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Paper Citation Record · LEDGER

Code Retrieval for MILP Instance Generation

As of 21 August 2026, this Paper Citation Record lists 58 of 58 outbound references and 0 inbound Pith citation observations for arXiv:2505.11526.

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

pith.paper-citation-record.v1
2505.11526 v1

Coverage vector

measured 58 of 58 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T22:35:07.849672Z

measured 58 of 58 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+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

58 of 58 outbound references displayed

  • verified exact1
  • verified fuzzy34
  • unresolved23
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 221f6993-3fd4-4f0d-9fe6-de01d936815e · outbound

This paper cites write newline.

Code Retrieval for MILP Instance Generation write newline

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:35:07.505470Z digest=sha256:348e3996166680a6a554eed9967d04240018dc025075e5efee076cee06375725

Observation 5dec0ecb-f22d-4ca7-a141-78499c9bb190 · outbound

This paper cites and Ho, A.

Code Retrieval for MILP Instance Generation and Ho, A

Reference 2

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.512741Z digest=sha256:f50c5eb65e2a7016ac7cd69775aee37a5903da8a38e4b80eeba8276f48a0ba63

Observation ae591385-5d97-4689-8d80-4dfcccfe9f20 · outbound

This paper cites Generating hard instances for maxsat.

Code Retrieval for MILP Instance Generation Generating hard instances for maxsat

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.518629Z digest=sha256:403a5cc4f5a826e07befc43392aa997f9b183d64186c0a7430fd0e39ff22843e

Observation 3a3b74b6-ba09-47b1-a59d-43b73dab07cf · outbound

This paper cites Machine learning for combinatorial optimization: a methodological tour d’horizon.

Code Retrieval for MILP Instance Generation Machine learning for combinatorial optimization: a methodological tour d’horizon

Reference 4

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source=arxiv_source observed=2026-08-15T22:35:07.525293Z digest=sha256:4e0907b3229097e65fc0539db1813fee7de92f7f7404c5aa842d3c679bb4292d

Observation 569cb821-2791-46ec-afa7-2cfa7072434b · outbound

This paper cites A., Van Hoeve, W.-J., and Hooker, J.

Code Retrieval for MILP Instance Generation A., Van Hoeve, W.-J., and Hooker, J

Reference 5

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source=arxiv_source observed=2026-08-15T22:35:07.531050Z digest=sha256:58796f7810ef748655299928fb1b22967e8ade6894e26b215cf8671d764f9116

Observation 447671c1-352b-4000-a6e6-c88e956613f6 · outbound

This paper cites u hmer, E., Pfetsch, M. E., Schl \.

Code Retrieval for MILP Instance Generation u hmer, E., Pfetsch, M. E., Schl \

Reference 6

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raw_fallback, observed 2026-08-15T22:35:08.831212Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.536409Z digest=sha256:a96e863231d0dc0fcddf7fe203210046ee87eaf76048a304a0dc93b95245315c

Observation 5e03eaaa-8642-469c-ad58-4a8e9472d463 · outbound

This paper cites Generation techniques for linear programming instances with controllable properties.

Code Retrieval for MILP Instance Generation Generation techniques for linear programming instances with controllable properties

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.541536Z digest=sha256:2b10851635b8240e436bb381d8a337e4d12de7a9a0d5b769f036531745c12f0b

Observation 63bb1be3-a7f2-4373-aef2-9ebe7dbe6a81 · outbound

This paper cites The vehicle routing problem: State of the art classification and review.

Code Retrieval for MILP Instance Generation The vehicle routing problem: State of the art classification and review

Reference 8

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raw_fallback, observed 2026-08-15T22:35:08.796703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.547624Z digest=sha256:287a8504261a40b52048bce8d870a949eb4b2a87aedb088652fdd1dbe39e154d

Observation 4aa77dde-aad4-4583-a535-c2b04014ebd1 · outbound

This paper cites an unresolved cited work.

Code Retrieval for MILP Instance Generation Unresolved cited work

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.553007Z digest=sha256:bb9dec755aadd2b3c48842bd660a1cdf8fc7ed5c8b3bb848fc7787865a33d13b

Observation 30a5b8a2-cb05-45fe-b97e-aed0158a101e · outbound

This paper cites An milp for scheduling problems in an fms with one vehicle.

