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Paper Citation Record · LEDGER

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP

As of 19 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 1 inbound Pith citation observation for arXiv:2505.18434.

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

pith.paper-citation-record.v1
2505.18434 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:35:00.461950Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-15T19:15:11.575505Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-15T19:16:31.450717Z

Reference resolution

40 of 40 outbound references displayed

  • verified exact1
  • verified fuzzy1
  • unresolved38
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c9d0cb42-2f23-4ea5-9148-2962863cff81 · outbound

This paper cites online" 'onlinestring :=.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP online" 'onlinestring :=

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:34:57.896668Z digest=sha256:58713a96471323673d299ebe0e0b0948a82f05f6a3c665d4c8106941751baa6a

Observation 306b044b-2668-49fe-aaf1-d7081cfcad73 · outbound

This paper cites write newline.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP write newline

Reference 2

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source=arxiv_source observed=2026-08-07T14:34:58.031815Z digest=sha256:4907378ee50b21793c9cea0064a15b7f408cc0268088c0cac876e248b2640cec

Observation 6a51e034-03ea-4726-a7a1-89714e6234a0 · outbound

This paper cites Vision-Language Models Do Not Understand Negation.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Vision-Language Models Do Not Understand Negation

Reference 4

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T14:34:58.344234Z digest=sha256:3c4a024e0ad9659c77a5802cbe01c4f00988244a50b47d3496436d7474947040

Observation 2b108680-dfdc-46d3-b705-51d38cde0f40 · outbound

This paper cites O'Reilly Media, Inc.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP O'Reilly Media, Inc

Reference 5

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no resolver link, observed 2026-08-07T14:34:58.468407Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:34:58.468407Z digest=sha256:2a30779e3bec2ee01bbfdd6acfc8476010862e9236ea17fe28ec2117d079911d

Observation d2b9491a-266b-4ec7-bef6-c6006df35f50 · outbound

This paper cites Language Models are Few-Shot Learners.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Language Models are Few-Shot Learners

Reference 6

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source=arxiv_source observed=2026-08-07T14:34:58.621742Z digest=sha256:9c101890178d98e588dc9b420b5d4ea2f26061766ec0ef5c8ce9b4a33a45fcf3

Observation e79b67e6-d8cc-4ebe-b975-5d3dea00e77c · outbound

This paper cites an unresolved cited work.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Unresolved cited work

Reference 7

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:34:58.797807Z digest=sha256:6fdcc61cc40d8bea48f4529440b590300f387b05ee67face3fb6cdf69ee6aaa8

Observation d6a4368f-86b2-4cff-ba4a-aed2cc1eaf71 · outbound

This paper cites an unresolved cited work.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Unresolved cited work

Reference 8

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raw_fallback, observed 2026-08-07T14:35:01.388403Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T14:34:58.904318Z digest=sha256:914a75384aaae23b8106abe86ea25b470de9ddb763024bea5fdec244ee472465

Observation 24bc5e7d-237e-4aea-a8b8-1b81580e35b4 · outbound

This paper cites Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Conceptual 12M: Pushing Web-Scale Image-Text Pre-Training To Recognize Long-Tail Visual Concepts

Reference 9

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T14:34:59.063835Z digest=sha256:55df3addffb06ac97eeb8294d13ecf22a3fcb9deb963105d2ff512f8120e6221

Observation 96eaa59d-1ad0-4f11-bbc3-5b58e322ed64 · outbound

This paper cites Impact of Noisy Supervision in Foundation Model Learning.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Impact of Noisy Supervision in Foundation Model Learning

Reference 10

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source=arxiv_source observed=2026-08-07T14:34:59.229920Z digest=sha256:3fa5f03cfe054bd22e06a1208e030b51cce41d2af786763cfab952ba7f009b65

Observation ed928f12-0e0e-4068-9a70-60c50677747e · outbound

This paper cites Microsoft COCO Captions: Data Collection and Evaluation Server.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Microsoft COCO Captions: Data Collection and Evaluation Server

