Pith. sign in

Paper Citation Record · LEDGER

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data

As of 18 August 2026, this Paper Citation Record lists 78 of 78 outbound references and 1 inbound Pith citation observation for arXiv:2505.10551.

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

pith.paper-citation-record.v1
2505.10551 v1

Coverage vector

measured 78 of 78 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T21:10:42.342685Z

measured 79 of 79 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T19:14:24.554237Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-28T19:22:34.797020Z

Reference resolution

78 of 78 outbound references displayed

  • verified exact1
  • verified fuzzy28
  • unresolved49
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bffdd981-6824-4eb3-8dd8-1258ec3cb761 · outbound

This paper cites GPT-4 Technical Report.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data GPT-4 Technical Report

Reference 1

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:41.998958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:41.998958Z digest=sha256:482e2c1ef9f89b379355ec2821785455e9e7cb38250bdf0f2b68d30ef61ae3be

Observation f84b8cea-ec84-4ecd-9cfe-6f91401b9f3d · outbound

This paper cites VisMin: Visual Minimal-Change Understanding.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data VisMin: Visual Minimal-Change Understanding

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.004742Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.004742Z digest=sha256:f8645f3075d135dc0d24df676a7ec4e3cda2db4f3da1dfe993433bcc05d1c8e3

Observation ee9fbef3-5e17-4273-b740-cf9e563146a2 · outbound

This paper cites ClearDepth: en- hanced stereo perception of transparent objects for robotic manipulation.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data ClearDepth: en- hanced stereo perception of transparent objects for robotic manipulation

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.010452Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.010452Z digest=sha256:a6ad4da05db62f943725e32bfe1d119b70418156cdb6e9fabee57fe0f96ae82e

Observation 3a25e97c-268a-4ea5-8c85-77d0a69c48d9 · outbound

This paper cites Deep learners benefit more from out-of-distribution examples.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Deep learners benefit more from out-of-distribution examples

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.615905Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.015118Z digest=sha256:cfeb85518c36b90be96d5c28e8a9ef6449ca8a1a6270f0f1799b2ea0a65559dd

Observation 1db83f7d-3114-4748-8960-00ceb7e99541 · outbound

This paper cites Briaai background removal v1.4 model, 2024.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Briaai background removal v1.4 model, 2024

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.601370Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.020031Z digest=sha256:27e16c29af421228ffeab9db21994754fecaacbdcc0419b8e3ca31dbc5767b1c

Observation e78722a1-ef94-4991-a15c-b527a6528fdd · outbound

This paper cites In- structpix2pix: Learning to follow image editing instructions.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data In- structpix2pix: Learning to follow image editing instructions

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.586681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.025632Z digest=sha256:c3101d4a01cf66ffc5605d730f95e61e28a6083f21fd50c763f86f4afc31fcce

Observation 6d980ffe-b908-4610-b01d-900a181c66ed · outbound

This paper cites Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Internvl: Scaling up vision foundation mod- els and aligning for generic visual-linguistic tasks

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.030220Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.030220Z digest=sha256:2824dd8e67286cafe238d508040ef5da10a7d8203edfa949d5e217847545fd9c

Observation ab8ddb00-b181-4047-9c07-cc55ca03d7ee · outbound

This paper cites Diversified in-domain synthesis with efficient fine-tuning for few-shot classification.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Diversified in-domain synthesis with efficient fine-tuning for few-shot classification

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.035057Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.035057Z digest=sha256:854fa44823321bcf1e3a7f83df5cfefe2365a025b4658ef6fab717aadd75a4b5

Observation 944bb286-a044-4127-b543-9fe93d3c2a68 · outbound

This paper cites The value of out-of- distribution data.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data The value of out-of- distribution data

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.564027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.039822Z digest=sha256:5bffe907a9439f9093947cbed6d809df9eee6cef6eb203003086e91e6f52f831

Observation 08d31bd6-e4d6-43b8-9ff1-a99c081f2cd9 · outbound

This paper cites ImageNet: A large-scale hierarchical im- age database.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data ImageNet: A large-scale hierarchical im- age database

