Paper Citation Record · LEDGER

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition

As of 24 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2608.10765.

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

pith.paper-citation-record.v1
2608.10765 v1

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T17:55:44.989050Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-23T06:30:58.430688+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

verified exact2
verified fuzzy19
unresolved6
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 048b5b65-2f97-4fda-86cc-24ecfc273405 · outbound

This paper cites Logic tensor networks.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Logic tensor networks

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.664312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 25acdc02-470a-4c14-a527-0d7c0cccdb10 · outbound

This paper cites Enhancing action recognition by leveraging the hierarchical structure of actions and textual context.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Enhancing action recognition by leveraging the hierarchical structure of actions and textual context

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.645971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c57a096f-e4b6-494f-b811-0b43be3e0627 · outbound

This paper cites Vision and Intention Boost Large Language Model in Long-Term Action Anticipation.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Vision and Intention Boost Large Language Model in Long-Term Action Anticipation

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-12T17:55:45.166090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2b3b312e-85c0-43d8-b0cc-d9653b358bc6 · outbound

This paper cites an unresolved cited work.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Unresolved cited work

Reference 4

Resolution: unresolved; raw_fallback, observed 2026-08-12T17:55:45.626315Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation c36b0bf5-7547-41e1-9e50-6973747c9d93 · outbound

This paper cites Procedu- ralgenerationofvideostotraindeepactionrecognitionnetworks,in: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Procedu- ralgenerationofvideostotraindeepactionrecognitionnetworks,in: 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pp

Reference 5

Resolution: verified exact; doi, observed 2026-08-12T17:55:45.049400Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 6f0c3470-1d75-479f-801a-44387c452f0c · outbound

This paper cites Datasheetsfordatasets.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Datasheetsfordatasets

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.584032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation cf5fbbb3-b9df-427e-8d2b-83336d24af42 · outbound

This paper cites What has been lost with synthetic evaluation? arXiv preprint arXiv:2505.22830.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition What has been lost with synthetic evaluation? arXiv preprint arXiv:2505.22830

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-12T17:55:44.868737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51936507-11f2-472a-b6c6-df8b5d1fc88a · outbound

This paper cites Heterogeneous graph transformer, in: Proceedings of the web conference 2020, pp.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Heterogeneous graph transformer, in: Proceedings of the web conference 2020, pp

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-12T17:55:44.876085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e80ff31-bf5b-4827-8bf8-40a71591b33e · outbound

This paper cites Cogs: A compositional generalization challenge based on semantic interpretation, in: Proceedings of the 2020conferenceonempiricalmethodsinnaturallanguageprocessing (emnlp), pp.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Cogs: A compositional generalization challenge based on semantic interpretation, in: Proceedings of the 2020conferenceonempiricalmethodsinnaturallanguageprocessing (emnlp), pp

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.551639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation a56091b8-8f78-4770-8b46-f46e46a26f22 · outbound

This paper cites C2c: Component-to-composition learning for zero- shot compositional action recognition, in: European Conference on Computer Vision, Springer.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition C2c: Component-to-composition learning for zero- shot compositional action recognition, in: European Conference on Computer Vision, Springer

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.531439Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d2c7cb33-181b-4aa7-897d-70d6aec7a0a5 · outbound

This paper cites an unresolved cited work.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Unresolved cited work

Reference 11

Resolution: unresolved; raw_fallback, observed 2026-08-12T17:55:45.504377Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 709fb47f-c0a9-46f6-924f-4a2889413159 · outbound

This paper cites Fineaction: A fine-grained video dataset for temporal action localization.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Fineaction: A fine-grained video dataset for temporal action localization

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.463109Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 20ee0575-d9ec-4243-a4b3-89b219a57bfe · outbound

This paper cites Intention-conditioned long- term human egocentric action anticipation, in: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Intention-conditioned long- term human egocentric action anticipation, in: Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, pp

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.444956Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation e51cb3ef-e9ac-44a3-baa4-67e2c85ae553 · outbound

This paper cites 1049– 1059.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition 1049– 1059

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.424323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d823cbe7-5bcb-4dfe-b22d-e71d72042c5a · outbound

This paper cites Gaze-guided graph neural network for action anticipation conditioned on intention, in: Proceedings of the 2024 Symposium on Eye Tracking Research and Applications, pp.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Gaze-guided graph neural network for action anticipation conditioned on intention, in: Proceedings of the 2024 Symposium on Eye Tracking Research and Applications, pp

