Pith. sign in

Paper Citation Record · LEDGER

Text embedding models can be great data engineers

As of 14 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 0 inbound Pith citation observations for arXiv:2505.14802.

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

pith.paper-citation-record.v1
2505.14802 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T15:32:28.149076Z

measured 52 of 52 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

52 of 52 outbound references displayed

  • verified exact2
  • verified fuzzy41
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation aacb4c7b-da0d-4ebc-ab65-9a302abd3f9f · outbound

This paper cites Information dropout: Learning optimal representations through noisy computation.

Text embedding models can be great data engineers Information dropout: Learning optimal representations through noisy computation

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:36.807405Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:23.449404Z digest=sha256:8bc0479a1ce37757b03d381b23bfc35a7b1f3f58abba7b2d3df57bc24034d2c6

Observation 0db71dfa-c6cf-43d4-8a04-d67870adee7f · outbound

This paper cites Deep Variational Information Bottleneck.

Text embedding models can be great data engineers Deep Variational Information Bottleneck

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-07T15:32:23.539258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:32:23.539258Z digest=sha256:e31cb1b2f49ca826b2f6ac0bf8a95ca0a7a1e6f63d67572cb71930eb655a5e7b

Observation 82a662dd-42d9-4442-842a-43f15faa5bec · outbound

This paper cites A comprehensive review on machine learning in healthcare industry: classification, restrictions, opportunities and challenges.Sensors, 23(9):4178, 2023.

Text embedding models can be great data engineers A comprehensive review on machine learning in healthcare industry: classification, restrictions, opportunities and challenges.Sensors, 23(9):4178, 2023

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:36.652667Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:23.710711Z digest=sha256:7477842f4ab40c1e5c0e2c7056b26c49cc1741976fe492cd5f8ca6e328ec9810

Observation d46e92b6-649d-4188-a975-e4d878738106 · outbound

This paper cites TSFEL: Time series feature extraction library.

Text embedding models can be great data engineers TSFEL: Time series feature extraction library

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:36.477008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:23.866001Z digest=sha256:29ef1cbfe74f48ae6993c424e97cd2c218cda43e8f9bd2dd30ad0fe6f96520aa

Observation 9c31e9f5-1b95-4219-8a0b-5e84d132c3f8 · outbound

This paper cites TSFEL: Time series feature extraction library.

Text embedding models can be great data engineers TSFEL: Time series feature extraction library

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:36.345622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:24.004731Z digest=sha256:660a81f4442bcdacd337d3211157a87d2336962a15199744778a1c35e7c597f8

Observation 7919b5eb-7e0b-4760-b50f-5b20f360e9d6 · outbound

This paper cites Financial time series forecasting-a deep learning approach.

Text embedding models can be great data engineers Financial time series forecasting-a deep learning approach

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:36.202852Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:24.189561Z digest=sha256:4877c7def75c4c43f5bfab17bee911479c63f4cd8df74352946c1ff80bf6b439

Observation 99796cb8-9e58-4af4-80c6-8cd38cc937e0 · outbound

This paper cites Information transmission with additional noise.

Text embedding models can be great data engineers Information transmission with additional noise

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:36.057154Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:24.317957Z digest=sha256:62f15a44473ce940de799f04d6fdd4a1586d5f60ec6fbc5085e455e81a58206c

Observation 53513bc2-c581-4707-99be-fc8529756920 · outbound

This paper cites Systematic literature review of preprocessing techniques for imbalanced data.

Text embedding models can be great data engineers Systematic literature review of preprocessing techniques for imbalanced data

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:35.888579Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:24.468785Z digest=sha256:1cdc8c53ffac6d764ea24525d41ef693676166727aca1891a766ac1ee88ee0c6

Observation a1b96534-a468-470e-a70c-f8e465856b3d · outbound

This paper cites Springenberg, Manuel Blum, and Frank Hutter.

Text embedding models can be great data engineers Springenberg, Manuel Blum, and Frank Hutter

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:35.693472Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:24.557269Z digest=sha256:447b51faa66f90523fe7412921534e2221a35ce1af0929b0908db053081bc092

Observation 0d5d15df-7f62-4bd4-b908-6200807d8b80 · outbound

This paper cites Transient classifiers for fink-benchmarks for lsst.

