Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-12T14:44:59.796239Z
Paper Citation Record · LEDGER
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation
As of 12 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2411.14957.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
58 of 58 outbound references displayed
- verified exact0
- verified fuzzy44
- unresolved14
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 5d31a3c0-be01-4d2d-ae62-0c45da68db94 · outbound
This paper cites Form2Seq : A framework for higher-order form structure extraction.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Form2Seq : A framework for higher-order form structure extraction
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.596276Z
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.
Observation f0688c60-6869-4895-af93-ec34e1189337 · outbound
This paper cites Data protection, 2024.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Data protection, 2024
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.582008Z
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.
Observation 969f4d54-cb0a-46df-8c34-ffd5c20d56a4 · outbound
This paper cites The claude 3 model family: Opus, sonnet, haiku,.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation The claude 3 model family: Opus, sonnet, haiku,
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:44:59.563767Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cd6701fd-e7cb-400e-b1f1-3e200082221d · outbound
This paper cites Introducing the next generation of claude, 2024.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Introducing the next generation of claude, 2024
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.558517Z
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.
Observation 14423e75-5e59-4599-9dc2-78bf1cd1bd25 · outbound
This paper cites Prompt engineering, 2024.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Prompt engineering, 2024
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.542804Z
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.
Observation dc1a055f-f90e-43d4-b0fe-b886d927305d · outbound
This paper cites Manmatha.
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.529622Z
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.
Observation 19edde72-2833-48bc-bfa9-5d09f6b0085c · outbound
This paper cites Wukong-reader: Multi-modal pre-training for fine-grained visual document understanding, 2022.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Wukong-reader: Multi-modal pre-training for fine-grained visual document understanding, 2022
Reference 7
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.516053Z
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.
Observation 739c429b-932b-441b-b12a-e09549a628d3 · outbound
This paper cites Unilmv2: Pseudo-masked lan- guage models for unified language model pre-training, 2020.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Unilmv2: Pseudo-masked lan- guage models for unified language model pre-training, 2020
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.501847Z
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.
Observation 634fcd91-c06b-4a0a-923b-6fb233f6128b · outbound
This paper cites an unresolved cited work.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Unresolved cited work
Reference 9
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T14:45:00.487979Z
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.
Observation 6582a774-a4ab-40ab-9bf4-a2eab4a79659 · outbound
This paper cites an unresolved cited work.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Unresolved cited work
Reference 10
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T14:45:00.474371Z
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.
Observation 642fa838-8a97-46f3-ba5a-43c602a88a96 · outbound
This paper cites Gonzalez, Ion Stoica, and Eric P.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Gonzalez, Ion Stoica, and Eric P
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.460416Z
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.
Observation 34a96809-63f9-4272-8787-1b3607e3c0a1 · outbound
This paper cites an unresolved cited work.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Unresolved cited work
Reference 12
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T14:45:00.446143Z
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.
Observation 353eca23-7166-4f60-9244-4a3a2b251558 · outbound
This paper cites Binarized neural networks: Training deep neural networks with weights and activations constrained to +1 or -1, 2016.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Binarized neural networks: Training deep neural networks with weights and activations constrained to +1 or -1, 2016
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.432335Z
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.
Observation 3908b9f7-0209-4bc1-af60-9820931bfc20 · outbound
This paper cites Denk and Christian Reisswig.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Denk and Christian Reisswig
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.416613Z
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.
Observation d4a799f4-2594-45de-a892-726f7cde9c9d · outbound
This paper cites Bert: Pre-training of deep bidirectional trans- formers for language understanding, 2019.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Bert: Pre-training of deep bidirectional trans- formers for language understanding, 2019
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.401341Z
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.
Observation ebbeb66c-b529-474f-ac5f-2b2989aa4484 · outbound
This paper cites Docparser: End-to-end ocr-free information extraction from visually rich documents, 2023.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Docparser: End-to-end ocr-free information extraction from visually rich documents, 2023
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.386865Z
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.
Observation c7447e3e-fd5f-4e0b-9a64-17da21d3eab6 · outbound
This paper cites Haralick, and I.T.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Haralick, and I.T
Reference 17
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.372423Z
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.
Observation f49174e5-b8ad-4d43-887d-36c84830980a · outbound
This paper cites A table detection method for pdf documents based on convo- lutional neural networks.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation A table detection method for pdf documents based on convo- lutional neural networks
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.359563Z
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.
Observation 37ddfbb0-d5f9-4b12-9f22-af3d742370b3 · outbound
This paper cites Ocr with tesseract, amazon textract, and google document ai: a benchmarking experiment.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Ocr with tesseract, amazon textract, and google document ai: a benchmarking experiment
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.346253Z
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.
