Paper Citation Record · LEDGER

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings

As of 20 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:1908.03477.

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

pith.paper-citation-record.v1
1908.03477 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T14:15:57.272572Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

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

measured 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

42 of 42 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 09347ffc-8b47-4a24-89f0-7dcf42b6192e · outbound

This paper cites an unresolved cited work.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Unresolved cited work

Reference 1

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Observation 70e071cc-fe06-4f05-8010-266a3834f327 · outbound

This paper cites Re-ID done right: towards good practices for person re-identification.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Re-ID done right: towards good practices for person re-identification

Reference 2

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This paper cites NetVLAD: CNN architecture for weakly supervised place recognition.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings NetVLAD: CNN architecture for weakly supervised place recognition

Reference 3

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This paper cites An empirical study and analysis of generalized zero- shot learning for object recognition in the wild.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings An empirical study and analysis of generalized zero- shot learning for object recognition in the wild

Reference 4

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This paper cites Beyond triplet loss: a deep quadruplet network for person re-identiﬁcation.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Beyond triplet loss: a deep quadruplet network for person re-identiﬁcation

Reference 5

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Observation 0b862c3b-5658-46a5-81f0-01806def26c8 · outbound

This paper cites Scaling egocentric vision: The epic-kitchens dataset.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Scaling egocentric vision: The epic-kitchens dataset

Reference 6

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Observation c4095747-5b8f-4326-9d83-56a92a40de35 · outbound

This paper cites Predict- ing visual features from text for image and video caption re- trieval.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Predict- ing visual features from text for image and video caption re- trieval

Reference 7

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Observation 86de2abf-eb5e-4198-8626-0b4c4a2c1b66 · outbound

This paper cites Dual Encoding for Zero-Example Video Retrieval.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Dual Encoding for Zero-Example Video Retrieval

Reference 8

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This paper cites Improving image-sentence embeddings using large weakly annotated photo collections.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Improving image-sentence embeddings using large weakly annotated photo collections

Reference 9

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Observation 24c39c6a-2d93-41d4-ab83-5847f64df17e · outbound

This paper cites Deep image retrieval: Learning global representations for image search.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Deep image retrieval: Learning global representations for image search

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:58.065837Z

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Observation 437a4b4c-65a0-4334-91a8-3b7703c905ea · outbound

This paper cites Beyond instance-level im- age retrieval: Leveraging captions to learn a global visual representation for semantic retrieval.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Beyond instance-level im- age retrieval: Leveraging captions to learn a global visual representation for semantic retrieval

Reference 11

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Observation 8356357a-0ab1-4ed0-a846-89dbbf0fb2a7 · outbound

This paper cites Something Something.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Something Something

Reference 12

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Observation 48d26ae9-a8df-4a56-a7a8-807789c60ed5 · outbound

This paper cites Ava: A video dataset of spatio-temporally localized atomic visual actions.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Ava: A video dataset of spatio-temporally localized atomic visual actions

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:58.009196Z

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Observation ce2de66e-540f-4bbb-87b6-0d4b12c9a203 · outbound

This paper cites Youtube2text: Recognizing and describing arbitrary activities using semantic hierarchies and zero-shot recognition.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Youtube2text: Recognizing and describing arbitrary activities using semantic hierarchies and zero-shot recognition

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:57.985015Z

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Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Unresolved cited work

Reference 15

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Observation 47c7d464-2874-4da8-b38a-bda26323ec06 · outbound

This paper cites In Defense of the Triplet Loss for Person Re-Identification.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings In Defense of the Triplet Loss for Person Re-Identification

Reference 16

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Observation cce0550f-0af1-45af-bb9b-8b78364b9faa · outbound

This paper cites Deep metric learning using triplet network.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Deep metric learning using triplet network

Reference 17

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Observation 46f38826-3731-4783-a1ae-56bcc6ed91d4 · outbound

This paper cites Unifying visual-semantic embeddings with multimodal neu- ral language models.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Unifying visual-semantic embeddings with multimodal neu- ral language models

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:57.927132Z

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This paper cites Learning two-branch neural networks for image-text match- ing tasks.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Learning two-branch neural networks for image-text match- ing tasks

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:57.908471Z

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This paper cites On the effectiveness of task granularity for transfer learning.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings On the effectiveness of task granularity for transfer learning

Reference 20

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Observation 611c895f-318a-438d-82f6-b8eef42c219e · outbound

This paper cites Learnable pooling with Context Gating for video classification.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Learnable pooling with Context Gating for video classification

Reference 21

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Observation ad39cbdd-ded8-4ef3-a79b-62d059664eaf · outbound

This paper cites Learning a Text-Video Embedding from Incomplete and Heterogeneous Data.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Learning a Text-Video Embedding from Incomplete and Heterogeneous Data

