Pith. sign in

Paper Citation Record · LEDGER

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning

As of 18 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 0 inbound Pith citation observations for arXiv:2506.20814.

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

pith.paper-citation-record.v1
2506.20814 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:44:05.592838Z

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+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

21 of 21 outbound references displayed

  • verified exact1
  • verified fuzzy11
  • unresolved9
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4f0991c9-4155-497e-a5c6-f427633c7b0f · outbound

This paper cites Pervasive and Mobile Computing 104, 101973 (2024).

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning Pervasive and Mobile Computing 104, 101973 (2024)

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:07.625969Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:44:03.944959Z digest=sha256:fcc2f52db5368d459c0cb3470c06cece2b23fcd9da763241a338615d06d7e79a

Observation e6fd2e48-71af-495a-89f6-08793036b644 · outbound

This paper cites OpenML Benchmarking Suites.

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning OpenML Benchmarking Suites

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T22:44:04.015420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:04.015420Z digest=sha256:d1a37381e7fa0d51e091895c8eba8fa49cc882570746c7e754a4fc6fd97d107b

Observation 0eab8e98-2c8c-4c44-8861-947a8a8b52d2 · outbound

This paper cites Machine learning45, 5–32 (2001).

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning Machine learning45, 5–32 (2001)

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-06T22:44:04.146627Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:04.146627Z digest=sha256:25628e64d66012b42a239023132ed6af53b62740293cbba71b0a80ba2ff5f962

Observation 5389a55d-6292-463e-8ded-3df284ff3c18 · outbound

This paper cites In: Sixth International Conference on Data Mining (ICDM’06).

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning In: Sixth International Conference on Data Mining (ICDM’06)

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:07.431884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:44:04.293795Z digest=sha256:5c04d31df51c57bad071bc6c3080f999fa3d3c06be3da1bb6ad482eaf31be799

Observation 77d5ce0d-2a4c-4dda-a514-9329e1537cbb · outbound

This paper cites In: Proceedings of the twenty-first international conference on Machine learning.

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning In: Proceedings of the twenty-first international conference on Machine learning

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:07.219622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:44:04.409851Z digest=sha256:cee235d1c9ce0bdb5429ec750221c37d0286b3064084c0d746b41a2c7626bbb4

Observation d29e9e3f-c565-42eb-9d45-b5ad323677c8 · outbound

This paper cites Neural computing and applications22, 673–688 (2013).

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning Neural computing and applications22, 673–688 (2013)

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:07.077655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:44:04.545802Z digest=sha256:bf70390f6ae60c3bdce11e9e123eabe7f58a646c17640f10e3c5a47f2e28e4f4

Observation e3752ef8-1117-47fb-9e2b-3aeeca205e28 · outbound

This paper cites In: Proceedings of the 22nd ACM SIGKDD International Con- ference on Knowledge Discovery and Data Mining.

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning In: Proceedings of the 22nd ACM SIGKDD International Con- ference on Knowledge Discovery and Data Mining

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T22:44:04.636106Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:04.636106Z digest=sha256:12e4e3a76e076c19076b4ccd7087caefaf1cc2ebecd3722a7a8378b5d3c53ee7

Observation c75db7b2-a5f2-49e5-b65a-388d88b66369 · outbound

This paper cites Pattern recognition48(5), 1925–1935 (2015).

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning Pattern recognition48(5), 1925–1935 (2015)

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:06.941049Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:44:04.707825Z digest=sha256:f014955c32e543a8a8f8dd587e52169d466693022e39bcfc059bebe6870d229e

Observation a058c5e1-8808-4180-831a-a1ab3d8e0892 · outbound

This paper cites Ensemble machine learn- ing: Methods and applications pp.

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning Ensemble machine learn- ing: Methods and applications pp

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:06.818115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:44:04.794701Z digest=sha256:73c1297d0dfa96b20096d0bfa37d4cfdc601336c960c7973b3ed1d351493f8ec

Observation 7a524d5b-83c1-4406-99e3-41e02712e64a · outbound

This paper cites In: International work- shop on multiple classifier systems.

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning In: International work- shop on multiple classifier systems

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T22:44:04.857702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:04.857702Z digest=sha256:5b1136de3327188e8ce6f908e428dfc59edcfad6eabe938d9862208b1309ea83

Observation 2802386e-945a-48bf-86ad-3d2abdc552f9 · outbound

This paper cites Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing.

