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Paper Citation Record · LEDGER

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence

As of 13 August 2026, this Paper Citation Record lists 100 of 128 outbound references and 1 inbound Pith citation observation for arXiv:2412.07138.

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

pith.paper-citation-record.v1
2412.07138 v1

Coverage vector

measured 100 of 128 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T19:10:52.503291Z

measured 101 of 101 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-14T19:59:13.378797Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-05-14T19:59:25.750285Z

Reference resolution

100 of 128 outbound references displayed

  • verified exact2
  • verified fuzzy33
  • unresolved65
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bbee5fce-7468-4416-9b87-8f38a6b409c7 · outbound

This paper cites A gradient method for multilevel optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A gradient method for multilevel optimization

Reference 1

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source=pdf_text observed=2026-08-11T19:10:52.057373Z digest=sha256:b9f5558ac1e6142bd2ea0437a3ef78bbb17a7c850821ac4f1b259cf2e2c9ca1d

Observation c00e5244-d635-4548-a8fc-5726275abfca · outbound

This paper cites Betty: An automatic differentiation library for multilevel optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Betty: An automatic differentiation library for multilevel optimization

Reference 2

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source=pdf_text observed=2026-08-11T19:10:52.062428Z digest=sha256:72eb2a43484198f4c57617e4e30cf186beb979f574a925e27393711f124d2960

Observation ea94778a-ca84-45cd-be47-9e4927ae9ff7 · outbound

This paper cites When nas meets robustness: In search of robust architectures against adversarial attacks.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence When nas meets robustness: In search of robust architectures against adversarial attacks

Reference 3

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source=pdf_text observed=2026-08-11T19:10:52.067200Z digest=sha256:b67a7dd3c51a355aca50e014785be0351ca48f3191e1552ed07d4fc7ce335b9f

Observation 44bec79c-cfa4-4a73-9f7f-8a986b14925a · outbound

This paper cites Provably convergent federated trilevel learning.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Provably convergent federated trilevel learning

Reference 4

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source=pdf_text observed=2026-08-11T19:10:52.072827Z digest=sha256:08ef6cd674a10f367a303b4b865e6f99a6a6950b76e54028559e620273a912a7

Observation e02f707d-e95d-4406-97c0-ec0be7067864 · outbound

This paper cites The computational complexity of multi-level linear programs.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence The computational complexity of multi-level linear programs

Reference 5

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source=pdf_text observed=2026-08-11T19:10:52.077561Z digest=sha256:2923111505e8301461215b3ad36f2cce0840a8e3b794c89292545652c3af9518

Observation 9bd0eb9f-3c72-4e70-8d3b-63e7b0e02c2b · outbound

This paper cites Mixed-integer multi-level optimization through multi-parametric programming.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Mixed-integer multi-level optimization through multi-parametric programming

Reference 6

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source=pdf_text observed=2026-08-11T19:10:52.081963Z digest=sha256:fe1150046fc54eba0fa81384cdc127cdf4718b04e23ada6672f407d01fa31108

Observation 2323e23f-dd77-4a9a-80f1-b471d1356784 · outbound

This paper cites Computational difficulties of bilevel linear programming.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Computational difficulties of bilevel linear programming

Reference 7

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source=pdf_text observed=2026-08-11T19:10:52.087722Z digest=sha256:2c1c0ff5708163349b445aac304623ae11d7c64de76db5c250f404f0074b2ba4

Observation 21e12519-d2db-45a4-b61a-c05603a6a5ca · outbound

This paper cites A review on bilevel optimization: From classical to evolutionary approaches and applications.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A review on bilevel optimization: From classical to evolutionary approaches and applications

Reference 8

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source=pdf_text observed=2026-08-11T19:10:52.092031Z digest=sha256:aa82ea20f6521a3f9e31c5c6c3fc43d2abe75f9415367799143a75ed65bd0e16

Observation d3aac9b0-70e6-400d-ac6b-98ee89e04323 · outbound

This paper cites Communication-efficient stochastic zeroth-order optimization for federated learning.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Communication-efficient stochastic zeroth-order optimization for federated learning

Reference 9

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source=pdf_text observed=2026-08-11T19:10:52.096294Z digest=sha256:5496591b68af97e860e7eebeb398e5ead055aa428c5024410b7307fdcdf0b520

Observation aaed98d5-2416-40a3-ac95-55b10b922d1e · outbound

This paper cites Zeroth-order methods for nondifferentiable, nonconvex, and hierarchical federated optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Zeroth-order methods for nondifferentiable, nonconvex, and hierarchical federated optimization

Reference 10

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source=pdf_text observed=2026-08-11T19:10:52.100453Z digest=sha256:1192da28b3d16a776ca5e4a7779eadca6faccfa6e4259179a9bfa4d48e1a72fd

Observation 0797b59c-bf96-461d-8da5-2c81f2b7abea · outbound

This paper cites Zeroth-order stochastic variance reduction for nonconvex optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Zeroth-order stochastic variance reduction for nonconvex optimization

Reference 11

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source=pdf_text observed=2026-08-11T19:10:52.104983Z digest=sha256:84f439709c052fd4633b544aafdf01f3298a4723a8f0d68ee690df6e9cf3b959

Observation e65c27a2-d1c0-42ee-a930-48b211f89513 · outbound

This paper cites Zo-adamm: Zeroth-order adaptive momentum method for black-box optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Zo-adamm: Zeroth-order adaptive momentum method for black-box optimization

Reference 12

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source=pdf_text observed=2026-08-11T19:10:52.109246Z digest=sha256:347413024913337771f89a15da04da911cae139085d0dabe987b631406e76693