Reference 11

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:34:59.356659Z digest=sha256:164b8522efd39e0b4ad7e1f2b1f08d972fd41526b3d5f48351ea332e5dbb73da

Observation 4b592db5-4eaa-4624-8c27-6084533a4246 · outbound

This paper cites an unresolved cited work.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Unresolved cited work

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T14:34:59.511051Z digest=sha256:22fbac7c5de2dc3716af6c800296f8d0497637e1b62bf2df70ef278092e40d4e

Observation f001e031-08e8-45ac-967e-f2ee853f5eca · outbound

This paper cites Scaling Instruction-Finetuned Language Models.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Scaling Instruction-Finetuned Language Models

Reference 13

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source=arxiv_source observed=2026-08-07T14:34:59.627115Z digest=sha256:5ed4d4b91cf36769a398003d1c7f124df3aba3e915e659e0270978d19b95b13f

Observation 2b5ce8d2-4753-4f89-bbac-cb02303aa3f5 · outbound

This paper cites an unresolved cited work.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Unresolved cited work

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T14:34:59.747994Z digest=sha256:c02295ce7893a744ea9b94bd4559b4deba2e6190398402441509ffe8b26af4e1

Observation 47d76b6c-c3b1-46c2-9c1f-99288e3e0672 · outbound

This paper cites Everingham, L.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Everingham, L

Reference 15

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verified fuzzy
raw_fallback, observed 2026-08-07T14:35:01.330130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T14:34:59.863173Z digest=sha256:9c4f03a9917fadcc7b6627f50386ea1f01f66a42a1647ec3a44611d70e8d366a

Observation 1a41bdd0-012e-4d5d-9687-6606f9dd0f03 · outbound

This paper cites an unresolved cited work.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Unresolved cited work

Reference 16

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T14:35:00.036352Z digest=sha256:61600c42d5daa3b4af4be1556b9c977be925dca74dccaae698fa4a90b4b987b3

Observation dcf6fbc6-a23b-4a18-bb99-9ffac3e87109 · outbound

This paper cites an unresolved cited work.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Unresolved cited work

Reference 17

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raw_fallback, observed 2026-08-07T14:35:01.312841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T14:35:00.179358Z digest=sha256:2865f2a851a348124f2c114a935fca6cfe65d52cc56d020aee5213a5d3b94a58

Observation ecd4db44-fa06-448d-b888-2d51b40f7100 · outbound

This paper cites an unresolved cited work.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Unresolved cited work

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.281112Z digest=sha256:26ff2a43e924c7a06baf9ad0f85b46aa8d879d2603ad116a014815696d3a86ab

Observation 338c2a94-95c9-43ff-94cb-622dd6a851e1 · outbound

This paper cites TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP TIFA: Accurate and Interpretable Text-to-Image Faithfulness Evaluation with Question Answering

Reference 19

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T14:35:00.351522Z digest=sha256:d9bc5eac7ee47c3ac91426088132204fe2c76004ec5923e0b471d81d16474127

Observation d320334e-ef9c-49b0-aac3-8208f8a951de · outbound

This paper cites Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Adaptive Data Optimization: Dynamic Sample Selection with Scaling Laws

Reference 20

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source=arxiv_source observed=2026-08-07T14:35:00.356911Z digest=sha256:82abec159ab337c5c79221805cd9656af0fc2f7a58b24a830fb6ba6f8c020d3c

Observation 8bddf210-a09c-4092-910c-691bb03ca8db · outbound

This paper cites an unresolved cited work.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Unresolved cited work

Reference 21

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T14:35:00.361568Z digest=sha256:37a90f6cdf54c9e0e41881dc809e2351fa560edd33505bb49a6671ef01ab759c

Observation d3fed293-b268-4ba2-9eff-878f1981a22d · outbound

This paper cites Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Fine-Tuning can Distort Pretrained Features and Underperform Out-of-Distribution

Reference 22

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T14:35:00.366526Z digest=sha256:32fcad7e0afe28fb1c4c555bd49979db4f2136988309f86cfc2d26818c435b68

