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Paper Citation Record · LEDGER

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM

As of 7 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2607.06905.

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

pith.paper-citation-record.v1
2607.06905 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-09T23:20:20.660926Z

measured 18 of 18 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+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

18 of 18 outbound references displayed

  • verified exact1
  • verified fuzzy16
  • unresolved1
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a7d26b26-38fe-4365-9572-40c5257583fa · outbound

This paper cites 2014 , publisher =.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM 2014 , publisher =

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.337193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:b13f12bf3c94bee6d30d738f7a36a4c6d631be4a6806b91beb9c988ee7e67643

Observation 1c9c34f9-c5c4-4cbc-8a8f-ae04da4f2ffe · outbound

This paper cites Lord , title =.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM Lord , title =

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.336935Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:72a3ba0b3ff89c66c3facaaf0eb7198f60d0960dab9b298b17940de40910af51

Observation d9b743b3-62ac-4b9e-acd9-fe9bb8d3bdc2 · outbound

This paper cites 1979 , publisher=.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM 1979 , publisher=

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.325746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:6ad499589a640a2c0a98bc3e9fa71521ae201016bd9605a835b8d6a7c24e033d

Observation b3c7ee2c-f597-45d7-b286-851846a8fee9 · outbound

This paper cites Journal of Computer Assisted Learning , volume=.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM Journal of Computer Assisted Learning , volume=

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.323878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:159afddf81ffbb9b6b91ba29ab8de4388b38919b9f8f48db8b5a8ffd4fa40918

Observation a8217ea5-0d52-468f-971c-2ae36651ead3 · outbound

This paper cites Educational Measurement: Issues and Practice , volume=.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM Educational Measurement: Issues and Practice , volume=

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.320480Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:e1706c63a5672c95e48f253949c62b3e2f73ef7900164177761840d9254eacc5

Observation 0396f19f-ff27-4715-be21-da550c067c70 · outbound

This paper cites Tesol Quarterly , volume=.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM Tesol Quarterly , volume=

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.329413Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:180143c89e32411bef2969101142491a87e96135d530e89f2a4c744f438062b1

Observation 6fe3cb8c-03a4-4869-aa85-b77a225f69d1 · outbound

This paper cites , title =.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM , title =

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.327803Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:22e22a86b933880b80765041845243b54941e2dcfc85bba7ae5b92838736d2ce

Observation 84ce84af-397f-40b8-b1cf-90acabf37cd2 · outbound

This paper cites Proceedings of the 2021 conference on empirical methods in natural language processing , pages=.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM Proceedings of the 2021 conference on empirical methods in natural language processing , pages=

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.332184Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:f7c0533905b5f8dc36526d766227e8142fba52a8b30763080786746333b26ed4

Observation 8b648b84-7b5d-4af2-9eba-b1bc6c7745f2 · outbound

This paper cites Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2024) , pages=.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM Proceedings of the 19th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2024) , pages=

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.327991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:d9eaac8f7188914fc2ec84735cecd9f799d3507bb52987b51692f22e658f2010

Observation 2e759717-2970-4661-abfc-3fd2e48f666d · outbound

This paper cites AutoIRT: Calibrating Item Response Theory Models with Automated Machine Learning.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM AutoIRT: Calibrating Item Response Theory Models with Automated Machine Learning

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-07-09T23:26:36.876687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:a5afac16713f94cdb54a6414f99f6798ceadda48c36ba26fd16746246df16778

Observation 910d97d2-027d-4661-bfa4-55c08112665c · outbound

This paper cites an unresolved cited work.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM Unresolved cited work

Reference 11

Resolution
unresolved
raw_fallback, observed 2026-07-09T23:26:37.330121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:34b583e631e31b3c8d8abe5c507d3d6437e08c04e33136cf626b4f9d0cbcd7ea

Observation 449cbbac-3e0f-49f0-9dec-a43db334c217 · outbound

This paper cites and Liao, Manqian and Lockwood, J.R.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM and Liao, Manqian and Lockwood, J.R

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.332978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:7f821252faf30480fbf079112ac737f0cd0bed13385af4a0aa6a6d42dc050137

Observation 34e8120e-b977-4ad4-b268-64ebdc9fc879 · outbound

This paper cites 2021 , publisher=.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM 2021 , publisher=

Reference 13

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.330976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:e284fa96e6ff626f062b4d60bf225a49c06d7ccf30fc11c80e6210fe991c3e09

Observation c643c25e-8f51-4912-928f-32eb483a756b · outbound

This paper cites and Settles, Burr , journal=.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM and Settles, Burr , journal=

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.318608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:6c411e1318cf9260d3da0e6ab451d9118b53d7dba1705481fdee5e6b086f9a2d

Observation e13804e7-324d-48dd-bc51-076025218bc6 · outbound

This paper cites Frontiers in Artificial Intelligence , volume=.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM Frontiers in Artificial Intelligence , volume=

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.312279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:cf11a594c3e4bedbef53bae1f5712221a93dc768d1902868dab1b02e00d77b38

Observation e04ffdfb-b74e-4e21-9ece-c69a1506d15a · outbound

This paper cites 2008 , howpublished =.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM 2008 , howpublished =

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.320118Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:a41c478058b5f01341f8664613c9a17e0df919fac859db090cd2e625c06a4f11

Observation 15704da8-599f-4f7c-a743-00f3e092f129 · outbound

This paper cites 2001 , publisher =.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM 2001 , publisher =

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.325927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:c7872ea59757133c37cd2a081cc22b09fa94fb4db72e5fa6c1b4d38dfccf1dde

Observation e1c7f82b-9395-470e-b940-015f9eeeb350 · outbound

This paper cites International Conference on Learning Representations (ICLR) , year=.

Learning Item Embeddings and Hyperparameters for IRT Calibration via Monte Carlo EM International Conference on Learning Representations (ICLR) , year=

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-07-09T23:26:37.306271Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

source=arxiv_source observed=2026-07-09T23:20:20.660926Z digest=sha256:4e0d63c0f04505124d12b43b89d92f82af1c68cc76e4e7b21631d3d847803f51

Pith citing papers

No inbound Pith citation observations are available.