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.403010Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 86836c17-c2f9-4691-bb32-d177b69aa011 · outbound

This paper cites Ad- versarial generative grammars for human activity prediction, in: Eu- ropean Conference on Computer Vision, Springer.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Ad- versarial generative grammars for human activity prediction, in: Eu- ropean Conference on Computer Vision, Springer

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.372536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 589744c7-f555-48ae-9bea-0d8d383cac2d · outbound

This paper cites Predicting human activities using stochastic grammar, in: Proceedings of the IEEE International Conference on Computer Vision, pp.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Predicting human activities using stochastic grammar, in: Proceedings of the IEEE International Conference on Computer Vision, pp

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.352585Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 24e0d288-b7c3-453d-8033-8203d466e0e3 · outbound

This paper cites Assembly101: A large-scale multi-view video datasetforunderstandingproceduralactivities,in:Proceedingsofthe IEEE/CVFConferenceonComputerVisionandPatternRecognition, pp.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Assembly101: A large-scale multi-view video datasetforunderstandingproceduralactivities,in:Proceedingsofthe IEEE/CVFConferenceonComputerVisionandPatternRecognition, pp

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.326530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation aeb1e38b-9377-4858-83e4-bbb21af5f596 · outbound

This paper cites Humanactivitiesasstochastickroneckergraphs, in:EuropeanConferenceonComputerVision,Springer.pp.130–143.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Humanactivitiesasstochastickroneckergraphs, in:EuropeanConferenceonComputerVision,Springer.pp.130–143

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.302847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 7854195f-5839-4528-80b5-124241425ecf · outbound

This paper cites A semantic loss function for deep learning with symbolic knowledge, in: International conference on machine learning, PMLR.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition A semantic loss function for deep learning with symbolic knowledge, in: International conference on machine learning, PMLR

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.282153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation d4dae1f0-b6aa-4369-908f-764dedbc7ca6 · outbound

This paper cites Logicmp: A neuro-symbolic approach for encodingfirst-orderlogicconstraints,in:InternationalConferenceon Learning Representations, pp.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Logicmp: A neuro-symbolic approach for encodingfirst-orderlogicconstraints,in:InternationalConferenceon Learning Representations, pp

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.262876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 3a5ecf8e-34a7-4dda-b740-b374b5bec8c5 · outbound

This paper cites Skelformer:Anadaptivehi- erarchical transformer-based approach on skeleton graphs for human action recognition in video sequences.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Skelformer:Anadaptivehi- erarchical transformer-based approach on skeleton graphs for human action recognition in video sequences

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.244190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 2cd5829d-5e96-423e-80ce-c49319f27a37 · outbound

This paper cites Zero-shot composi- tionalactionrecognitionwithneurallogicconstraints,in:Proceedings ofthe33rdACMInternationalConferenceonMultimedia,pp.3625– 3634.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Zero-shot composi- tionalactionrecognitionwithneurallogicconstraints,in:Proceedings ofthe33rdACMInternationalConferenceonMultimedia,pp.3625– 3634

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.224901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9dfa9b34-7964-48a3-9060-676e287eeac1 · outbound

This paper cites Action anticipation with goal consis- tency, in: 2023 IEEE International Conference on Image Processing (ICIP), IEEE.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Action anticipation with goal consis- tency, in: 2023 IEEE International Conference on Image Processing (ICIP), IEEE

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.203082Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 9794bc85-4f0e-409e-9511-839251dc4e49 · outbound

This paper cites an unresolved cited work.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Unresolved cited work

Reference 25

Resolution: unresolved; raw_fallback, observed 2026-08-12T17:55:45.185883Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation da105146-6cdc-42d1-bcb4-fc86b49cc3ec · outbound

This paper cites IEEE transactions on pattern analysis and machine intelligence 42, 2684–2701.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition IEEE transactions on pattern analysis and machine intelligence 42, 2684–2701

Reference 2019

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T17:55:45.480358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 731d8be4-42cb-44fb-b62d-ff9546ee4640 · outbound

This paper cites an unresolved cited work.

Compositional Benchmark Synthesis for Hierarchical Human Action Recognition Unresolved cited work

Reference 2020

Resolution: unresolved; raw_fallback, observed 2026-08-12T17:55:45.604725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Pith citing papers

No inbound Pith citation observations are available.