Text embedding models can be great data engineers Transient classifiers for fink-benchmarks for lsst

Reference 10

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:35.469734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:24.678017Z digest=sha256:07a9edff27fd4bcb27b76ad34326ab51f0d657ef5e426380848bb0798eb6369b

Observation 35602a54-dd1a-44aa-97b6-8637ca670b5c · outbound

This paper cites The information bottleneck problem and its applications in machine learning.

Text embedding models can be great data engineers The information bottleneck problem and its applications in machine learning

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:35.300410Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:24.781800Z digest=sha256:8298c60b306aa7b7b1848c9b09ccda3bad426ace9f4744455194360727225b38

Observation d3df4971-112a-4dbc-bef2-8bab118fd115 · outbound

This paper cites Audioclip: Extending clip to image, text and audio.

Text embedding models can be great data engineers Audioclip: Extending clip to image, text and audio

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:35.146788Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:24.879276Z digest=sha256:ecd1b4e3b43c3678ce6fc957b37ae570d699b4ec44584ab647986c6cc7c2790e

Observation 74567220-6d05-4def-934d-ff40b7ed6196 · outbound

This paper cites Distributional structure.

Text embedding models can be great data engineers Distributional structure

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-07T15:32:24.982583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:32:24.982583Z digest=sha256:d91a479c2bf8ac89d5681678004d2552f0c58da672193feedaab92ec69f84985

Observation e015a6d3-fc5d-4755-9d79-cea5b93c70c9 · outbound

This paper cites beta-vae: Learning basic visual concepts with a constrained variational framework.

Text embedding models can be great data engineers beta-vae: Learning basic visual concepts with a constrained variational framework

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T15:32:25.063577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:32:25.063577Z digest=sha256:ec3f85db90b729c51641e52e61222da718f3695c21856e64a1890ce6afb8e50e

Observation 537649ab-9193-40d6-bfdb-60211967b3e4 · outbound

This paper cites A survey of outlier detection methodologies.

Text embedding models can be great data engineers A survey of outlier detection methodologies

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:34.975140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:25.187335Z digest=sha256:ba3ecee01925558d911a5dc1a708b520d9187586d67973a1f9f4f1b04de8c6e9

Observation 32b4ba2e-bd3e-453e-85b4-dc4f03b88284 · outbound

This paper cites A framework for extracting urban functional regions based on multiprototype word embeddings using points-of- interest data.

Text embedding models can be great data engineers A framework for extracting urban functional regions based on multiprototype word embeddings using points-of- interest data

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:34.791855Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:25.289589Z digest=sha256:dc72b16ddc01ad37ea1a8a04efe3460e21cf1b9d3b8fd42ad72b160cad9ac397

Observation 55aea251-22de-4aa0-9b17-0f549ed178bc · outbound

This paper cites Multilevel temporal-spectral fusion network for multivariate time series classification.

Text embedding models can be great data engineers Multilevel temporal-spectral fusion network for multivariate time series classification

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:34.629350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:25.385463Z digest=sha256:cfa4fdb6791e76f07afecf34d4f74bb938665de3f7dcb912d370149dc25ba532

Observation fcaf7703-024d-4943-b2cb-e4c80251f9a3 · outbound

This paper cites HRI Dataset.

Text embedding models can be great data engineers HRI Dataset

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:34.395332Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:25.487288Z digest=sha256:a9bce3a8d54ceee03cb7cfb05f707bf037f9a77cd5084de5ee6dbc70f6babf1f

Observation 74a333e3-b53f-4b99-bce4-83831901fd62 · outbound

This paper cites Large-scale representation learning from visually grounded untranscribed speech.

Text embedding models can be great data engineers Large-scale representation learning from visually grounded untranscribed speech

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-07T15:32:28.628245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:25.641047Z digest=sha256:11725f14910055e7a9f8e490f12e8bad04be2ec0551f724e6bebc76057c04dcd

Observation b5a24275-a152-431c-aa3f-977250d189b2 · outbound

This paper cites Autokeras: An automl library for deep learning.

Text embedding models can be great data engineers Autokeras: An automl library for deep learning

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:34.218015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:25.728739Z digest=sha256:a896a6d4e62641293fc856752cf5d4387e3c7bb2dd8eea72a446c2f3e64b62dd

Observation e4ba270b-4c23-4381-b4ef-e6a5948946d4 · outbound

This paper cites Dimensionality reduction for fast similarity search in large time series databases.