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.043667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.043667Z digest=sha256:2b21db5736f0297ec2600ecac207a527ec259575dfd8364ec6a0e6a7273b171f

Observation 84b6a56f-1403-406d-8527-f51fcd9bc176 · outbound

This paper cites The MNIST database of handwritten digit images for machine learning research.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data The MNIST database of handwritten digit images for machine learning research

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.540827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.049282Z digest=sha256:9657f724e9655fff5aac4d02e3334535cc315d1a3338baf4617ff860056ae10f

Observation 77e42b67-5b3b-43de-96c8-ac725f571e5a · outbound

This paper cites A Survey on In-context Learning.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data A Survey on In-context Learning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.053834Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.053834Z digest=sha256:933db9a248164de14c5b0a29463beef897a6ee063c561740d2c561135d870172

Observation 16a2c7e3-6c78-4dc3-9a4b-a8fa70d63c21 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.058517Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.058517Z digest=sha256:9c4b59d186e1c0e7e28b23a1c8304e72fcc474d894101894e7620e5ab42e6bb2

Observation 608bb21b-7799-43c4-b3d8-1d34487a1558 · outbound

This paper cites Gonzalez, and Trevor Darrell.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Gonzalez, and Trevor Darrell

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.524192Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.063086Z digest=sha256:a5428758db7b5f6afc4273f26048e0b540a1f1a2411c845fc9007490f0b3e4b9

Observation cac2b856-3983-44f4-b3ca-b21e21aa434a · outbound

This paper cites Deep genera- tive models for synthetic data: A survey.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Deep genera- tive models for synthetic data: A survey

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.511014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.068526Z digest=sha256:9e7b71fd0a66103c377174218fe429485f1beb6931fc5998eee8ee848971d723

Observation cc83ca00-d49f-49ec-95f8-cdb934a93134 · outbound

This paper cites Scaling laws of synthetic images for model training.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Scaling laws of synthetic images for model training

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.497562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.073567Z digest=sha256:e32d563e1e62be78bb3bce441c1dd5426e04e562ca171df64a26bc4fa7bc472e

Observation fe165deb-6fd8-4687-a98e-c1cdae2f2fdb · outbound

This paper cites Instagen: Enhancing object detection by training on synthetic dataset.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Instagen: Enhancing object detection by training on synthetic dataset

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.482603Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.077965Z digest=sha256:1c5521b308b8e9727482386c3a2bd1c8711a64cb85da072de0c0b20176fac745

Observation 70b28113-da9e-4f26-859f-9d5fb82a4797 · outbound

This paper cites Guiding Instruction-based Image Editing via Multimodal Large Language Models.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Guiding Instruction-based Image Editing via Multimodal Large Language Models

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.082483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.082483Z digest=sha256:5612254276743735fd9aaf65ba9831a6393d4304cbb1ef59588fd1cfd81000c7

Observation a7a4da35-5d6e-4922-8fee-50515a7e50a8 · outbound

This paper cites How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.086745Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.086745Z digest=sha256:9e3b9db14f3326c595d9f5d2cda069a09a77b193023e79d1a826d577142e8695

Observation 681c58b2-1ac7-4170-ae0d-dc6af8735631 · outbound

This paper cites Synthetic data in health care: A narrative review.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Synthetic data in health care: A narrative review

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.467669Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.090571Z digest=sha256:41cb691196c8b9f84a2bd63004d0b10b5052a0d54d251190f2e7e71f86e41612

Observation e903de15-6651-4519-a8fd-7b3e8298d618 · outbound

This paper cites Generative adversarial networks.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Generative adversarial networks

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.094479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.094479Z digest=sha256:0464337b8821e09d3f20d042eb9787c56ad9229dae14c88d70f9de247c1bdbee

Observation ad1547ba-d7d5-4064-8d4f-818eb3ad9b28 · outbound

This paper cites SynthCLIP: Are We Ready for a Fully Synthetic CLIP Training?.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data SynthCLIP: Are We Ready for a Fully Synthetic CLIP Training?

