Paper Citation Record · LEDGER

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation

As of 14 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 1 inbound Pith citation observation for arXiv:2411.16810.

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

pith.paper-citation-record.v1
2411.16810 v1

Coverage vector

measured 53 of 53 reference resolution

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measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:47:50.708047Z

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Source: pith, observed 2026-08-07T04:47:50.945595Z

Reference resolution

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External citation measurements

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Outbound references

Observation e88d7794-2539-49dc-a4f4-f604ee72c26b · outbound

This paper cites Development of arabic sign language dictionary using 3d avatar technologies.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Development of arabic sign language dictionary using 3d avatar technologies

Reference 1

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Observation 4a1ff52a-33bc-4f04-81c4-7fc150084765 · outbound

This paper cites Neural sign language trans- lation.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Neural sign language trans- lation

Reference 2

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Observation 0baa0e83-2937-4330-9c12-f2722ccc31bf · outbound

This paper cites Multi-channel transformers for multi- articulatory sign language translation.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Multi-channel transformers for multi- articulatory sign language translation

Reference 3

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This paper cites Realtime multi-person 2d pose estimation using part affinity fields.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Realtime multi-person 2d pose estimation using part affinity fields

Reference 4

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Observation 796ebc2f-47bb-45bc-84dc-4079fa3fcc02 · outbound

This paper cites The devisign large vocabulary of chinese sign language database and base- line evaluations.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation The devisign large vocabulary of chinese sign language database and base- line evaluations

Reference 5

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Observation 49845ea4-6dce-4a96-9f69-5b3121d424da · outbound

This paper cites Querying a sign lan- guage dictionary with videos using dense vector search.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Querying a sign lan- guage dictionary with videos using dense vector search

Reference 6

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Observation 52c208bd-de09-4db6-868a-cac6547f38ec · outbound

This paper cites Benchmark databases for video- based automatic sign language recognition.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Benchmark databases for video- based automatic sign language recognition

Reference 7

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Observation 18314c64-7c99-41c9-8b4c-0e9be7b87e15 · outbound

This paper cites Cross-modal neural sign language translation.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Cross-modal neural sign language translation

Reference 8

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Observation 3a266164-0a8c-4779-8946-a8221085c9d3 · outbound

This paper cites Llms are good sign language translators.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Llms are good sign language translators

Reference 9

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Observation 33b14bee-68ec-4922-b546-7064fed235c7 · outbound

This paper cites Online early-late fusion based on adaptive hmm for sign language recognition.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Online early-late fusion based on adaptive hmm for sign language recognition

Reference 10

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Observation f466600d-5419-4cd7-b419-5e59dddc1421 · outbound

This paper cites Hierarchical lstm for sign language translation.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Hierarchical lstm for sign language translation

Reference 11

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Observation e1eab931-3fe0-46ec-8d30-9aabc918a81c · outbound

This paper cites Connectionist temporal modeling of video and language: A joint model for translation and sign labeling.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Connectionist temporal modeling of video and language: A joint model for translation and sign labeling

Reference 12

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Observation 15c2d763-0df5-440e-97e3-48769d8242ca · outbound

This paper cites Sign language recognition.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Sign language recognition

Reference 13

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Observation 29fbaa7e-4431-4fe5-a5d4-6921b03da85f · outbound

This paper cites Denoising diffusion probabilistic models.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Denoising diffusion probabilistic models

Reference 14

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Observation 400a10fd-6143-4e71-ac3f-fa142c33f6e5 · outbound

This paper cites Collaborative multilingual continuous sign language recog- nition: A unified framework.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Collaborative multilingual continuous sign language recog- nition: A unified framework

Reference 15

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Observation 29e3b402-3686-4c78-bac8-0a20f7ad9645 · outbound

This paper cites Signbert+: Hand-model-aware self-supervised pre- training for sign language understanding.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Signbert+: Hand-model-aware self-supervised pre- training for sign language understanding

Reference 16

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Observation 98641369-1907-43dc-88fd-f1c9227e90f9 · outbound