Observation 8376e333-6957-4c9c-8217-783bfe938823 · outbound
This paper cites Distilling the knowledge in a neural network, 2015.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Distilling the knowledge in a neural network, 2015
Reference 20
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:44:59.636887Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 51fb9bee-48c3-47b5-9a1e-3f2105e24667 · outbound
This paper cites Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen- Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen- Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:44:59.641189Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 07d7e8c0-94e4-4dec-b1bb-addf2d59dc24 · outbound
This paper cites Cre- ating something from nothing: Unsupervised knowledge dis- tillation for cross-modal hashing, 2020.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Cre- ating something from nothing: Unsupervised knowledge dis- tillation for cross-modal hashing, 2020
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.313050Z
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.
Observation e6126d0f-16fe-4100-a7c8-eba01a4114f5 · outbound
This paper cites Layoutlmv3: Pre-training for document ai with unified text and image masking, 2022.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Layoutlmv3: Pre-training for document ai with unified text and image masking, 2022
Reference 23
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.297324Z
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.
Observation 9e5e1688-6369-4d38-827e-1808a561633a · outbound
This paper cites Spatial dependency parsing for semi-structured document information extraction, 2021.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Spatial dependency parsing for semi-structured document information extraction, 2021
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.283659Z
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.
Observation a6dd6fd0-22b6-40b3-af57-48ce230cae56 · outbound
This paper cites Funsd: A dataset for form understanding in noisy scanned documents, 2019.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Funsd: A dataset for form understanding in noisy scanned documents, 2019
Reference 25
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.269920Z
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.
Observation 31e5e396-2550-4bf4-8f17-c8b0e008d0b1 · outbound
This paper cites an unresolved cited work.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Unresolved cited work
Reference 26
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T14:45:00.256806Z
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.
Observation ef68e150-f49e-4636-94eb-0b35be8bd1f1 · outbound
This paper cites Chargrid: Towards understanding 2d documents, 2018.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Chargrid: Towards understanding 2d documents, 2018
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.244009Z
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.
Observation 3e6c28de-0d98-42ec-9100-300437f78235 · outbound
This paper cites A diagram is worth a dozen images, 2016.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation A diagram is worth a dozen images, 2016
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:44:59.671051Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c5ba4a83-72d6-45d3-80a4-2c382c0e5db4 · outbound
This paper cites Formnetv2: Multimodal graph contrastive learning for form document information extraction, 2023.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Formnetv2: Multimodal graph contrastive learning for form document information extraction, 2023
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.222100Z
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.
Observation d1c84f92-2054-45cb-8d9a-5ee887e2bb1c · outbound
This paper cites Lewis, G.
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.208223Z
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.
Observation f64a1341-8213-4e38-85e8-61bbd1ffba4c · outbound
This paper cites Improved baselines with visual instruction tuning, 2023.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Improved baselines with visual instruction tuning, 2023
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:44:59.684430Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 22e20805-2216-4cfa-b015-4e3d8024073b · outbound
This paper cites Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Liu, Kevin Lin, John Hewitt, Ashwin Paranjape, Michele Bevilacqua, Fabio Petroni, and Percy Liang
Reference 32
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.185835Z
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.
Observation 0672716b-4602-4034-a689-3fdbda6d1896 · outbound
This paper cites Roberta: A robustly optimized bert pretraining approach, 2019.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Roberta: A robustly optimized bert pretraining approach, 2019
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:44:59.692672Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 188b7b9a-4903-42e0-9b30-a08ee14a4d1d · outbound
This paper cites Repre- sentation learning for information extraction from form-like documents.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Repre- sentation learning for information extraction from form-like documents
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.162465Z
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.
Observation fa6efbeb-5b2b-4d73-9d81-bc591faeebec · outbound
This paper cites Marinai, M.
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.148483Z
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.
Observation 8a536668-a449-43cd-ab84-3a637ddc8027 · outbound
This paper cites Chartqa: A benchmark for question an- swering about charts with visual and logical reasoning, 2022.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Chartqa: A benchmark for question an- swering about charts with visual and logical reasoning, 2022
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.135258Z
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.
Observation 6c7d6891-2c9b-4471-81c4-78a0d7ae974f · outbound
This paper cites an unresolved cited work.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Unresolved cited work
Reference 37
- Resolution
- unresolved
- raw_fallback, observed 2026-08-12T14:45:00.121435Z
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.
Observation 7c13a8b8-f3e5-49d0-9fa4-bbc19ecef613 · outbound
This paper cites Open language learning for information extraction.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Open language learning for information extraction
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.106520Z
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.
Observation a4ccb2ad-444f-43ed-ac53-8cff4fee6cf7 · outbound
This paper cites doctr: Document text recognition.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation doctr: Document text recognition
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.091979Z
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.
Observation ffeb3918-4313-4d87-9519-cb4e1d539e11 · outbound
This paper cites O’Gorman.
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.078048Z
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.
Observation 6a2380ef-13aa-4fe6-9b7f-e95b979ad99c · outbound
This paper cites Gpt-4 is openai’s most advanced system, 2023.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Gpt-4 is openai’s most advanced system, 2023
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.064584Z
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.
