Pith. sign in

Paper Citation Record · LEDGER

Enhancing CLIP Conceptual Embedding through Knowledge Distillation

As of 12 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 2026-08-12T06:34:41.77262+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

Resolution
unresolved
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:f27504bb98868bff527403faae2a359beab83347a9d77fb65df979faf1841b1f

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

Resolution
unresolved
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=sha256:3c5844fd85b6d0494ca993be5236d167e0b349169eba823c1c9c0b76ff11c392

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

Resolution
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=sha256:84cc02b1aaccbfe198282af154344048894431360627ecca4c03e547ce9a0162

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

Resolution
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=sha256:3c4f71fa8f8746acd8561d3b49f1377303f45a829c64e751470e5c95eb2e5dac

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

Resolution
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:bcefa0841bbabbdc61928c3ed601de19d623e373c4f3241cb014d15f080ef395

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

Resolution
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:fa8ed2bc055cc209413b3164a8a947fd77b425f3287ebb841dcda595fb8d22af

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

Resolution
unresolved
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:da43c827a413e203d0e08a4aa9bb3c86ed055020c9ef7ae35582dd179ddeffa0

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

Resolution
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 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T22:24:06.752891Z digest=sha256:a6f4ae7c8165c3ae0ad3044f3ff7ae66c9090759c4d4f356019d96a8d0c92dd1

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

Resolution
unresolved
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:b8870170b2c3453414bcb88fda11f09bbdd1edd29a1a430658aa926f7e6e08d2

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

Resolution
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:a949f33ad7bcb0ac8bf6b436c84eb7fabea6be4b3ecd88fcbc44d8e7d7099e71

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

Resolution
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:c900a7ea23cc29ec165e974cfa8e5fc064bc1799e6039e3c3a9dfe2cc4a32dd1

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

Resolution
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:aed5a91c25f3294ec6f83df0edde3f9140300604dacc5272629d10d2102bb835

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 2026-08-12T06:34:41.77262+00:00.

source=arxiv_source observed=2026-08-11T22:24:06.772843Z digest=sha256:b9316ae93393482d65bc1c72b2a432014a949ae9fca5a9e4524386bb322e8703

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

Resolution
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:fc38820dec90b73c483a0cee6c22176ec1c19d06d0055d1125e2f9c5816fa338

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

Resolution
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=sha256:69c7029e1f91218aabadf1b119ac868dba63823c370ed0dabde0b70f910be017

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

This paper cites URL: " 'urlintro :=.

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

Reference 16

Resolution
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=sha256:051a55ce3a0a309c3036a9e784dd5deb1550248ea9d776495050841bcfb42356

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

This paper cites write newline.

Enhancing CLIP Conceptual Embedding through Knowledge Distillation write newline

Reference 17

Resolution
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:b690fd21de5197a622ea1e1b4a35d7e6a8953adc9d29dd2275387dc9af3244b8

Pith citing papers

No inbound Pith citation observations are available.