Code Retrieval for MILP Instance Generation An milp for scheduling problems in an fms with one vehicle

Reference 10

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raw_fallback, observed 2026-08-15T22:35:08.761350Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.558958Z digest=sha256:3c2b9331e610aa0bd660e9fd7a4f1e52607cbcfdb58a7638275235da6cc6b776

Observation 01a5ea22-0a31-4ebc-8e0a-578a0932253e · outbound

This paper cites The generalized independent set problem: Polyhedral analysis and solution approaches.

Code Retrieval for MILP Instance Generation The generalized independent set problem: Polyhedral analysis and solution approaches

Reference 11

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raw_fallback, observed 2026-08-15T22:35:08.741274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.564670Z digest=sha256:8b9e34151b8c7343f04f6cec3cebaf736319db91863db25c4aa8292a0c8bd3c0

Observation aacabb74-02b0-49c3-b672-6cc09d1ea4d9 · outbound

This paper cites Xtuner: A toolkit for efficiently fine-tuning llm.

Code Retrieval for MILP Instance Generation Xtuner: A toolkit for efficiently fine-tuning llm

Reference 12

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raw_fallback, observed 2026-08-15T22:35:08.724281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.570756Z digest=sha256:166095f29dc5099dd049d8952226eedfcfe1f6b0d44d3d3bf7d0aceb36116e1d

Observation b038ddde-50a8-44a1-8c00-5a846429110a · outbound

This paper cites A comparison of heuristics and relaxations for the capacitated plant location problem.

Code Retrieval for MILP Instance Generation A comparison of heuristics and relaxations for the capacitated plant location problem

Reference 13

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raw_fallback, observed 2026-08-15T22:35:08.706041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.576261Z digest=sha256:6808ecf306ba677b61024609e3ae059ece0f7919d74f5ef12cd9a02a06d6cdf7

Observation d9787013-f7cf-4adf-8372-19c5660c10cb · outbound

This paper cites The Llama 3 Herd of Models.

Code Retrieval for MILP Instance Generation The Llama 3 Herd of Models

Reference 14

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T22:35:07.582107Z digest=sha256:3ed9f64b3c2c82c7ff5f1fd10ac0823e3c69d188d7567d732364670adef325ff

Observation 38b4095f-1e95-4d83-9319-07fe1af119d4 · outbound

This paper cites an unresolved cited work.

Code Retrieval for MILP Instance Generation Unresolved cited work

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.587979Z digest=sha256:e686f22423219085e199594942653a1dd91c60bee9f9d72b93b767f62b95aa8e

Observation e3e46ab6-993e-496a-b322-78b7d707d676 · outbound

This paper cites Reverse logistics network design for a biogas plant: An approach based on milp optimization and analytical hierarchical process (ahp).

Code Retrieval for MILP Instance Generation Reverse logistics network design for a biogas plant: An approach based on milp optimization and analytical hierarchical process (ahp)

Reference 16

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raw_fallback, observed 2026-08-15T22:35:08.670313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.593459Z digest=sha256:cc95e82471d7eb6ac060dcdd7ffcf8ce1e3a1da20425b4d814786a7b7c239366

Observation f2ff9923-a707-4641-b995-b0af90752be4 · outbound

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

Code Retrieval for MILP Instance Generation Exact combinatorial optimization with graph convolutional neural networks

Reference 17

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T22:35:07.600178Z digest=sha256:da7bed216b3e857da2d355dc5c4f94246844f2bd970144ddb2bed5439850cd69

Observation 53a8bd59-f9ca-439b-b555-9f7c9d9ce8c7 · outbound

This paper cites A deep instance generative framework for milp solvers under limited data availability.

Code Retrieval for MILP Instance Generation A deep instance generative framework for milp solvers under limited data availability

Reference 18

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.606231Z digest=sha256:b822e32401de2f5e81c7961addf8f7dee71d56d927da77a44e3d4db9e8189417

Observation df365ef5-fe36-472e-9262-d57affb2e6b8 · outbound

This paper cites Miplib 2017: data-driven compilation of the 6th mixed-integer programming library.