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.098029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.098029Z digest=sha256:4c36b282d658bc45f7af4b43a81ba9cb2b4c2acb65817b7ff1199cd4ab57cd8b

Observation b97555f4-8c5d-4be8-abb0-c898a73643b3 · outbound

This paper cites Deep residual learning for image recognition.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Deep residual learning for image recognition

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.102646Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.102646Z digest=sha256:d0ee04561b888d3e53d3ac038f704ca410c0a012012b4936d924c72cbbe9381f

Observation 30c65c69-1c03-4064-8359-904db1834762 · outbound

This paper cites Is synthetic data from generative models ready for image recognition?.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Is synthetic data from generative models ready for image recognition?

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.107261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.107261Z digest=sha256:2a6b281e1932819a3159552b12d945b03897d66e3f9cc9e59bdc49317d371220

Observation 517d8f73-1146-4dc6-a0f2-b888b653a584 · outbound

This paper cites Prompt-to-Prompt Image Editing with Cross Attention Control.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Prompt-to-Prompt Image Editing with Cross Attention Control

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.113042Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.113042Z digest=sha256:d9720a831d5df65ae8153cf9a79349ae10023409b0db22bffafc01fde86371ab

Observation 36c955e0-0b59-422d-8fb6-2f711c199944 · outbound

This paper cites Denoising diffu- sion probabilistic models.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Denoising diffu- sion probabilistic models

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.117758Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.117758Z digest=sha256:2ef6e330c4c6026639a9acd68c03466ea47d307ae7d6c9fb1cfddca2ddec92fc

Observation eadd8442-11d0-41f2-a66e-5c313a93cfd4 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data LoRA: Low-Rank Adaptation of Large Language Models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.122132Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.122132Z digest=sha256:a97e559f03f8bb42702ed4a3b361811506733ed8255d26d8010b6df148dabcb0

Observation 1135e8fd-6537-46ea-aa9c-2c202fcb0e8e · outbound

This paper cites DataDream: Few-shot Guided Dataset Generation.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data DataDream: Few-shot Guided Dataset Generation

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-15T21:10:42.719317Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.126974Z digest=sha256:60a97b9900e113a6f233c6a785be9679a2d70ecac57f05b812aa35d11e183243

Observation 4ef951ed-b21c-48c8-8447-99aa48911537 · outbound

This paper cites DiffBlender: Composable and Versatile Multimodal Text-to-Image Diffusion Models.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data DiffBlender: Composable and Versatile Multimodal Text-to-Image Diffusion Models

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.131433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.131433Z digest=sha256:0ffac2a3436c382edfc4f7ce651299d9f1a1d6872547b95934e67fb7f9017904

Observation 6f9752c9-7106-4450-a0c9-7dbabfb77f5f · outbound

This paper cites Auto-Encoding Variational Bayes.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Auto-Encoding Variational Bayes

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.136123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.136123Z digest=sha256:77e4b4398b11e8e4562f56f419dc3000134224b6587d8eddaf2b315548f91641

Observation a14f7b9b-dd51-4a81-96f1-b5a2616d8733 · outbound

This paper cites Segment any- thing.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Segment any- thing

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.140085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.140085Z digest=sha256:fb3b16446315335404b539f2e85573a5238b4acbc67f116c32dd7294d21ce140

Observation 319f22fb-d517-4ef9-ac2b-c99aa6802ed9 · outbound

This paper cites 3d object representations for fine-grained categorization.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data 3d object representations for fine-grained categorization

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.418096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.144400Z digest=sha256:15d41efae27cacaa22a575f0f168bea672223abb16b27b160c3bd1e77c806d20

Observation e7ea46e9-d1de-4577-9f25-37fe23b2fb37 · outbound

This paper cites LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data LLaVA-NeXT-Interleave: Tackling Multi-image, Video, and 3D in Large Multimodal Models

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.148824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.148824Z digest=sha256:35e7ca5cc1b4f40f69190633a316d92d0faa4231b9de48fd622e258bd2428fa7

Observation 681a6e61-13c7-4180-bd79-755b21756d53 · outbound

This paper cites Towards understanding cross and self-attention in stable diffusion for text-guided image editing.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Towards understanding cross and self-attention in stable diffusion for text-guided image editing

