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Paper Citation Record · LEDGER

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods

As of 14 August 2026, this Paper Citation Record lists 25 of 25 outbound references and 0 inbound Pith citation observations for arXiv:2608.13333.

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

pith.paper-citation-record.v1
2608.13333 v1

Coverage vector

measured 25 of 25 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:30:55.685027Z

measured 25 of 25 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+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

25 of 25 outbound references displayed

  • verified exact11
  • verified fuzzy3
  • unresolved11
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation ccb86d8c-340a-4725-a22b-7d0985af9d11 · outbound

This paper cites SUNNY: a lazy portfolio approach for constraint solving.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods SUNNY: a lazy portfolio approach for constraint solving

Reference 1

Resolution
verified exact
doi, observed 2026-08-14T13:30:55.938146Z

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.

source=arxiv_source observed=2026-08-14T13:30:55.564080Z digest=sha256:6135de2fa828c4095dcc4fef075e4a54ec2e348d2314672cee01f870c11c868b

Observation c93b9727-f8cf-4686-8f5e-cf5bf4ef6c6d · outbound

This paper cites Large language model meets constraint propagation.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Large language model meets constraint propagation

Reference 2

Resolution
verified exact
doi, observed 2026-08-14T13:30:55.922845Z

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.

source=arxiv_source observed=2026-08-14T13:30:55.569428Z digest=sha256:56d68627f2041a816039e9db4cf04a4b015bde6de6ac7dac471a620abd35e7cf

Observation 97999970-55af-463a-95a1-7b08f84d4e78 · outbound

This paper cites Tree clustering for constraint networks.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Tree clustering for constraint networks

Reference 3

Resolution
verified exact
doi, observed 2026-08-14T13:30:55.906682Z

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.

source=arxiv_source observed=2026-08-14T13:30:55.574519Z digest=sha256:2dc7b532a65041d3ebb25d08476ac3c77bd8417eaafc9400f4c46a4620fa950a

Observation ff8da600-7300-4751-b078-7d6f49a8afde · outbound

This paper cites SAT -based local improvement for finding tree decompositions of small width.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods SAT -based local improvement for finding tree decompositions of small width

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-14T13:30:55.580867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:30:55.580867Z digest=sha256:fa70e858e920d5529dbb22a56ffd49d076e603752a25573a31c69eff948a6e9c

Observation 74ea18b3-c068-436e-9ce9-e97f46d29726 · outbound

This paper cites Exact combinatorial optimization with graph convolutional neural networks.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Exact combinatorial optimization with graph convolutional neural networks

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:30:56.372677Z

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.

source=arxiv_source observed=2026-08-14T13:30:55.586097Z digest=sha256:37987f101f4107694a8fc94586708797a3f10bd04619441b6f6bc5ac81218c88

Observation 296f5cc9-37da-4ba6-94af-fe84ca786db7 · outbound

This paper cites Hypertree decompositions and tractable queries.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Hypertree decompositions and tractable queries

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-14T13:30:55.591835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:30:55.591835Z digest=sha256:354ee307dec056f76e90b550598fa83bc7d046de541798d9aed646ec18dc2b43

Observation 734e9375-8d38-44ab-b13a-fe2a52a81134 · outbound

This paper cites Neural large neighborhood search for routing problems.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Neural large neighborhood search for routing problems

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-14T13:30:55.597217Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:30:55.597217Z digest=sha256:922ef6605698b769b9be90be2c91050028598096d3274dfdfb4f3cc198069a21

Observation 7f21113b-0b58-4157-8da5-3167cc004680 · outbound

This paper cites GRAPH reinforcement learning for operator selection in the ALNS metaheuristic.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods GRAPH reinforcement learning for operator selection in the ALNS metaheuristic

Reference 8

Resolution
verified exact
doi, observed 2026-08-14T13:30:55.882591Z

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.

source=arxiv_source observed=2026-08-14T13:30:55.601824Z digest=sha256:fda257b0ad6ae12e490ebbabedf22a97d71ea6c2236a753e51d1d774798592ec