Code Retrieval for MILP Instance Generation Miplib 2017: data-driven compilation of the 6th mixed-integer programming library

Reference 19

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raw_fallback, observed 2026-08-15T22:35:08.623985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.612722Z digest=sha256:7a0d4a2c87da8e03c2b0edec23b00e186c2a24e3f29d6ea004dbb70a9cc166f8

Observation 58fba5bb-087d-4951-aebb-41953c72ff74 · outbound

This paper cites Acm-milp: Adaptive constraint modification via grouping and selection for hardness-preserving milp instance generation.

Code Retrieval for MILP Instance Generation Acm-milp: Adaptive constraint modification via grouping and selection for hardness-preserving milp instance generation

Reference 20

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raw_fallback, observed 2026-08-15T22:35:08.606560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.622155Z digest=sha256:8cde0e6b9f526e941826d14f12e4b1cdeee00a4f74a6044a50074c2c61830cb3

Observation 4cfb2173-7d90-4b43-98e8-b1f102c6e2a8 · outbound

This paper cites Hybrid models for learning to branch.

Code Retrieval for MILP Instance Generation Hybrid models for learning to branch

Reference 21

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raw_fallback, observed 2026-08-15T22:35:08.588606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.627224Z digest=sha256:e6bcddb715a85cc2178e5438a859d36685dc77773fabde3b82880a19384f6a33

Observation a0e511d7-a57e-4a25-83d3-8c99f7d0a66c · outbound

This paper cites Lookback for Learning to Branch.

Code Retrieval for MILP Instance Generation Lookback for Learning to Branch

Reference 22

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Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T22:35:07.632737Z digest=sha256:578b9c09497dd111d039c9978802c0f8988cc1974cfc73bafb8b24945632ae32

Observation 6d756fb2-0465-4a63-b11a-8ca4c994e4c4 · outbound

This paper cites Gurobi Optimizer Reference Manual , 2024.

Code Retrieval for MILP Instance Generation Gurobi Optimizer Reference Manual , 2024

Reference 23

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source=arxiv_source observed=2026-08-15T22:35:07.637980Z digest=sha256:910400c33a965bdba6c533086435ebc1d713df39c07bdd32e6c967476866ed2e

Observation bf1f6ae9-aa7f-4175-b611-e05408390887 · outbound

This paper cites A GNN-Guided Predict-and-Search Framework for Mixed-Integer Linear Programming.

Code Retrieval for MILP Instance Generation A GNN-Guided Predict-and-Search Framework for Mixed-Integer Linear Programming

Reference 24

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source=arxiv_source observed=2026-08-15T22:35:07.643231Z digest=sha256:c88c8000bde6c3ca5a75fb253e8f545659a51601f9f147e08593f26ae79e90ba

Observation aefae100-b081-48e6-af1a-578bd7bb1b0d · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

Code Retrieval for MILP Instance Generation Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 25

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source=arxiv_source observed=2026-08-15T22:35:07.649331Z digest=sha256:f9b234e73445158d899936bb6a435f63a8a6c8c98fd72871976c2cd92c6bd890

Observation e00ef3c9-05ea-44cd-92f0-9bfb100dfbd6 · outbound

This paper cites L., and Savelsbergh, M.

Code Retrieval for MILP Instance Generation L., and Savelsbergh, M

Reference 26

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raw_fallback, observed 2026-08-15T22:35:08.548746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.654684Z digest=sha256:e6da1c14facdcdae5bca2da11b4ddd69de66e995ece1da87b15435bc50f8ebf7

Observation 0f2ea07e-1928-4f2a-945e-4c26f79f715b · outbound

This paper cites o m, K., G \.

Code Retrieval for MILP Instance Generation o m, K., G \

Reference 27

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raw_fallback, observed 2026-08-15T22:35:08.531952Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.660407Z digest=sha256:fb678a8af6854b820a6235a1327b9b74a6fc84f10038ec91b1493e0b07e16928

Observation e9b88416-511d-4547-ac9a-15c1ce1b1e62 · outbound

This paper cites M., Tian, Y., Dilkina, B., and Steiner, B.

Code Retrieval for MILP Instance Generation M., Tian, Y., Dilkina, B., and Steiner, B

Reference 28

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verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.515523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.666773Z digest=sha256:5883583cf6269ec0d3bc56fd15d8a1804b14ea6358f5c4a781a06486c6cb5fc0

Observation 0cc815d3-ebdc-4dab-a11a-fe312c6f325c · outbound

This paper cites GPT-4o System Card.