Reference 22

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This paper cites HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings HowTo100M: Learning a Text-Video Embedding by Watching Hundred Million Narrated Video Clips

Reference 23

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This paper cites Learning joint embedding with multimodal cues for cross-modal video-text retrieval.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Learning joint embedding with multimodal cues for cross-modal video-text retrieval

Reference 24

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Observation bcaa3663-4b73-45ec-8b97-3e3a89210ea3 · outbound

This paper cites Learning joint representations of videos and sentences with web image search.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Learning joint representations of videos and sentences with web image search

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:57.859538Z

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Observation 23fb74cc-65c8-4b6a-88d3-d2106a05bdee · outbound

This paper cites Enhancing video summarization via vision-language embed- ding.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Enhancing video summarization via vision-language embed- ding

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:57.839909Z

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This paper cites CNN image retrieval learns from BoW: Unsupervised ﬁne-tuning with hard examples.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings CNN image retrieval learns from BoW: Unsupervised ﬁne-tuning with hard examples

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:57.818744Z

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Observation 2aa1b1a3-a3bd-4aa1-b917-fb7cae7cb855 · outbound

This paper cites Recognizing ﬁne-grained and composite ac- tivities using hand-centric features and script data.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Recognizing ﬁne-grained and composite ac- tivities using hand-centric features and script data

Reference 28

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This paper cites Facenet: A uniﬁed embedding for face recognition and clus- tering.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Facenet: A uniﬁed embedding for face recognition and clus- tering

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:57.773385Z

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Observation 9967b099-b0d6-4ea4-8209-3ee0cbe3c6e2 · outbound

This paper cites Higher-order Network for Action Recognition.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Higher-order Network for Action Recognition

Reference 30

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Observation a2eab173-ae32-4ee7-b040-75ac41588ab3 · outbound

This paper cites Sigurdsson, G ¨ul Varol, Xiaolong Wang, Ali Farhadi, Ivan Laptev, and Abhinav Gupta.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Sigurdsson, G ¨ul Varol, Xiaolong Wang, Ali Farhadi, Ivan Laptev, and Abhinav Gupta

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:57.745079Z

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Observation 888645c1-88be-4105-b163-bea0dd21e166 · outbound

This paper cites Improved deep metric learning with multi- class n-pair loss objective.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Improved deep metric learning with multi- class n-pair loss objective

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:57.726059Z

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Observation ffd6b78b-0223-4de0-8d70-c4c8d8e10659 · outbound

This paper cites Cross modal embeddings for video and audio retrieval.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Cross modal embeddings for video and audio retrieval

Reference 33

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Observation 8555b7f9-6dfc-4b21-8d2a-0122fb6050c0 · outbound

This paper cites Learning Language-Visual Embedding for Movie Understanding with Natural-Language.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Learning Language-Visual Embedding for Movie Understanding with Natural-Language

Reference 34

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This paper cites Learn- ing ﬁne-grained image similarity with deep ranking.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Learn- ing ﬁne-grained image similarity with deep ranking

Reference 35

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Observation 939fc6d5-a252-4f04-9e2f-fbf3a1fbdf57 · outbound

This paper cites Learning deep structure-preserving image-text embeddings.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Learning deep structure-preserving image-text embeddings

Reference 36

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Observation ebca65a9-0e2d-4061-8e1c-0fc8167dc29a · outbound

This paper cites Temporal segment networks: Towards good practices for deep action recogni- tion.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Temporal segment networks: Towards good practices for deep action recogni- tion

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:57.634381Z

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Observation 1bb59219-bbbf-433e-aa3d-aacdf9ac1e7b · outbound

This paper cites Learning visual actions using multiple verb-only labels.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Learning visual actions using multiple verb-only labels

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:57.611464Z

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Observation e00a62a1-00b5-42b8-8970-f9002b97fd6a · outbound

This paper cites Msr-vtt: A large video description dataset for bridging video and language.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Msr-vtt: A large video description dataset for bridging video and language

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:57.591146Z

Source-reported events for the cited work

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Observation 51108899-bda2-4313-823d-5bb99511e90c · outbound

This paper cites Jointly modeling deep video and compositional text to bridge vision and language in a uniﬁed framework.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Jointly modeling deep video and compositional text to bridge vision and language in a uniﬁed framework

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:57.556663Z

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Observation ecc408dc-a83e-4a8f-8726-c74941c7f6b9 · outbound

This paper cites A joint se- quence fusion model for video question answering and re- trieval.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings A joint se- quence fusion model for video question answering and re- trieval

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-14T14:15:57.533791Z

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This paper cites Zero-shot learning via semantic similarity embedding.

Fine-Grained Action Retrieval Through Multiple Parts-of-Speech Embeddings Zero-shot learning via semantic similarity embedding

Reference 42

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Source-reported events for the cited work

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

Pith citing papers

No inbound Pith citation observations are available.