Observation ef3566d2-4264-4d9b-949a-c0b034410c3f · outbound
This paper cites Revisiting the tree edit distance and its backtracing: A tutorial, 2022.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Revisiting the tree edit distance and its backtracing: A tutorial, 2022
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.048737Z
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.
Observation 78894fef-321f-4922-8358-3973b32ebecd · outbound
This paper cites Cloud- scan - a configuration-free invoice analysis system using re- current neural networks, 2017.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Cloud- scan - a configuration-free invoice analysis system using re- current neural networks, 2017
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.034542Z
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.
Observation ecaa873f-8758-4d08-8590-3e534a3ea5a3 · outbound
This paper cites Cord: A con- solidated receipt dataset for post-ocr parsing.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Cord: A con- solidated receipt dataset for post-ocr parsing
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.018187Z
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.
Observation acafe7c5-00db-46ed-ba49-ffc5faa2fe72 · outbound
This paper cites Ernie-layout: Layout knowledge en- hanced pre-training for visually-rich document understand- ing, 2022.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Ernie-layout: Layout knowledge en- hanced pre-training for visually-rich document understand- ing, 2022
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:45:00.003908Z
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.
Observation 08d06f40-fa1d-428e-9d11-6cf695eb09c5 · outbound
This paper cites Lmdx: Language model-based document information ex- traction and localization, 2024.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Lmdx: Language model-based document information ex- traction and localization, 2024
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:44:59.989477Z
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.
Observation 967348e0-bd89-4926-8d55-37c2f4bafb9a · outbound
This paper cites Learning transferable visual models from natural language supervision, 2021.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Learning transferable visual models from natural language supervision, 2021
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:44:59.751400Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d815c8f5-8c8d-4d18-a8cc-d6d196ab1f02 · outbound
This paper cites Xnor-net: Imagenet classification using bi- nary convolutional neural networks, 2016.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Xnor-net: Imagenet classification using bi- nary convolutional neural networks, 2016
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:44:59.967070Z
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.
Observation f6e6e4d8-2807-409c-88e3-2553b7b1ca52 · outbound
This paper cites Simon, J.-C.
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:44:59.951961Z
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.
Observation cad7e608-e92a-47be-8b1d-04a0dcf130bc · outbound
This paper cites Llama 2: Open foundation and fine- tuned chat models, 2023.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Llama 2: Open foundation and fine- tuned chat models, 2023
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:44:59.762683Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9d633094-348b-4e56-b5a8-19debecbef84 · outbound
This paper cites Layout and task aware instruction prompt for zero-shot document image question answering, 2023.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Layout and task aware instruction prompt for zero-shot document image question answering, 2023
Reference 51
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:44:59.929187Z
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.
Observation 1ade8e34-f35a-4089-b70a-91659233de26 · outbound
This paper cites Cogvlm: Visual expert for pretrained language models, 2024.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Cogvlm: Visual expert for pretrained language models, 2024
Reference 52
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:44:59.915013Z
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.
Observation a09d24d2-de2b-4e75-a13b-7c5560ec6727 · outbound
This paper cites Cnnpack: packing convolutional neural networks in the frequency domain.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Cnnpack: packing convolutional neural networks in the frequency domain
Reference 53
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:44:59.900947Z
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.
Observation c031da7e-21ba-419f-8970-8f457e282546 · outbound
This paper cites Queryform: A simple zero-shot form entity query framework, 2023.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Queryform: A simple zero-shot form entity query framework, 2023
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:44:59.886091Z
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.
Observation 18dcfba2-5e07-48f2-8c6c-d6d3f29b3342 · outbound
This paper cites Chain-of-thought prompting elicits reasoning in large language models, 2023.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Chain-of-thought prompting elicits reasoning in large language models, 2023
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T14:44:59.783046Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e9f5aa14-7f6a-4827-9071-c78e5c1b7c30 · outbound
This paper cites Layoutlm: Pre-training of text and layout for document image understanding.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Layoutlm: Pre-training of text and layout for document image understanding
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:44:59.862305Z
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.
Observation 1360fab2-f0dd-4841-a859-b2b3a464840b · outbound
This paper cites Layoutlmv2: Multi-modal pre-training for visually-rich document under- standing, 2022.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Layoutlmv2: Multi-modal pre-training for visually-rich document under- standing, 2022
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:44:59.848026Z
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.
Observation f458db77-eaea-46c7-af01-01c4e2a876b3 · outbound
This paper cites Data-free knowledge amalgamation via group-stack dual-gan, 2020.
Information Extraction from Heterogeneous Documents without Ground Truth Labels using Synthetic Label Generation and Knowledge Distillation Data-free knowledge amalgamation via group-stack dual-gan, 2020
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-12T14:44:59.833301Z
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.
Pith citing papers
No inbound Pith citation observations are available.