Code Retrieval for MILP Instance Generation GPT-4o System Card

Reference 29

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source=arxiv_source observed=2026-08-15T22:35:07.673125Z digest=sha256:461f32d5f91ae0def605450bdf88c30be3ae8eba1cfba6ca6dbf7d80ab464ae9

Observation 797bd7b5-8d68-491f-b0da-b6e8055ad609 · outbound

This paper cites and Pardalos, P.

Code Retrieval for MILP Instance Generation and Pardalos, P

Reference 30

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raw_fallback, observed 2026-08-15T22:35:08.498675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.679130Z digest=sha256:38814d2d9c56c5d78bbfa36915c6998d5711df37c4b669b1e5ff74a1dc58201c

Observation 66042b17-c52d-48b7-9406-8b7d1300ea59 · outbound

This paper cites an unresolved cited work.

Code Retrieval for MILP Instance Generation Unresolved cited work

Reference 31

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source=arxiv_source observed=2026-08-15T22:35:07.684325Z digest=sha256:a973648d950e49ae26292ed5864213917d6e32a5ddc52847684963f20ead1cfa

Observation 1be45a1a-0021-4bf6-a5b8-acb845a635da · outbound

This paper cites Accelerate Presolve in Large-Scale Linear Programming via Reinforcement Learning.

Code Retrieval for MILP Instance Generation Accelerate Presolve in Large-Scale Linear Programming via Reinforcement Learning

Reference 32

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no resolver link, observed 2026-08-15T22:35:07.689711Z

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source=arxiv_source observed=2026-08-15T22:35:07.689711Z digest=sha256:5db727425b40079d8c763e2a9e1428de10355fb6a0e5117f5f1b00ee7c0737f6

Observation c8197033-0ed1-405d-a80c-96f023e0c4a7 · outbound

This paper cites NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models.

Code Retrieval for MILP Instance Generation NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models

Reference 33

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no resolver link, observed 2026-08-15T22:35:07.695811Z

Source-reported events for the cited work

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source=arxiv_source observed=2026-08-15T22:35:07.695811Z digest=sha256:158abbeca614b4eff9208131c114465addfa7f47cdb292a5036f03997d63361a

Observation b87fb9be-377c-40ca-9270-8f3db3436e50 · outbound

This paper cites Towards a universal test suite for combinatorial auction algorithms.

Code Retrieval for MILP Instance Generation Towards a universal test suite for combinatorial auction algorithms

Reference 34

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source=arxiv_source observed=2026-08-15T22:35:07.702632Z digest=sha256:61b6b1cfbcf10ba132b87b8da626dc9800a83d41b957982a7b0787d294290207

Observation 981b0ca6-f777-4b56-baa7-16d53f932cc9 · outbound

This paper cites Towards Foundation Models for Mixed Integer Linear Programming.

Code Retrieval for MILP Instance Generation Towards Foundation Models for Mixed Integer Linear Programming

Reference 35

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no resolver link, observed 2026-08-15T22:35:07.707797Z

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source=arxiv_source observed=2026-08-15T22:35:07.707797Z digest=sha256:b1a8715edafbb044fd7d4ef7804b5a926766f302e7ceeea955cad7cf1ef03257

Observation 8b0e19f9-8742-4e5e-812e-38985a5d5e89 · outbound

This paper cites Machine Learning Insides OptVerse AI Solver: Design Principles and Applications.

Code Retrieval for MILP Instance Generation Machine Learning Insides OptVerse AI Solver: Design Principles and Applications

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:35:07.713319Z digest=sha256:aa0dd731f16a194e92da2799b61e5d6a96551cec65f5bc7f9ac2ddf1931efce3

Observation cfe29235-8100-48cf-b5ec-0740f5c9f5e6 · outbound

This paper cites Divergence measures based on the shannon entropy.

Code Retrieval for MILP Instance Generation Divergence measures based on the shannon entropy

Reference 37

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verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.458319Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.718756Z digest=sha256:ab5049f217ae774bce74e5558f9ca4d97dc91a904b47ae5be4db4054d5aa2955

Observation 7a61ec41-e190-4c68-8a7e-2389ef8f19a2 · outbound

This paper cites L2p-mip: Learning to presolve for mixed integer programming.

