3cfdc41ed3195ab2535d8f

Observation 1998310f-49a7-4008-9da2-c5345659f054 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T13:00:18.745978Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:00:18.745978Z digest=sha256:605771daa3bf518892b34a56c2b6583a055226fd8dbca843271eed8f876d8587

Observation 4051f030-8926-461b-bf2a-e1e7591822f3 · outbound

This paper cites Are Sixteen Heads Really Better than One?.

Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs Are Sixteen Heads Really Better than One?

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T13:00:18.891139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:00:18.891139Z digest=sha256:482ef7286c969af05603cd0520b2c2b6297bd8ac1cfba474c591ace5a737e86f

Observation 7c845ed8-4996-4754-87e4-119710cf40ef · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-07T13:00:19.234347Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:00:19.234347Z digest=sha256:c7464037510d4846056d55bada875c79c67ac117493fc075e7253f5d0b640b37

Observation ada6274c-ce72-406c-8c9e-e7e5458145de · outbound

This paper cites MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices.

Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs MobileBERT: a Compact Task-Agnostic BERT for Resource-Limited Devices

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-07T13:00:19.341875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:00:19.341875Z digest=sha256:069dc18aa07c605677423e9afda7f1fcb97162451da07ce58808060672d75be1

Observation 5939c643-4574-4da8-8e76-c5e1d1ca55b5 · outbound

This paper cites EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks.

Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T13:00:19.476496Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:00:19.476496Z digest=sha256:127f4963f3b86c9a80920da8f2d2b940d261ef488853471b97c27ba21709a761

Observation b1ca2b39-0f77-464d-85a4-f1a871a109da · outbound

This paper cites HuggingFace's Transformers: State-of-the-art Natural Language Processing.

Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs HuggingFace's Transformers: State-of-the-art Natural Language Processing

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-07T13:00:19.587939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:00:19.587939Z digest=sha256:d41b3f3362120966a714f5c144a28045a96f584f431c5843a46bf0991f6ebba9

Observation 3816da20-5b77-433d-9b3a-17589c51fc40 · outbound

This paper cites URL http://dx.doi.org/10.18653/v1/N19-4013.

Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs URL http://dx.doi.org/10.18653/v1/N19-4013

Reference 12

Resolution
verified exact
doi, observed 2026-08-07T13:00:20.155159Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-07T13:00:19.691332Z digest=sha256:836f93d4109cd7de948715624966e83fe5590bc587ba435640a29cddc8753b02

Observation 1d886ad3-6a42-4a60-a9b7-53dc96b9b740 · outbound

This paper cites XLNet: Generalized Autoregressive Pretraining for Language Understanding.

Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs XLNet: Generalized Autoregressive Pretraining for Language Understanding

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T13:00:19.816137Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:00:19.816137Z digest=sha256:179b8f6eeddaf87dd3f09597ccd78d432128111051fe0ee9a6149325e68cd592

Observation fab35afe-435a-47da-a9a4-b80506ac0f48 · outbound

This paper cites URL http://dx.doi.org/10.1109/EMC2-NIPS53020.

Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs URL http://dx.doi.org/10.1109/EMC2-NIPS53020

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T13:00:19.948091Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:00:19.948091Z digest=sha256:915444742713c90b7f3b741859a550a02b7798fa03e764cbcc76ec5d4c8aaba2

Observation 53b41c09-7f34-4f69-9018-634b80448b36 · outbound

This paper cites SQuAD: 100,000+ Questions for Machine Comprehension of Text.

Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs SQuAD: 100,000+ Questions for Machine Comprehension of Text

Reference 2016

Resolution
unresolved
no resolver link, observed 2026-08-07T13:00:19.141127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:00:19.141127Z digest=sha256:3b08388b686928867ce7651153c481c48149bcb30f9febaa34ecbaca7419c1eb

Observation a68421f2-6cb5-446c-ad3f-d3500979cc43 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-07T13:00:18.556909Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:00:18.556909Z digest=sha256:d5172f9c1a2ddba3166467912799ddb937ed48f172ff2f9ea3b12f781efb6a22

Observation 1f551861-26df-408a-bf21-8f56a6aacc2c · outbound

This paper cites ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators.

Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs ELECTRA: Pre-training Text Encoders as Discriminators Rather Than Generators

Reference 2020

Resolution
unresolved
no resolver link, observed 2026-08-07T13:00:18.472231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:00:18.472231Z digest=sha256:486149c199f60bb6f9ee2029eb8dd38303f6ad4bb3a635579a588a9111db52f8

Observation 049b5480-c4af-4aab-bfbc-5a321cc6a88b · outbound

This paper cites Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer.

Improving QA Efficiency with DistilBERT: Fine-Tuning and Inference on mobile Intel CPUs Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer

Reference 2023

Resolution
unresolved
no resolver link, observed 2026-08-07T13:00:19.029127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:00:19.029127Z digest=sha256:6003e1e2e50174c84c6e0caeb717dda9ba6fe86169b0b39fe42183d8b759d59a

Pith citing papers

No inbound Pith citation observations are available.