Observation ba406c80-172f-45f1-962b-2c9c6fad770f · outbound

This paper cites Hoos, Frank Hutter, and Torsten Schaub.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Hoos, Frank Hutter, and Torsten Schaub

Reference 9

Resolution
verified exact
doi, observed 2026-08-14T13:30:55.866182Z

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.

source=arxiv_source observed=2026-08-14T13:30:55.606526Z digest=sha256:19d0df15fa371e5c15d96b6a2551151d921e57607e812ce8f48f3aa292824900

Observation 734a67bc-7a7f-4090-a081-2a54c038cc44 · outbound

This paper cites A SAT approach to branchwidth.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods A SAT approach to branchwidth

Reference 10

Resolution
verified exact
doi, observed 2026-08-14T13:30:55.850426Z

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.

source=arxiv_source observed=2026-08-14T13:30:55.611273Z digest=sha256:2f1ca2cd30017ed95f74d604a055419663c80a440fba9d42d0362f6c311668a1

Observation 1cc5f2d9-d63f-40fc-a4d3-c03e25915994 · outbound

This paper cites Learning large Bayesian networks with expert constraints.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Learning large Bayesian networks with expert constraints

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:30:56.357108Z

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.

source=arxiv_source observed=2026-08-14T13:30:55.615932Z digest=sha256:9cf8ee5ba7499341754b25dddd07bda83c9b1ca9ddbada38fe4c7255a7126317

Observation 1e56912b-8aa0-4733-85de-9e25b84ee356 · outbound

This paper cites Large neighborhood search.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Large neighborhood search

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-14T13:30:55.620906Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:30:55.620906Z digest=sha256:1535b4d02984521396e425f747f38076b3ef8ca5ed901aee5b53b11a751ca1a0

Observation 4b8d116c-f3a2-4c23-813d-e3216093fe3d · outbound

This paper cites MaxSAT-Based postprocessing for treedepth.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods MaxSAT-Based postprocessing for treedepth

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-14T13:30:55.625659Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:30:55.625659Z digest=sha256:a9ac6aba4f8169aa2ecd92ae817f8d82e6dfb963e8e87a1b1dd1c44016b8cf41

Observation 45fedd24-ae71-412e-abe1-6dc5002c495a · outbound

This paper cites Turbocharging treewidth-bounded bayesian network structure learning.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Turbocharging treewidth-bounded bayesian network structure learning

Reference 14

Resolution
verified exact
doi, observed 2026-08-14T13:30:55.816231Z

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.

source=arxiv_source observed=2026-08-14T13:30:55.631305Z digest=sha256:4dd49462d98fcf6f8833c9adc40a89636a33ae1fb9cbfd699b208f1be1df5c53

Observation f5d381d4-75a8-4abb-95aa-d09533e201dc · outbound

This paper cites The power of collaboration: Learning large bayesian networks at scale.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods The power of collaboration: Learning large bayesian networks at scale

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-14T13:30:55.636009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:30:55.636009Z digest=sha256:f5f979dc8aef2b27b966ac84d68bdee3b1170969969fe4d8d6167b5f11a215bf

Observation 91490db1-959e-4d5a-bebb-8892490876e0 · outbound

This paper cites Pawan Kumar, Emilien Dupont, Francisco J.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Pawan Kumar, Emilien Dupont, Francisco J

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-14T13:30:55.640842Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:30:55.640842Z digest=sha256:dec31b2f44a8803184503108f0b3150e2d1cab101fde2d40c248c0ec00e2f2e2

Observation 4eb6b54a-f98e-4658-85a7-544530ff881f · outbound

This paper cites An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods An adaptive large neighborhood search heuristic for the pickup and delivery problem with time windows

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-14T13:30:55.646327Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:30:55.646327Z digest=sha256:6fc78057d3d83ee1de41163c7f2867c66a97fcef972123bc736ddc9519649e1b