Text embedding models can be great data engineers Dimensionality reduction for fast similarity search in large time series databases

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:34.086845Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:25.826625Z digest=sha256:49f19c752c56dfa064f3d626a7ada7b4e8d160fb91ca472c2f4f5f77cd5a6de8

Observation 4d727bee-f71e-4692-a108-2362698a90a1 · outbound

This paper cites Representation learning of clinical multivariate time series with random filter banks.

Text embedding models can be great data engineers Representation learning of clinical multivariate time series with random filter banks

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:33.898229Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:25.917897Z digest=sha256:bf44a47719dee0ccb2835995f1dc4c7660a5c6f5393a5ad0e0c578cf2dfc3bc8

Observation 8ae5e05e-d9dd-4e95-8c1e-e63084497fc7 · outbound

This paper cites Time series classification of cryptocurrency price trend based on a recurrent lstm neural network.

Text embedding models can be great data engineers Time series classification of cryptocurrency price trend based on a recurrent lstm neural network

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:33.669396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:26.016139Z digest=sha256:07dca347fa2786c2c8a8ce8e87d034292cd999d05ed2eff7e43c3a0d67513370

Observation 2a8b3490-f2cf-4f08-8b97-ae7adef50d86 · outbound

This paper cites H2o automl: Scalable automatic machine learning.

Text embedding models can be great data engineers H2o automl: Scalable automatic machine learning

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:33.506535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:26.113061Z digest=sha256:7b3811fef484028e3bdccdd801dcbe1a62771cf4581d18b09a667120d953e1b8

Observation b7ef3520-7abb-420a-9e9e-082143188850 · outbound

This paper cites Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median.

Text embedding models can be great data engineers Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:33.364053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:26.201904Z digest=sha256:4fe9bc872ceb6c80f459220a82894f91a88331bb96e2f244fcb94b1816bb8ab6

Observation 9dd3406b-5ef4-463a-90fc-31e6daa6b1fa · outbound

This paper cites Feature selection: A data perspective.

Text embedding models can be great data engineers Feature selection: A data perspective

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:33.187424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:26.337252Z digest=sha256:981e1dac977041cdbf78cb80f36e431d6f64cf9c58bff674dfd922756a7254bf

Observation 69faa19b-20cf-414d-8ec1-f4c7654ec2a4 · outbound

This paper cites Missing value imputation: a review and analysis of the literature (2006–2017).

Text embedding models can be great data engineers Missing value imputation: a review and analysis of the literature (2006–2017)

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:33.032228Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:26.427866Z digest=sha256:d3922a531f31196f25c833b7792367821b1994c15cb39521045248a574affa5c

Observation 274199f1-7afd-4ab2-9f2e-312f1dca847c · outbound

This paper cites Cubic spline interpolation.

Text embedding models can be great data engineers Cubic spline interpolation

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-07T15:32:26.493453Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:32:26.493453Z digest=sha256:1836477b6f5d1da5ee6405e645654304d3b45ba51bcb32a7b9d0d1a72ed768a8

Observation 234353db-c57a-4f8d-b060-2880cddd3775 · outbound

This paper cites Howto100m: Learning a text-video embedding by watching hundred million narrated video clips.

Text embedding models can be great data engineers Howto100m: Learning a text-video embedding by watching hundred million narrated video clips

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-07T15:32:26.582632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:32:26.582632Z digest=sha256:c2e14eb914e2b05f985483c6505fb6e641b7127e35fb58f0c6833890203d8c2e

Observation f17e056f-7a01-49fd-8841-216ca5d12eab · outbound

This paper cites Enhanced bitcoin price direction forecasting with dqn.

Text embedding models can be great data engineers Enhanced bitcoin price direction forecasting with dqn

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:32.838416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:26.646460Z digest=sha256:81073c47f035b7b5918a5e66eec0d03a245b0c505054a03c7e3bf075cb3c73ca

Observation 91a10310-20c0-4c35-93dc-fc494478a284 · outbound

This paper cites Unsupervised embedding of trajectories captures the latent structure of scientific migration.

Text embedding models can be great data engineers Unsupervised embedding of trajectories captures the latent structure of scientific migration

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:32.667924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:26.723782Z digest=sha256:72bbc11d05589a1ff7455ce02078148a9b9911e45730dd62341a117b60db7ab8

Observation 79a2bb15-2987-46df-8ccd-bae7ff6abbb5 · outbound

This paper cites Delineating urban functional use from points of interest data with neural network embedding: A case study in greater london.