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.403420Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.153572Z digest=sha256:85f9352a4cb5351008204c1f685e1f2b02317729813d598aac1eabea6e969e94

Observation d689c804-64b5-47e0-8c89-2d400de8e3a0 · outbound

This paper cites Visual instruction tuning.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Visual instruction tuning

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.157957Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.157957Z digest=sha256:bd4462a1b5340c528442c519b82501ebd500f7efc251bf9023bec7ab2075da97

Observation ad313806-da34-44e1-9c95-9eda62ca76a3 · outbound

This paper cites Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Grounding DINO: Marrying DINO with Grounded Pre-Training for Open-Set Object Detection

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.162175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.162175Z digest=sha256:de426e5ef0edc4377c65440b1a15c319cbc458475d64350fbc7eae2c88a84522

Observation ecc64cc0-c05d-4f1f-8e9f-d3064490520d · outbound

This paper cites Summary of chatgpt-related research and perspective towards the future of large language models.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Summary of chatgpt-related research and perspective towards the future of large language models

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.379146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.166702Z digest=sha256:ede8898102d47306b273029eba7f8c5005b71ad8b907b3ee8c6052b1a2eb5947

Observation 4de8ee70-2ae3-438b-bef4-e2be3de2bc80 · outbound

This paper cites Decoupled Weight Decay Regularization.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Decoupled Weight Decay Regularization

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.170867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.170867Z digest=sha256:a0eff4d40f6b00ca7e840df09bd703d68af3988f11756220bc2a993ed41dc06e

Observation 0254a91e-11de-4c19-9081-9899e8e1f58a · outbound

This paper cites Repaint: Inpainting using denoising diffusion probabilistic models.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Repaint: Inpainting using denoising diffusion probabilistic models

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.363031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.175399Z digest=sha256:db17d420b05565ef62a0c0df32aa6b34f54a392ead6fec129019b674a478c84c

Observation aec88484-2490-46c7-be6e-dcb63c60f07e · outbound

This paper cites Inpainting using denoising diffusion probabilistic models.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Inpainting using denoising diffusion probabilistic models

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.348908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.179446Z digest=sha256:a7076241dddb518648b43dfda6c2d5def60b3ce35163ea1bde7c1cd1357eb8b4

Observation 2bd8a0e8-5f3c-40ba-adcd-eaf5fb3517d3 · outbound

This paper cites Fine-Grained Visual Classification of Aircraft.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Fine-Grained Visual Classification of Aircraft

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.183412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.183412Z digest=sha256:8ed012d0c18fa6327a79bebb5302bdcaeaddbdf4f78d489dc15ba5ac161fd84d

Observation 4a832c17-fcd7-4a8d-9a7b-30257ab8a7b3 · outbound

This paper cites Backpropagating through Fr\'echet Inception Distance.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Backpropagating through Fr\'echet Inception Distance

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.188381Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.188381Z digest=sha256:acf5f1cdc8044402ba8fb58dc0b8d99979e7f569c7e4bc8246a7fc59b520ba75

Observation 652e60a2-e14b-4757-a8a0-e92a9b3f353b · outbound

This paper cites Context Diffusion: In-Context Aware Image Generation.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Context Diffusion: In-Context Aware Image Generation

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.192748Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.192748Z digest=sha256:a4b2741fcd1948faac843ed3ff25f4332ace43e5e548a3e53d290bec57b3e379

Observation db77cfed-db33-42ae-820c-207fbea5e371 · outbound

This paper cites GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.196518Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.196518Z digest=sha256:a5bb437c9ece25db295f29f5f4924b3ec30f93c5902b5f2d01d6e4c3717a640a

Observation 6fbc2c98-7248-4674-9cf2-d620cce37e5d · outbound

This paper cites DINOv2: Learning Robust Visual Features without Supervision.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data DINOv2: Learning Robust Visual Features without Supervision

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.200425Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.200425Z digest=sha256:71e223719d3645acf4a2db2b0e6bd34386320970ce7cbae374ea24af577cde22

Observation 69fae5c4-7322-42f1-8ad7-1d5d63d9be7f · outbound

This paper cites Cats and dogs.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Cats and dogs