Observation 32094757-5d6e-4e21-ac46-f78a0f6697c5 · outbound

This paper cites Sat-boosted tabu search for coloring massive graphs.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Sat-boosted tabu search for coloring massive graphs

Reference 18

Resolution
verified exact
doi, observed 2026-08-14T13:30:55.789549Z

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.

source=arxiv_source observed=2026-08-14T13:30:55.651015Z digest=sha256:374e3a4aced409c71c0c2524d5ccd5050fecf1ee0750b7790d68d5485101dcf6

Observation cfb9e0e1-9204-48b5-a668-f58b6a81cc01 · outbound

This paper cites Structure-guided local improvement for maximum satisfiability.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Structure-guided local improvement for maximum satisfiability

Reference 19

Resolution
verified exact
doi, observed 2026-08-14T13:30:55.773572Z

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.

source=arxiv_source observed=2026-08-14T13:30:55.656381Z digest=sha256:189460404bf09aa2e0758a20a627b339a07eb33dbd4ee99d9a526c010722d311

Observation 78c9a0a1-37fd-49c9-8414-1afa8bf47deb · outbound

This paper cites SAT -based decision tree learning for large data sets.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods SAT -based decision tree learning for large data sets

Reference 20

Resolution
unresolved
no resolver link, observed 2026-08-14T13:30:55.661782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:30:55.661782Z digest=sha256:0b7e5419b9c566939d2b940afa5ee1d0a9362eb3a2305ad03a5f551eacf26b75

Observation 24e688bb-9607-43fc-ad44-3a4661b537a2 · outbound

This paper cites Using constraint programming and local search methods to solve vehicle routing problems.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Using constraint programming and local search methods to solve vehicle routing problems

Reference 21

Resolution
verified exact
doi, observed 2026-08-14T13:30:55.748404Z

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.

source=arxiv_source observed=2026-08-14T13:30:55.666534Z digest=sha256:508665eeec2cd0298a71c315d5d8dfe073b705e7b734e317ac57a58de8d8bad3

Observation 75d741e3-6c22-44f8-b6bf-02707606e1ad · outbound

This paper cites Text2Zinc: A Cross-Domain Dataset for Modeling Optimization and Satisfaction Problems in MiniZinc.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Text2Zinc: A Cross-Domain Dataset for Modeling Optimization and Satisfaction Problems in MiniZinc

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-14T13:30:55.671259Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:30:55.671259Z digest=sha256:747895d6aac24855ebddac44095635da6e3360687c7660c4a0d7fe6d3e3ec887

Observation 0284afe4-9ae2-4410-ba85-4c06cf8f138e · outbound

This paper cites SAT-Based tree decomposition with iterative cascading policy selection.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods SAT-Based tree decomposition with iterative cascading policy selection

Reference 23

Resolution
verified exact
doi, observed 2026-08-14T13:30:56.342314Z

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.

source=arxiv_source observed=2026-08-14T13:30:55.675880Z digest=sha256:6faaece4503037cb9ae8bd81f3b95c129f5a0d9e764a4c1aa4ad8f7ef7cce5c9

Observation ab412a5c-7166-439d-b2e3-b5c09ac6a96e · outbound

This paper cites Hoos, and Kevin Leyton - Brown.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Hoos, and Kevin Leyton - Brown

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-14T13:30:55.680429Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-14T13:30:55.680429Z digest=sha256:f909e37914b35de92735d07f48c19b217d6034604331ac40213963c5b98d3147

Observation c952cd8b-fa56-4a77-8f50-2811f004cf94 · outbound

This paper cites Le, Denny Zhou, and Xinyun Chen.

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods Le, Denny Zhou, and Xinyun Chen

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:30:56.326480Z

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.

source=arxiv_source observed=2026-08-14T13:30:55.685027Z digest=sha256:6f4fc4a1c9ecbee7d43cfd5e7353cd608e8a9197be27a7fbe057d392e667b172

Pith citing papers

No inbound Pith citation observations are available.