Text embedding models can be great data engineers Delineating urban functional use from points of interest data with neural network embedding: A case study in greater london

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:32.468483Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:26.789070Z digest=sha256:92e0d866b9519e62b2aaea994d6d2f3c60e9a1797440224afd6ac691489130e9

Observation f3c80c0b-993d-4fef-bdbd-c17149a3508e · outbound

This paper cites AMPEL workflows for LSST: Modular and reproducible real-time photometric classification.

Text embedding models can be great data engineers AMPEL workflows for LSST: Modular and reproducible real-time photometric classification

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-07T15:32:26.862403Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:32:26.862403Z digest=sha256:39fd509f2445ce37550e03e041ee9fcbaa1e34d28d2d2d6edd49542a5fec53e8

Observation 9a6514c0-98bc-4723-a6f5-8d050042e49e · outbound

This paper cites Nomic Embed: Training a Reproducible Long Context Text Embedder.

Text embedding models can be great data engineers Nomic Embed: Training a Reproducible Long Context Text Embedder

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-07T15:32:26.935041Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T15:32:26.935041Z digest=sha256:381b3d111f4b4bf150ee11c1fc3b93b5be62b72e994cb7d54282388d12e410fb

Observation 58cd422e-7336-411a-b495-99db0578e862 · outbound

This paper cites Olson, Nathan Bartley, Ryan J.

Text embedding models can be great data engineers Olson, Nathan Bartley, Ryan J

Reference 35

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:32.241264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.015106Z digest=sha256:a7f7b5d990ef7f1874340ff344c3ca69f1d143090fb7c1f746c79d5240a8b173

Observation 57a58a61-9cc0-452b-9e71-8f433005e410 · outbound

This paper cites text-embedding-3-small.

Text embedding models can be great data engineers text-embedding-3-small

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:32.011822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.082813Z digest=sha256:048b7735a65032f1e5d34994b061b61a77271e72fef0358aef1eb05f0f54b90d

Observation 14063025-a6b5-4085-8cb5-cd15a329cc9c · outbound

This paper cites Tsem: Temporally-weighted spatiotemporal explainable neural network for multivariate time series.

Text embedding models can be great data engineers Tsem: Temporally-weighted spatiotemporal explainable neural network for multivariate time series

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:31.833307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.155965Z digest=sha256:b92a969c902c0d98c3cb010e9595dc75841970da4ef41b5722be2c1ee3215a75

Observation 5130f959-d010-4531-b5c2-06bfa5a7eea7 · outbound

This paper cites Convolutional neural net- work fault classification based on time-series analysis for benchmark wind turbine machine.

Text embedding models can be great data engineers Convolutional neural net- work fault classification based on time-series analysis for benchmark wind turbine machine

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:31.607659Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.211284Z digest=sha256:c02d9fc6d7bf7e092d95009ea0a999d42a6bcbc45afcf3cd9950cf995ffc54fd

Observation e7767995-9404-492c-97e4-ed32ab3fb562 · outbound

This paper cites Modelling data pipelines.

Text embedding models can be great data engineers Modelling data pipelines

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:31.380298Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.301404Z digest=sha256:167985c3934bb4915548bd5dc772efdbafb29dae723997bde8047cbf62b26d0b

Observation eac3e038-1e51-469b-a062-9793f709cf5a · outbound

This paper cites Time-series cryptocurrency forecasting using ensemble deep learning.

Text embedding models can be great data engineers Time-series cryptocurrency forecasting using ensemble deep learning

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:31.162771Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.359698Z digest=sha256:339b515333d685fff6d5da2aeb49038f2f7aa2b99cefc87bbc490b4a54a8a968

Observation 26e8ab9b-723e-40e8-93fd-12214060f545 · outbound

This paper cites Word embeddings for the analysis of ideological placement in parliamentary corpora.

Text embedding models can be great data engineers Word embeddings for the analysis of ideological placement in parliamentary corpora

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:30.939335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.449438Z digest=sha256:51691331a30f7482d5c5b5ae9132d23e710aab9def23123636c4decf8171aef4

Observation 636bf2ca-0d3d-4da7-8323-ff72aa8064f6 · outbound

This paper cites Predicting high-level human judgment across diverse behavioral domains.