Code Retrieval for MILP Instance Generation L2p-mip: Learning to presolve for mixed integer programming

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.438649Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.723961Z digest=sha256:d8a92f19f5fa0d1cd1878b344f0bf76ad1e5ed33dc07944a050eab5ea4ec2e2c

Observation d899f980-5186-4160-8361-8b49c4d929c0 · outbound

This paper cites MILP-StuDio: MILP Instance Generation via Block Structure Decomposition.

Code Retrieval for MILP Instance Generation MILP-StuDio: MILP Instance Generation via Block Structure Decomposition

Reference 39

Resolution
verified exact
local_arxiv, observed 2026-08-15T22:35:07.954658Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.728896Z digest=sha256:48432352b2f8f4c36320e9b798cce874016c92d1c4f3cc9c58217fbce8f63199

Observation e83406dd-05ec-4fea-9d25-55f42d4fca26 · outbound

This paper cites P., and Mittal, M.

Code Retrieval for MILP Instance Generation P., and Mittal, M

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.420611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.734305Z digest=sha256:4dac77bddef48593fb9f48b7498005eed4e01f5053e2d16c994fdef6f1f87300

Observation 304ce957-cc8b-4474-af6f-c9528ee9d39d · outbound

This paper cites M., and Ramos, A.

Code Retrieval for MILP Instance Generation M., and Ramos, A

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.402189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.739114Z digest=sha256:74287b3d1c067cf2ab710322bc8009771fcc12661d35060210a166181f01c3d1

Observation 8b956cf6-b168-4c43-b79a-1c58f3a6e7ab · outbound

This paper cites G., and Manzolini, G.

Code Retrieval for MILP Instance Generation G., and Manzolini, G

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.382892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.744120Z digest=sha256:ec1dce9c6d2bd3fa613f146d9a26d15b526bc8e84692278348907463ba1822c1

Observation 237c4c5f-6bdf-4172-802a-637195dd321c · outbound

This paper cites An exact algorithm for large multiple knapsack problems.

Code Retrieval for MILP Instance Generation An exact algorithm for large multiple knapsack problems

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.365102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.749404Z digest=sha256:fb72420facd2be1cec18249056008b7df505f8d5027214bb5fb6e02d1d54d7cc

Observation d3f09c37-2631-481a-83c3-49a264285795 · outbound

This paper cites W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al.

Code Retrieval for MILP Instance Generation W., Hallacy, C., Ramesh, A., Goh, G., Agarwal, S., Sastry, G., Askell, A., Mishkin, P., Clark, J., et al

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-15T22:35:07.754638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:35:07.754638Z digest=sha256:1946a692aaa1e88a4740278ab61507778d9c8acd894a7616f8dfe99078e84893

Observation 20d33f90-73b4-4663-8c85-3563e5976ed4 · outbound

This paper cites and Pinto, J.

Code Retrieval for MILP Instance Generation and Pinto, J

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.335702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.760130Z digest=sha256:12c6414bea8568c9a7cbb7b01e7869eb636caa416ea320e10c957009cf3ad0ce

Observation d3ee7c02-c372-4ea8-a8e0-d947ce2b8159 · outbound

This paper cites and Gao, W.

Code Retrieval for MILP Instance Generation and Gao, W

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.315928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.767421Z digest=sha256:f6c6c8ab5fd61773da7dd4b536d7bb8c4aa5b9bc26b9c9079766bed24d7bb000

Observation daa244bf-030f-4102-ac9c-fc7428005afe · outbound

This paper cites Improved techniques for training gans.

Code Retrieval for MILP Instance Generation Improved techniques for training gans

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-15T22:35:07.779503Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:35:07.779503Z digest=sha256:259f6a1a5e10d43f35272b8f9792da90a6f63e5d18b0f0ea826d1f03ab4944f6

Observation e21f74d3-c337-4cfc-9ab2-61b5b947f33d · outbound

This paper cites and Bowly, S.

Code Retrieval for MILP Instance Generation and Bowly, S

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.286197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.785993Z digest=sha256:ccabe8e0739375a18a7010a7a2b2ef48badab087a15213252a1d73d2c83b2411

Observation 328e0614-5721-44b9-a763-0a98732e243c · outbound

This paper cites D., Park, K., and Kim, J.