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.334636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.204322Z digest=sha256:d003343020a4596521b50a107b4a6b457112a0fcd80a8ca93d27d66690d2e807

Observation b999b8b9-eab1-43a2-87e4-1fc1961ecc45 · outbound

This paper cites Learning transferable visual models from natural language supervi- sion.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Learning transferable visual models from natural language supervi- sion

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.319818Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.208428Z digest=sha256:74c32d288072f83cb30d416f394381127d834ffd99fce75d279ab94dc814ee17

Observation eaffccd6-1aec-4ace-b880-21c41fabb15e · outbound

This paper cites In- finigen indoors: Photorealistic indoor scenes using procedu- ral generation.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data In- finigen indoors: Photorealistic indoor scenes using procedu- ral generation

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.304479Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.213083Z digest=sha256:b2ee378247a4911a4acecc75a99ad1d854cd3cfefb7f33dcea0a29a85a07b700

Observation 86aad177-fa2b-40e5-879c-f75053496fad · outbound

This paper cites Zero-shot text-to-image generation.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Zero-shot text-to-image generation

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.217721Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.217721Z digest=sha256:23b9bb923e75cf10495a363768ca64dc4950e5bcb5bfcf63213a15c07a599346

Observation 293d3615-c648-43d4-bddf-bead4c5a829e · outbound

This paper cites SAM 2: Segment Anything in Images and Videos.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data SAM 2: Segment Anything in Images and Videos

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.222159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.222159Z digest=sha256:98b72fb456da2eac49f2ecbfdb07d8f7802e4f6121bfbd8862639e714b5e19af

Observation 99329760-1782-4ff7-9414-8de0cc7ea1b9 · outbound

This paper cites High-resolution image syn- thesis with latent diffusion models.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data High-resolution image syn- thesis with latent diffusion models

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.279410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.226892Z digest=sha256:bf5547ad0bb6b8c1a73bb24254f91eb72a6eacfa33a83078dbd06f7e8d1dea93

Observation 9eb61ced-5c68-4b3b-8f86-5437ef19bc00 · outbound

This paper cites U- Net: Convolutional networks for biomedical image segmen- tation.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data U- Net: Convolutional networks for biomedical image segmen- tation

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.231212Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.231212Z digest=sha256:22649b99b1c35cf7c4e26a6144b886de01a9086ba993f08a4a66c181502c32bf

Observation e63801db-5efd-4d96-86a8-0df326f45c29 · outbound

This paper cites Photorealistic text-to-image diffusion models with deep language understanding.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Photorealistic text-to-image diffusion models with deep language understanding

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.235196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.235196Z digest=sha256:ec7c5fa9f5c9184faa7d041677781979cc0cf71839bdb817d61e0fda9802597c

Observation 83f10f8b-ae10-4951-aad4-f528558241d6 · outbound

This paper cites Fake it till you make it: Learning trans- ferable representations from synthetic imagenet clones.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Fake it till you make it: Learning trans- ferable representations from synthetic imagenet clones

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.246077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.239786Z digest=sha256:7b52bc8d4988bfe869890d84ae0ae78ecf4fe84ffd077aa105e84787c01a9b7c

Observation 0dc7e59a-3139-4fb5-9b69-b8107a6ff097 · outbound

This paper cites Diffumask: Synthesizing images with pixel-level annotations for semantic segmentation using dif- fusion models.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Diffumask: Synthesizing images with pixel-level annotations for semantic segmentation using dif- fusion models

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.232179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.244014Z digest=sha256:377a0d78d4d089d949c50f162e31088d6a5c67d89cd1bb7c1c9dc276c02e3cd7

Observation 2ce605e7-9d21-4d14-b369-95974fff0dd1 · outbound

This paper cites Paint by example: Exemplar-based image editing with diffusion mod- els.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Paint by example: Exemplar-based image editing with diffusion mod- els

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.248292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.248292Z digest=sha256:fbb5da7a5bc5af43f186a5bdf727462dcd01c51b3edfd4bf433befe3df48990a