Observation 8aceb938-ba68-4d48-bf61-407c5439ebde · outbound

This paper cites an unresolved cited work.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Unresolved cited work

Reference 23

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no resolver link, observed 2026-08-07T14:35:00.371300Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.371300Z digest=sha256:401115c047c17e78f5cd486b80a9b770b8f4b716ac77247d0811f3859b3b8360

Observation fa7b9d85-8e92-4008-8008-7d8ef8d08a2f · outbound

This paper cites GPT-4o System Card.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP GPT-4o System Card

Reference 24

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-07T14:35:00.376552Z digest=sha256:0936a349a677294b2a4e65c295a1c9c3c805fd0f77690e899f52178fe6fe2ad4

Observation b2e067bb-131c-47b9-b3db-ca0b521d1a5f · outbound

This paper cites Training language models to follow instructions with human feedback.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Training language models to follow instructions with human feedback

Reference 25

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.381255Z digest=sha256:5d03087de8ac60052dfa71e56f0d49191db25f24f705f75074737100106b3939

Observation 2a9a22b1-ff96-4627-9f31-8f3b6b1c68b1 · outbound

This paper cites an unresolved cited work.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Unresolved cited work

Reference 26

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.386059Z digest=sha256:d72fa159e0b59b903f4adfe994dbfcf856e8dc809c307c4488514268afc55cf6

Observation f12c39f5-396f-4035-bf27-1220bb29279f · outbound

This paper cites an unresolved cited work.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Unresolved cited work

Reference 27

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.391230Z digest=sha256:6709ae8365cf5ae736db45609354eead055e54afed16876764716335815b44b2

Observation be44f958-c33a-4fd3-8214-91d47c34f5a9 · outbound

This paper cites Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Flickr30k Entities: Collecting Region-to-Phrase Correspondences for Richer Image-to-Sentence Models

Reference 28

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.396259Z digest=sha256:b8e5e3c238840244570f591a695a32a46b497a1ce8b04563d6eafaa79a973395

Observation 081d8f11-b579-4847-af2e-bf6959768789 · outbound

This paper cites How and where does CLIP process negation?.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP How and where does CLIP process negation?

Reference 29

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no resolver link, observed 2026-08-07T14:35:00.401122Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.401122Z digest=sha256:5fdaaa35b2adb01fe6b203db1adc20ce170dce44c5c00804167c4db47732c556

Observation 78d32ba2-ff16-40f4-b03b-4182cc671e6b · outbound

This paper cites Learning Transferable Visual Models From Natural Language Supervision.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Learning Transferable Visual Models From Natural Language Supervision

Reference 30

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no resolver link, observed 2026-08-07T14:35:00.406088Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.406088Z digest=sha256:f04953b699bbe7052639d3182916297c6a814bc26ad839b72aeb8fd14788d222

Observation 94964b6f-697f-4780-b5ff-52f8dd83537c · outbound

This paper cites Deep Learning is Robust to Massive Label Noise.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Deep Learning is Robust to Massive Label Noise

Reference 31

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no resolver link, observed 2026-08-07T14:35:00.411297Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.411297Z digest=sha256:d8798328aecb42d1609b07ae0e50779f8486719b99268af6f5fe340a905e0e51

Observation 21b6a9be-a77f-4c24-a7ce-059127703e79 · outbound

This paper cites High-Resolution Image Synthesis with Latent Diffusion Models.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP High-Resolution Image Synthesis with Latent Diffusion Models

Reference 32

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no resolver link, observed 2026-08-07T14:35:00.417623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.417623Z digest=sha256:a7b0bbb711f71f2c0bcc0c4cdc8b98a81bf448f4afd10d3fb645048b1a7f5370

Observation e7af6781-2a22-4476-b321-3d843c4160e8 · outbound

This paper cites Learn "No" to Say "Yes" Better: Improving Vision-Language Models via Negations.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Learn "No" to Say "Yes" Better: Improving Vision-Language Models via Negations

