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Paper Citation Record · LEDGER

Enhancing CLIP Conceptual Embedding through Knowledge Distillation

As of 18 August 2026, this Paper Citation Record lists 17 of 17 outbound references and 0 inbound Pith citation observations for arXiv:2412.03513.

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

pith.paper-citation-record.v1
2412.03513 v2

Coverage vector

measured 17 of 17 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T22:24:06.788727Z

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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

17 of 17 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 13ec0a32-35b0-4793-b0bf-0918a3b712f2 · outbound

This paper cites Knowledge Distillation from Internal Representations.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation Knowledge Distillation from Internal Representations

Reference 1

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no resolver link, observed 2026-08-11T22:24:06.722773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:24:06.722773Z digest=sha256:e6735d773b8c44a63b326c4569546249a0c230f8ffb71d1611b10864adac6aed

Observation 35881b1d-5b70-4877-a0be-9db346d04fa3 · outbound

This paper cites Do Deep Nets Really Need to be Deep?.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation Do Deep Nets Really Need to be Deep?

Reference 2

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no resolver link, observed 2026-08-11T22:24:06.727634Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:24:06.727634Z digest=sha256:2160f652da3fdd8d28aae815a66db69c15b0c31c79ca5e00b4dd80ddd6994605

Observation a0a06ef4-5215-4702-b268-a15f8565f823 · outbound

This paper cites Benchmarking Spatial Relationships in Text-to-Image Generation.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation Benchmarking Spatial Relationships in Text-to-Image Generation

Reference 3

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unresolved
no resolver link, observed 2026-08-11T22:24:06.731834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:24:06.731834Z digest=sha256:32a72f8d2a9edd1dd37d3e494abaaca0d25a884e1cc54306d2543ed268ebdec2

Observation 76adfcd2-8fb9-4e3c-8556-8c434a859e0c · outbound

This paper cites an unresolved cited work.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation Unresolved cited work

Reference 4

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unresolved
no resolver link, observed 2026-08-11T22:24:06.736142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:24:06.736142Z digest=sha256:9d5146714f2ec2b4e0c5ba45e0f3512cf884a025d4a55fc8f99be9fee668ad42

Observation 087af6c0-b93b-4adb-87ef-7074ef5f4f58 · outbound

This paper cites TinyBERT: Distilling BERT for Natural Language Understanding.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation TinyBERT: Distilling BERT for Natural Language Understanding

Reference 5

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unresolved
no resolver link, observed 2026-08-11T22:24:06.740158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:24:06.740158Z digest=sha256:d5af85f224c5fd58745e2b2de6d6cc663fb6d9d687d374b13c70aa846ede2795

Observation 7f7f135c-6b80-4c70-b083-f897bfa98c23 · outbound

This paper cites Text encoders bottleneck compositionality in contrastive vision-language models.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation Text encoders bottleneck compositionality in contrastive vision-language models

Reference 6

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unresolved
no resolver link, observed 2026-08-11T22:24:06.744349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:24:06.744349Z digest=sha256:aacd5fb7aeb1ccd89f21746a9ef5c491fc724847e4872cc3793544dba46cd26f

Observation dc0e7c27-9317-4d96-b877-43ec2caeae94 · outbound

This paper cites Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation Comparing Kullback-Leibler Divergence and Mean Squared Error Loss in Knowledge Distillation

Reference 7

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no resolver link, observed 2026-08-11T22:24:06.748831Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:24:06.748831Z digest=sha256:db045e973694b1d5316cd7943a38552b6c5ea28d01fe2821ba7391ac6616b654

Observation e789e2cf-3500-40c0-bba7-b700658f7607 · outbound

This paper cites an unresolved cited work.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation Unresolved cited work

Reference 8

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unresolved
raw_fallback, observed 2026-08-11T22:24:06.971100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T22:24:06.752891Z digest=sha256:03e357fc3f53ad93aff8ae44294170b0375d54e080b4de6c4ef5cec95e8cc7a5