This paper cites Attention-based 3d-cnns for large-vocabulary sign language recognition.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Attention-based 3d-cnns for large-vocabulary sign language recognition

Reference 17

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Observation 8c5786fc-cbd4-4055-8cf7-6782e657d1d2 · outbound

This paper cites Video-based sign language recognition without temporal segmentation.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Video-based sign language recognition without temporal segmentation

Reference 18

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Observation 436e4b37-4342-4561-820b-a5f8588ab563 · outbound

This paper cites To- wards fast and high-quality sign language production.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation To- wards fast and high-quality sign language production

Reference 19

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Observation bf25dc9a-2a1f-4a6b-830a-6fa0dce8501e · outbound

This paper cites Developing a bilingual mobile dictionary for in- dian sign language and gathering users experience with sign- dict.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Developing a bilingual mobile dictionary for in- dian sign language and gathering users experience with sign- dict

Reference 20

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Observation 2648b4e6-c855-4860-b921-13aa291bfd07 · outbound

This paper cites Guided motion diffusion for controllable human motion synthesis.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Guided motion diffusion for controllable human motion synthesis

Reference 21

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Observation b0fedbe0-a361-4b67-9984-de6c112eb45c · outbound

This paper cites Quantitative Survey of the State of the Art in Sign Language Recognition.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Quantitative Survey of the State of the Art in Sign Language Recognition

Reference 22

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This paper cites Grid diffusion models for text-to-video generation.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Grid diffusion models for text-to-video generation

Reference 23

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Observation 9c9f6b2f-4c9e-48d6-a1a8-bb7da77116e7 · outbound

This paper cites Word-level deep sign language recognition from video: A new large-scale dataset and methods comparison.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Word-level deep sign language recognition from video: A new large-scale dataset and methods comparison

Reference 24

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Observation e2dce73e-669e-4324-92c8-c6b071a95e92 · outbound

This paper cites Tspnet: Hier- archical feature learning via temporal semantic pyramid for sign language translation.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Tspnet: Hier- archical feature learning via temporal semantic pyramid for sign language translation

Reference 25

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Observation 940e6f64-f4e4-421d-acea-272d0fe3ec3e · outbound

This paper cites Movideo: Motion-aware video generation with diffusion model.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Movideo: Motion-aware video generation with diffusion model

Reference 26

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Observation a3ccc947-559d-422d-a4f0-6f7fa2945382 · outbound

This paper cites Rouge: A package for automatic evaluation of summaries.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Rouge: A package for automatic evaluation of summaries

Reference 27

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Observation 29c0b01b-d97e-486b-992e-542d5145aaa5 · outbound

This paper cites Translating sign language videos to talking faces.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Translating sign language videos to talking faces

Reference 28

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Observation c7888d3a-b21e-46d6-a7df-7905622c23f0 · outbound

This paper cites An auto- mated technique for real-time production of lifelike anima- tions of american sign language.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation An auto- mated technique for real-time production of lifelike anima- tions of american sign language

Reference 29

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This paper cites Dds2m: Self-supervised denoising diffusion spatio- spectral model for hyperspectral image restoration.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Dds2m: Self-supervised denoising diffusion spatio- spectral model for hyperspectral image restoration

Reference 30

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This paper cites Dit-3d: Exploring plain diffusion transformers for 3d shape generation.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Dit-3d: Exploring plain diffusion transformers for 3d shape generation

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Observation d58d8f21-c95b-4fe9-b090-c3594213ef38 · outbound

This paper cites Conditional image-to-video genera- tion with latent flow diffusion models.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Conditional image-to-video genera- tion with latent flow diffusion models

Reference 32

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This paper cites Bleu: a method for automatic evaluation of machine translation.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Bleu: a method for automatic evaluation of machine translation

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

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation High-resolution image syn- thesis with latent diffusion models

Reference 34

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This paper cites Progressive transformers for end-to-end sign language pro- duction.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Progressive transformers for end-to-end sign language pro- duction

Reference 35

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This paper cites Mixed signals: Sign language production via a mixture of motion primitives.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Mixed signals: Sign language production via a mixture of motion primitives