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning Hybrid LLM: Cost-Efficient and Quality-Aware Query Routing

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T22:44:04.913416Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:04.913416Z digest=sha256:f28a6bc411d86c2130610b839ecc78123bdd0e5efd077f3af45e2d9910b24e24

Observation 062da00c-42e3-4dea-9a8d-fd9240d604b2 · outbound

This paper cites AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data.

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning AutoGluon-Tabular: Robust and Accurate AutoML for Structured Data

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-06T22:44:05.037737Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:05.037737Z digest=sha256:f1ad98280958bfd94fb5bd2e331c5b3e7943a20519b25cc5fa12e43242c23704

Observation d03ad751-c7b0-4bd4-8283-6dff553584ef · outbound

This paper cites Journal of Machine Learning Research 23(261), 1–61 (2022).

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning Journal of Machine Learning Research 23(261), 1–61 (2022)

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T22:44:05.110002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:05.110002Z digest=sha256:b72d17ea4734ea939384e060f9d453ecef3612e2cd42bd71f43ee7fa8ff71c59

Observation 3f19760b-1982-4139-93dd-e3dc1f97aac8 · outbound

This paper cites Journal of computer and system sciences55(1), 119–139 (1997).

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning Journal of computer and system sciences55(1), 119–139 (1997)

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T22:44:05.172184Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:05.172184Z digest=sha256:dc75a447b8b9a620bc12c9e49d3f4f9775c4abf48680fbfd23a8603321515f8e

Observation 562dec42-5173-4987-a30c-8e23fc9f2fae · outbound

This paper cites Pattern Recognition34(9), 1879–1881 (2001).

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning Pattern Recognition34(9), 1879–1881 (2001)

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:06.660043Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:44:05.235462Z digest=sha256:98c7a0b053794788ca25b4f8efd5b9c5c41ab269a0366b3c6f24bb6e6b6e95cc

Observation ee9981aa-7c7e-41d5-9ee0-d71cfd5c74ae · outbound

This paper cites Pattern recognition41(5), 1718–1731 (2008).

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning Pattern recognition41(5), 1718–1731 (2008)

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:06.529414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:44:05.295453Z digest=sha256:a45f9106a0cef312548f269c0f5dd733596ad7ab477d9bd475898c6f616453cb

Observation edd440ea-9030-48c4-aa55-b60cb2a8626c · outbound

This paper cites When Do Neural Nets Outperform Boosted Trees on Tabular Data?.

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning When Do Neural Nets Outperform Boosted Trees on Tabular Data?

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T22:44:05.361071Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:44:05.361071Z digest=sha256:705e071f2479ce1e9135e21c8dd4f2154c498e92cf958be4e610fa7686716fcf

Observation d12b4a81-a257-48ba-86a0-7fec8b0e9536 · outbound

This paper cites In: International Conference on Machine Learning.

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning In: International Conference on Machine Learning

Reference 19

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:06.374444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:44:05.418258Z digest=sha256:9e25ce0edecca882ea5fe604d2121e8876211f36b18dab909d2fd191e9219fc7

Observation 7b7a31ea-2197-4e5e-9a5a-c70c65d88265 · outbound

This paper cites Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science.

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning Evaluation of a Tree-based Pipeline Optimization Tool for Automating Data Science

Reference 20

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:44:05.767153Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:44:05.496014Z digest=sha256:40ba225ab39d3bea9b22c446d03898f830baab191e2963d4393085f696a8febb

Observation ef1dc717-33d8-4321-8feb-46828f7b4960 · outbound

This paper cites Wiley interdisciplinary reviews: data min- ing and knowledge discovery5(1), 21–34 (2015).

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning Wiley interdisciplinary reviews: data min- ing and knowledge discovery5(1), 21–34 (2015)

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:06.207922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:44:05.530974Z digest=sha256:9331265a710f9fdd0dd7e1bec8f208fa8bb5a14342bfa4cbb310efabdd0dc3a7

Observation 6e195b9a-cb9e-491c-9972-48887603d603 · outbound

This paper cites IEEE transactions on pattern analysis and machine intelligence 19(4), 405–410 (1997).

Divide, Specialize, and Route: A New Approach to Efficient Ensemble Learning IEEE transactions on pattern analysis and machine intelligence 19(4), 405–410 (1997)

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:44:06.060142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-08-06T22:44:05.592838Z digest=sha256:08131feb12062141a0e114c58272daec6923989d06bc68fd9f151a0eaa18dcc9

Pith citing papers

No inbound Pith citation observations are available.