Text embedding models can be great data engineers Predicting high-level human judgment across diverse behavioral domains

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:30.731072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.524459Z digest=sha256:6ff73312f0055a61f83e880530bd64d90e732c7f807f3d248cbf0fca1a99c5c7

Observation 3a869dbe-e1fb-47f6-838e-da9d499c0fa4 · outbound

This paper cites Gaussian processes for time-series modelling.

Text embedding models can be great data engineers Gaussian processes for time-series modelling

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:30.530030Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.622073Z digest=sha256:346db2dc03cdf6f14f3606909d398649b125985af8f08d70c31ce8504dea9227

Observation 2d8fa0ee-c750-47b3-8d9e-108080e269e3 · outbound

This paper cites Automl: A systematic review on automated machine learning with neural architecture search.

Text embedding models can be great data engineers Automl: A systematic review on automated machine learning with neural architecture search

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:30.354364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.687851Z digest=sha256:056ba38f2191f15b8434a333e38cd396b3b92b80914e4ab18fa2b38ddcf65ea6

Observation d61ff29d-b2a8-42cb-984c-03e04ee80249 · outbound

This paper cites Oracle: A real-time, hierarchical, deep-learning photometric classifier for the lsst.

Text embedding models can be great data engineers Oracle: A real-time, hierarchical, deep-learning photometric classifier for the lsst

Reference 45

Resolution
verified exact
raw_fallback, observed 2026-08-07T15:32:28.392498Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.749167Z digest=sha256:fbc64379a5f499c9838b4d32b7c60420e0222349bc42a8475fe45e5ff78ebda5

Observation f8a37a06-51db-4f6a-a6cf-abd039445ee5 · outbound

This paper cites Videobert: A joint model for video and language representation learning.

Text embedding models can be great data engineers Videobert: A joint model for video and language representation learning

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:30.177369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.818031Z digest=sha256:383093b153895e6e9dcc6bf1bd1e9cf4fdd06ad61d4219057aa038dbf88290c9

Observation 43c3f354-6c5d-4559-b82b-29e0e2122e1d · outbound

This paper cites Survey: Time-series data preprocessing: A survey and an empirical analysis.

Text embedding models can be great data engineers Survey: Time-series data preprocessing: A survey and an empirical analysis

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:30.063099Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.857161Z digest=sha256:57e58f7cf20926e8b2a1863b597e3beea94cb424b478ac3b028e3488b7c31bf0

Observation 70f829bb-3685-4cc0-9a07-16db26455803 · outbound

This paper cites up”) or decrease (“down.

Text embedding models can be great data engineers up”) or decrease (“down

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:29.956990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.931923Z digest=sha256:55e51101e9202bd869050ecf623a6e5a704d48d5b798de9433e0394f19883284

Observation 131fc23c-644f-4ddd-8fa9-9aab34c140f5 · outbound

This paper cites an unresolved cited work.

Text embedding models can be great data engineers Unresolved cited work

Reference 49

Resolution
unresolved
raw_fallback, observed 2026-08-07T15:32:29.614622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.935295Z digest=sha256:9e0c71662462bb144d0b4012bc1c29699998fe59c4ea8877b34732f7a08d40a1

Observation e8adf54c-4ab2-4f36-b868-aa586f9d2076 · outbound

This paper cites an unresolved cited work.

Text embedding models can be great data engineers Unresolved cited work

Reference 50

Resolution
unresolved
raw_fallback, observed 2026-08-07T15:32:29.261692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:27.977320Z digest=sha256:758f8d552f29945abbf7480fb4a4f2fa04aa2a766cdb4b45ca94889c8de5d9f4

Observation 66ad6b61-c460-4154-9c06-c49657b3639d · outbound

This paper cites negativity.

Text embedding models can be great data engineers negativity

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:29.001501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:28.059564Z digest=sha256:ad0445de2165e975c8c80466a568f55ce106fc01c688ee9fc5390f56572bb5f3

Observation 98b2f3bd-e6f6-4819-ab83-55862510bc57 · outbound

This paper cites Table 5: Per-class performance on the HRI dataset.

Text embedding models can be great data engineers Table 5: Per-class performance on the HRI dataset

Reference 7009

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T15:32:28.792953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-07T15:32:28.149076Z digest=sha256:6a91197b2013ab8c2f999775972680f501565a32843ab3df6bc07284a2938ca5

Pith citing papers

No inbound Pith citation observations are available.