Observation e696e49d-8a58-43cb-931c-1c3cb90398ff · outbound

This paper cites Generalized out-of-distribution detection: A survey.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Generalized out-of-distribution detection: A survey

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.208600Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.253667Z digest=sha256:753e1d71fa3b6e12fda3e1cdf3812c13e821fcef506bc82d50f1c408d531b629

Observation 61502ff2-cb5f-44d8-b80a-2f60d3203b45 · outbound

This paper cites IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data IP-Adapter: Text Compatible Image Prompt Adapter for Text-to-Image Diffusion Models

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.257774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.257774Z digest=sha256:70aeffb2c0f1c283dbc9f55b66a261d1fb7f69318a930a4095468cc83bd1479a

Observation 59e40426-d132-4a35-8c2f-2cf84c62b365 · outbound

This paper cites Diversify, Don't Fine-Tune: Scaling Up Visual Recognition Training with Synthetic Images.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Diversify, Don't Fine-Tune: Scaling Up Visual Recognition Training with Synthetic Images

Reference 59

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.262444Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.262444Z digest=sha256:4049b0c91af3f056e237a4176aa8ead43a2a86da68822c600ae6e165e13366e6

Observation 89808b48-610d-4d20-a65e-0d88cc99e251 · outbound

This paper cites DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.266292Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.266292Z digest=sha256:e97f7f8f116d5a8d24f61984e89d450dbac551365c234b5c7888e2dead2020f2

Observation dc83eb4b-6f62-49ad-92aa-6ca74b4e2465 · outbound

This paper cites Adding conditional control to text-to-image diffusion models.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Adding conditional control to text-to-image diffusion models

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.193544Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.270317Z digest=sha256:856a35b0359fbc1ebe89d81103cb08d71357a072b8194196d878b1b14f7e3dfb

Observation 4658af5c-3026-4440-a35e-75c328441b78 · outbound

This paper cites The unreasonable effectiveness of deep features as a perceptual metric.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data The unreasonable effectiveness of deep features as a perceptual metric

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.274017Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.274017Z digest=sha256:294cf9a1b57502941a458472c411821cc4a5fadf465a83491554e7024a12421a

Observation 8e125235-91c6-4bae-bbe9-f789c26887b0 · outbound

This paper cites Hive: Harnessing human feedback for instructional visual editing.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Hive: Harnessing human feedback for instructional visual editing

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.278528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.278528Z digest=sha256:5fba8869c3f7f6257ef353ba08e21b66de8b90e15717635c3e68cc9f84cf59b4

Observation 0e76a086-465d-4813-b6e9-1bf40ae4697b · outbound

This paper cites Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Programming Every Example: Lifting Pre-training Data Quality Like Experts at Scale

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-15T21:10:42.282846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T21:10:42.282846Z digest=sha256:9e80321e8298878653360a8b8b934d02734bd4d9a5a4778e591cf467e58ddeb7

Observation b5c6b226-eef3-4d6d-abe7-a281ee9cc772 · outbound

This paper cites an unresolved cited work.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Unresolved cited work

Reference 65

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:10:43.161797Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.287568Z digest=sha256:71d8585637c0368be5df51d43a0fac54ba03db2fa00c19e86b44173128e5c441

Observation 1ef0069c-21c4-423a-883c-f185bed5cc88 · outbound

This paper cites an unresolved cited work.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Unresolved cited work

Reference 66

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:10:43.148222Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.292212Z digest=sha256:7c2b6fe7127931b7898de4b09024e30710535fe73b24b7d8d5aa73dd9ff1457e

Observation bdd5878b-85b7-4a00-8fdf-5372e4e22ae8 · outbound

This paper cites Positive Example: • Object Class: [CLASS] • Question: Provide five different [Attribute] for the object class, each accompanied by a concise visual description.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Positive Example: • Object Class: [CLASS] • Question: Provide five different [Attribute] for the object class, each accompanied by a concise visual description

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.134554Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.296855Z digest=sha256:d0448cfbeb9de23b3289fae3c58975e796d76b5a7c35a3dff66960b82fe56aa9