Reference 36

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This paper cites A study of sign language coarticulation.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation A study of sign language coarticulation

Reference 37

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This paper cites Diffusion-based 3d human pose estimation with multi- hypothesis aggregation.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Diffusion-based 3d human pose estimation with multi- hypothesis aggregation

Reference 38

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This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Deep unsupervised learning using nonequilibrium thermodynamics

Reference 39

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This paper cites Text2sign: Towards sign language produc- tion using neural machine translation and generative adver- sarial networks.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Text2sign: Towards sign language produc- tion using neural machine translation and generative adver- sarial networks

Reference 40

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This paper cites Sign language generation system based on indian sign language grammar.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Sign language generation system based on indian sign language grammar

Reference 41

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This paper cites Graph-based multimodal sequential embedding for sign lan- guage translation.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Graph-based multimodal sequential embedding for sign lan- guage translation

Reference 42

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This paper cites Gloss-driven conditional diffusion mod- els for sign language production.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Gloss-driven conditional diffusion mod- els for sign language production

Reference 43

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Observation 6f8fe393-f954-46e8-94d8-5d1fc11cc048 · outbound

This paper cites Including facial expressions in contextual embed- dings for sign language generation.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Including facial expressions in contextual embed- dings for sign language generation

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:16:00.630754Z

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Observation 7a1df874-0f79-416c-b278-956858499b3a · outbound

This paper cites Diffir: Efficient diffusion model for image restoration.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Diffir: Efficient diffusion model for image restoration

Reference 45

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Observation 4c76bd22-6f32-43ac-8f6c-c7f89c44c08c · outbound

This paper cites Boxdiff: Text-to-image synthesis with training-free box-constrained diffusion.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Boxdiff: Text-to-image synthesis with training-free box-constrained diffusion

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:16:00.616279Z

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Observation 1c637259-d7eb-4d3e-a167-21774e5d13f1 · outbound

This paper cites G2p-ddm: Generating sign pose se- quence from gloss sequence with discrete diffusion model.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation G2p-ddm: Generating sign pose se- quence from gloss sequence with discrete diffusion model

Reference 47

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Observation 7d8e25a3-94ce-4c06-99e4-ebf8844a3c3a · outbound

This paper cites Fresco: Spatial-temporal correspondence for zero-shot video translation.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Fresco: Spatial-temporal correspondence for zero-shot video translation

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:16:00.601200Z

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Observation 36fa8874-5c25-45ed-817a-dbd6ee04f3f9 · outbound

This paper cites Diff-retinex: Rethinking low-light image enhancement with a generative diffusion model.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Diff-retinex: Rethinking low-light image enhancement with a generative diffusion model

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:16:00.593367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a36534ea-fede-482b-94ab-2193d7f52b66 · outbound

This paper cites Neural sign language synthe- sis: Words are our glosses.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Neural sign language synthe- sis: Words are our glosses

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:16:00.585052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 90946f12-82dd-4670-9a34-7812159cd4d9 · outbound

This paper cites Highly fluent sign language synthesis based on variable motion frame interpolation.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Highly fluent sign language synthesis based on variable motion frame interpolation

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:16:00.575942Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 47d57463-5c22-4ffe-9db3-ec6bbfd4dcb0 · outbound

This paper cites Chinese sign language recognition with adap- tive hmm.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Chinese sign language recognition with adap- tive hmm

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:16:00.568537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 516f7031-8935-4bd8-bbf6-acee87bebc42 · outbound

This paper cites Best: Bert pre-training for sign language recognition with coupling tokenization.

Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation Best: Bert pre-training for sign language recognition with coupling tokenization

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T13:16:00.560875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Pith citing papers

Observation 21147b6d-accc-4774-af74-a3f494049a1d · inbound

Using Sign Language Production as Data Augmentation to enhance Sign Language Translation cites this paper.

Using Sign Language Production as Data Augmentation to enhance Sign Language Translation Discrete to Continuous: Generating Smooth Transition Poses from Sign Language Observation

Reference 73

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:47:50.950748Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.