Observation 133db7c9-7cb1-4d68-a032-e4e15956ee6e · outbound

This paper cites an unresolved cited work.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation Unresolved cited work

Reference 9

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no resolver link, observed 2026-08-11T22:24:06.756635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:24:06.756635Z digest=sha256:7b7d853b300e5f90db6d288d21bce14000edd48533dbda6ae034055dc9551fa6

Observation 0ade66f6-e0f5-442c-9fe1-4dbcc5e592af · outbound

This paper cites FitNets: Hints for Thin Deep Nets.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation FitNets: Hints for Thin Deep Nets

Reference 10

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unresolved
no resolver link, observed 2026-08-11T22:24:06.760196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:24:06.760196Z digest=sha256:aaecfd85f50ce49a2e37cec1e50358227b171b784800745bf8e5390eb883dfd6

Observation efa37557-38fb-4dfb-a641-5713c1c5cc24 · outbound

This paper cites Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation Winoground: Probing Vision and Language Models for Visio-Linguistic Compositionality

Reference 11

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unresolved
no resolver link, observed 2026-08-11T22:24:06.764337Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:24:06.764337Z digest=sha256:56db04c9ce80ab57c8d2c4e99782b0272869014075af06ee62f41f317c685024

Observation f19d5143-93d7-4028-9b9b-4f8032e32be8 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 12

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unresolved
no resolver link, observed 2026-08-11T22:24:06.768581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:24:06.768581Z digest=sha256:8c7486024239537617d56c7566f295690634a29d29780bb3fa28b96a26a52818

Observation ed15c2f9-7a7b-4711-a7f7-93e3141971b3 · outbound

This paper cites Belongie.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation Belongie

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-08-11T22:24:06.952823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

source=arxiv_source observed=2026-08-11T22:24:06.772843Z digest=sha256:c8758fd6d2d109ae7616e5427a840fe0608f3f981d4768bb4eeb0de065056f78

Observation 93352fcd-3388-4906-9044-c347724052b0 · outbound

This paper cites Zero-Shot Learning -- A Comprehensive Evaluation of the Good, the Bad and the Ugly.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation Zero-Shot Learning -- A Comprehensive Evaluation of the Good, the Bad and the Ugly

Reference 14

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unresolved
no resolver link, observed 2026-08-11T22:24:06.776535Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:24:06.776535Z digest=sha256:0bad8c5589e9805c7f7ea780f0aa83a1b4e167cfacbfb5dbf353e33f2c9f7dac

Observation 96a26a43-d54f-4170-b4aa-97439c27ece7 · outbound

This paper cites When and why vision-language models behave like bags-of-words, and what to do about it?.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation When and why vision-language models behave like bags-of-words, and what to do about it?

Reference 15

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unresolved
no resolver link, observed 2026-08-11T22:24:06.780353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:24:06.780353Z digest=sha256:77782e21758767233e68c8699b5ceabdc75940e485decf79cf94eccf070da714

Observation 60e0bff0-3a71-41d6-ba6f-80f3fa6183e3 · outbound

This paper cites URL: " 'urlintro :=.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation URL: " 'urlintro :=

Reference 16

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unresolved
no resolver link, observed 2026-08-11T22:24:06.784294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:24:06.784294Z digest=sha256:3b2b584f349d1c11217826571969e3d7b85d73e171812a326a4eeb96fbb13550

Observation fdcc2ae7-8f54-4b25-ae7d-68f58fa2fc14 · outbound

This paper cites write newline.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation write newline

Reference 17

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unresolved
no resolver link, observed 2026-08-11T22:24:06.788727Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T22:24:06.788727Z digest=sha256:d1863712190dbc83c4630c13c498751910aac5db7f3f8ce0c24a2b82dfad1cfa

Pith citing papers

No inbound Pith citation observations are available.