Observation 851d2a55-52d8-4600-b808-e8882e32a528 · outbound

This paper cites an unresolved cited work.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Unresolved cited work

Reference 68

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:10:43.120353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.301361Z digest=sha256:eaf8e66f7ab0349c5518ace52236cf270fd6d853529ec31c0ec5417b18e55544

Observation a0966f2b-fda0-40d1-b721-15674bef43ea · outbound

This paper cites inside a sun.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data inside a sun

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.107130Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.305676Z digest=sha256:7999e7b0d5d18375d4096c93fd552f2695d6c7980d111f3d9f439ba414024708

Observation 74065090-b9a2-4aa4-babd-12f577578d95 · outbound

This paper cites an unresolved cited work.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Unresolved cited work

Reference 70

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:10:43.093621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.310010Z digest=sha256:5f1fe0885b0bd15edeb6b9cf077fa3d02691baa9d424158d0bfd35ad7b955eec

Observation 0a1c0120-577c-4e7a-a7b5-7f795ce933ef · outbound

This paper cites an unresolved cited work.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Unresolved cited work

Reference 71

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:10:43.078430Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.314215Z digest=sha256:73dfa18d9fbcf2b4b6909da693468a7be0fcc749fc6378cdf095402ad18329f8

Observation 64c69d0c-f4bc-4db4-a2b2-896a6b779254 · outbound

This paper cites In Context Learning Example.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data In Context Learning Example

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.064938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.318444Z digest=sha256:318debeaa6e64b80f18205538d88ba39b0494368cfa846122627f5eeb0c9598f

Observation 7e018400-9378-4705-88ba-8366b870f8b8 · outbound

This paper cites an unresolved cited work.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Unresolved cited work

Reference 73

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:10:43.049947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.322714Z digest=sha256:86fe3937b101a573480e9639b8b2373b092ce88cbbe097b8f50f6200e43bb752

Observation cbf1ad41-3b30-421d-8b05-eabffbd766ac · outbound

This paper cites an unresolved cited work.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Unresolved cited work

Reference 74

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:10:43.034393Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.326526Z digest=sha256:72e987f51bac24fadd39e0e9e690de25954621f010ddf80acd3c7a3ded195422

Observation 1e38719b-b35e-4428-9a5e-d664c5cbf76c · outbound

This paper cites an unresolved cited work.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Unresolved cited work

Reference 75

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:10:43.018949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.330502Z digest=sha256:c4a774ef82232fd5ca8569f87ddbac2a983d3c723b3316b50f2972fb57a299ff

Observation c1496ef7-0cfa-4b84-bf01-c341cd8d0b22 · outbound

This paper cites unsuitable for pets.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data unsuitable for pets

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:43.004117Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.334208Z digest=sha256:01269d821793b731c7efc55ef0a14761485d03a13cf5cb83d7b7510ec02dc220

Observation 2515924a-355d-4f26-8fab-356188f3852e · outbound

This paper cites an unresolved cited work.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data Unresolved cited work

Reference 77

Resolution
unresolved
raw_fallback, observed 2026-08-15T21:10:42.989525Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.337851Z digest=sha256:69e473148991f6e064ae1eafb0905c1d00ac5015ff74b342b9559e6fd993cac6

Observation 15dd1473-49f4-439b-9c73-3f049ab467a5 · outbound

This paper cites edit instruction.

Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data edit instruction

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T21:10:42.974693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-15T21:10:42.342685Z digest=sha256:67321ea2bee2e888de1d6bd0a21381282cbe09d785dd971d6400c38d67ecd25a

Pith citing papers

Observation ac09a640-d1a6-4599-81a5-c2ae18a35c34 · inbound

On the Difficulty of Learning a Meta-network for Training Data Selection cites this paper.

On the Difficulty of Learning a Meta-network for Training Data Selection Does Feasibility Matter? Understanding the Impact of Feasibility on Synthetic Training Data

Reference 83

Resolution
verified exact
arxiv_id, observed 2026-06-28T19:22:34.798635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-06-28T19:14:24.554237Z digest=sha256:1b5e4c1d2b0ecbb289fbbbcef67fa255c2c12151318c35805a026a8ba1d1bf38