Reference 33

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.422103Z digest=sha256:d4482e9661b95845dbb3fdeefc4a1061e2e33d1804dc9862b9ee51a6f19dc4cd

Observation 3ad4ee9f-4a6c-485e-aa14-4980c0338733 · outbound

This paper cites Language models are not naysayers: An analysis of language models on negation benchmarks.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Language models are not naysayers: An analysis of language models on negation benchmarks

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.426587Z digest=sha256:baee148affe2aff4ba3a012b22d09777c7b468da035c48d06d8f0ad44a8ef69a

Observation a242486e-4317-48d8-ba10-ddb9dd126f08 · outbound

This paper cites an unresolved cited work.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Unresolved cited work

Reference 35

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.433365Z digest=sha256:e276ed3fffd2254008fcfc16e27b9e229c118d08c443c2af6ae7140de7bc6836

Observation 536df0a5-e6e6-4cc0-ba2f-6f9bd21f55ab · outbound

This paper cites Investigating and Addressing Hallucinations of LLMs in Tasks Involving Negation.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Investigating and Addressing Hallucinations of LLMs in Tasks Involving Negation

Reference 36

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no resolver link, observed 2026-08-07T14:35:00.437911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.437911Z digest=sha256:1dd60e7158de384b05c801bf0ac3666f7453f32b85c92f6e56ca6a529d489c52

Observation 71c6ea5d-ee54-48e8-9f1c-25d5aa41e6f5 · outbound

This paper cites Dynamic Sentence Sampling for Efficient Training of Neural Machine Translation.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Dynamic Sentence Sampling for Efficient Training of Neural Machine Translation

Reference 37

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verified exact
local_arxiv, observed 2026-08-07T14:35:00.751105Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-08-07T14:35:00.442422Z digest=sha256:a50fc962074ebca217ec0f943bbd469e1cfba4c2bfcddee53a67d710dee4d077

Observation da38d354-1cf5-4f4f-930b-eb6cb87ca16a · outbound

This paper cites Ehinger, Aude Oliva, and Antonio Torralba.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Ehinger, Aude Oliva, and Antonio Torralba

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.447280Z digest=sha256:e596403998e8b8281a0a140ebc0baa0e79b906d356126d804e4bf7d4bd0551d6

Observation 873d0639-3ea1-42a6-9779-70aaa38b6784 · outbound

This paper cites Self-training with Noisy Student improves ImageNet classification.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Self-training with Noisy Student improves ImageNet classification

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T14:35:00.452635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.452635Z digest=sha256:3616dfca08e76857b9375fa1742341698d930e25ef7e554cf275625066724217

Observation 3b905e8a-b3f0-4abc-a0ef-56ac6cc61eab · outbound

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

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP When and why vision-language models behave like bags-of-words, and what to do about it?

Reference 40

Resolution
unresolved
no resolver link, observed 2026-08-07T14:35:00.457612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.457612Z digest=sha256:c8b0b5883ad8bae246a69732c5c3b048ddbdc2df803d4f84b62e1c7416341edd

Observation 63328273-7ae5-40af-986b-50220ad4acde · outbound

This paper cites Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models.

TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP Beyond Positive Scaling: How Negation Impacts Scaling Trends of Language Models

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-07T14:35:00.461950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:35:00.461950Z digest=sha256:d29a367863805b5e491d48deb5214f03ca2d836e00d4b538cf2a1933fb0d989d

Pith citing papers

Observation 5359fe90-338b-42bc-8583-488d140a8ca2 · inbound

Exploring the AI Obedience: Why is Generating a Pure Color Image Harder than CyberPunk? cites this paper.

Exploring the AI Obedience: Why is Generating a Pure Color Image Harder than CyberPunk? TNG-CLIP:Training-Time Negation Data Generation for Negation Awareness of CLIP

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-15T19:16:31.454290Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-15T19:15:11.575505Z digest=sha256:52ee0c12ecbb2464c5e219b932efd940b78890f7cd46e76c9ce4ab1dc7db619d