Code Retrieval for MILP Instance Generation D., Park, K., and Kim, J

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.267693Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.791529Z digest=sha256:dba1715590857d2591d3d14c097d0b63b8c9920ed97e6087010c52611aeab125

Observation 90156ab0-dd15-4c1d-99ce-180a185f5ba4 · outbound

This paper cites Learning a Large Neighborhood Search Algorithm for Mixed Integer Programs.

Code Retrieval for MILP Instance Generation Learning a Large Neighborhood Search Algorithm for Mixed Integer Programs

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-15T22:35:07.798230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:35:07.798230Z digest=sha256:6d5083db1fea45363936f21b9d570c7da68a8d77eaa46a0fec300921e254240a

Observation a8116c7e-1f88-4e1c-a3e3-d03cab64f961 · outbound

This paper cites Rethinking the inception architecture for computer vision.

Code Retrieval for MILP Instance Generation Rethinking the inception architecture for computer vision

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-15T22:35:07.805067Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:35:07.805067Z digest=sha256:de3e170817c711eaad59b91d73ebc9103842fd4f71ece381c68cd9d23a858a81

Observation 187803fd-459f-432f-89bb-956aa1c88ccd · outbound

This paper cites Reinforcement learning for integer programming: Learning to cut.

Code Retrieval for MILP Instance Generation Reinforcement learning for integer programming: Learning to cut

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.234458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.811990Z digest=sha256:dbd2fe182357e2c97e105be5b5b9ddcd44816db73c509aed569613131dcdbf85

Observation 2a3fb72f-ffa5-447d-bf1c-107b61c50f23 · outbound

This paper cites P., Liu, J., Chen, X., Wang, X., Li, P., and Yin, W.

Code Retrieval for MILP Instance Generation P., Liu, J., Chen, X., Wang, X., Li, P., and Yin, W

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.215507Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.817912Z digest=sha256:87f436064f1d32456d51ca31f8dff1a98b71e3ec612b62d95320749dfa690f44

Observation 58a0ca64-08a6-4248-99f8-e5a9e50f3f7a · outbound

This paper cites Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model.

Code Retrieval for MILP Instance Generation Learning Cut Selection for Mixed-Integer Linear Programming via Hierarchical Sequence Model

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-15T22:35:07.823890Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T22:35:07.823890Z digest=sha256:b485c55f28c6a7b007ed2a1fd9dc581a618bb004b41a1f867c4da85e1c5611a8

Observation 48deafaa-5c1f-4085-99d9-c917433360ec · outbound

This paper cites Learning to generate scalable milp instances.

Code Retrieval for MILP Instance Generation Learning to generate scalable milp instances

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.196226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.830150Z digest=sha256:b479ef637858cb1c26efa1d2bf88ad0fc63791aaf4e2a1c583b774f0340e70bb

Observation 613cc0f5-eaf2-4bdd-b45f-3b82716f0a36 · outbound

This paper cites Gnn&gbdt-guided fast optimizing framework for large-scale integer programming.

Code Retrieval for MILP Instance Generation Gnn&gbdt-guided fast optimizing framework for large-scale integer programming

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.175201Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.836083Z digest=sha256:1a532c8a1a83aa04a829e2224ba62bd66d6019f185ea80ac5410386679e36c6b

Observation b115db3b-33f3-4eee-b0ff-1a40ac3223e2 · outbound

This paper cites Light- MILP opt: Solving large-scale mixed integer linear programs with lightweight optimizer and small-scale training dataset.

Code Retrieval for MILP Instance Generation Light- MILP opt: Solving large-scale mixed integer linear programs with lightweight optimizer and small-scale training dataset

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.155047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.842974Z digest=sha256:069c2b0ec1e3a392f0dbeeeb27a5186e55571c9ad81932b8b7e9b09f24fe5b6e

Observation c84494e9-f2b9-4ff5-a5e0-d05f4dd351e5 · outbound

This paper cites Milp-fbgen: Lp/milp instance generation with feasibility/boundedness.

Code Retrieval for MILP Instance Generation Milp-fbgen: Lp/milp instance generation with feasibility/boundedness

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T22:35:08.136115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

source=arxiv_source observed=2026-08-15T22:35:07.849672Z digest=sha256:e7e08b78e3d00c8bc369df40065902eade5fa75093515eaac2218f9ddf619da0

Pith citing papers

No inbound Pith citation observations are available.