Observation 69496f40-972f-4d9c-af02-94ddbd6e7c7e · outbound

This paper cites Stochastic zeroth-order optimization in high dimensions.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Stochastic zeroth-order optimization in high dimensions

Reference 13

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source=pdf_text observed=2026-08-11T19:10:52.113549Z digest=sha256:5a6416a42fe0d122ef91410ffd450e7f0b2386ae4457a65dcf26b8202dfe256e

Observation 6f37f70c-4aeb-49be-bd2b-3463cb69c409 · outbound

This paper cites Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Zoo: Zeroth order optimization based black-box attacks to deep neural networks without training substitute models

Reference 14

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source=pdf_text observed=2026-08-11T19:10:52.118259Z digest=sha256:e0a415e315d28d564e44b6cfce637d201e69fba7ce69502c84cc6591b5965363

Observation 5cb6a5bd-0392-404d-bcaa-08b9d3fa5d6d · outbound

This paper cites Zeroth-order non-convex learning via hierarchical dual averaging.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Zeroth-order non-convex learning via hierarchical dual averaging

Reference 15

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source=pdf_text observed=2026-08-11T19:10:52.122992Z digest=sha256:ef2ec8dd791a734089ed62f08217dbcd0caee745dd663d54f33b2e7ffadcd1b1

Observation 3df3d950-1148-42b3-bed4-6b84d26d1cbf · outbound

This paper cites A zeroth-order block coordinate descent algorithm for huge-scale black-box optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A zeroth-order block coordinate descent algorithm for huge-scale black-box optimization

Reference 16

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source=pdf_text observed=2026-08-11T19:10:52.127353Z digest=sha256:5e0eef1e8d437a34760ce6ac730e6dfee3b868aea5f43b0a945f3de0c464334f

Observation a0c4fb39-eabf-4b0b-a3a7-79328df7526a · outbound

This paper cites Can stochastic zeroth-order frank-wolfe method converge faster for non- convex problems? In International conference on machine learning, pages 3377–3386.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Can stochastic zeroth-order frank-wolfe method converge faster for non- convex problems? In International conference on machine learning, pages 3377–3386

Reference 17

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source=pdf_text observed=2026-08-11T19:10:52.131384Z digest=sha256:7e3cc6a878fc619276db95d591862229bb08db2a7e6e155114871d0d0a8e0cd8

Observation 3e4147d7-9bfe-440d-9018-b74b5754ae94 · outbound

This paper cites Zeroth-order optimization with weak dimension dependency.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Zeroth-order optimization with weak dimension dependency

Reference 18

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source=pdf_text observed=2026-08-11T19:10:52.135440Z digest=sha256:c9b3c4eebd1001a0d53892cda1b1c29fffaa9745f8a6e06352562b209196a589

Observation 70cfb9f5-96c8-4331-93eb-e2a23b62218e · outbound

This paper cites Zeroth-order optimization for composite problems with functional constraints.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Zeroth-order optimization for composite problems with functional constraints

Reference 19

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source=pdf_text observed=2026-08-11T19:10:52.140622Z digest=sha256:1525f15978df8e3fabf2989efce3bb61afe74190851e1e168efa459dc31ac19e

Observation 92fe52e3-08e9-4e97-9b16-0d745066ce18 · outbound

This paper cites Escaping saddle points in zeroth-order optimization: the power of two-point estimators.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Escaping saddle points in zeroth-order optimization: the power of two-point estimators

Reference 20

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source=pdf_text observed=2026-08-11T19:10:52.145167Z digest=sha256:00bb7210b371b8d95353133a1088066e2725798cec8984574bee46036e5a9f8b

Observation 9978564d-9e4c-4294-af88-fc8c253f60c5 · outbound

This paper cites Black-box generalization: Stability of zeroth-order learning.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Black-box generalization: Stability of zeroth-order learning

Reference 21

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source=pdf_text observed=2026-08-11T19:10:52.149627Z digest=sha256:d0c872d226450a022d59571178fb78a3ef9cddd1fe9fa70019332bf721093c5d

Observation 72f4ef16-2c27-4526-a830-1248349d9444 · outbound

This paper cites Autozoom: Autoencoder-based zeroth order optimization method for attacking black-box neural networks.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Autozoom: Autoencoder-based zeroth order optimization method for attacking black-box neural networks

Reference 22

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source=pdf_text observed=2026-08-11T19:10:52.154030Z digest=sha256:915a7ef3d4bdc1ae130cfb7cfe9a5694aa17dd73036e165350efba70fb7c68c6

Observation 1a3d4ad7-02d0-4022-98e7-59b3d8363552 · outbound

This paper cites An optimal structured zeroth-order algorithm for non-smooth optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence An optimal structured zeroth-order algorithm for non-smooth optimization

Reference 23

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source=pdf_text observed=2026-08-11T19:10:52.159099Z digest=sha256:625ee12c56595672de70c3934f485dd106b36fce75467704b78f349fbb8cd672

Observation abf68641-472c-462b-a50e-b43c32a133bb · outbound

This paper cites A comprehensive linear speedup analysis for asynchronous stochastic parallel optimization from zeroth-order to first-order.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A comprehensive linear speedup analysis for asynchronous stochastic parallel optimization from zeroth-order to first-order

Reference 24

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source=pdf_text observed=2026-08-11T19:10:52.163299Z digest=sha256:98814de2b25bb60875af7fc8da8ceb93329b990a2b3c7dbe771805cc8eda28d3

Observation f91421a6-f218-4959-93c5-c8506adfbd74 · outbound

This paper cites Distributed zero-order algorithms for nonconvex multiagent optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Distributed zero-order algorithms for nonconvex multiagent optimization

Reference 25

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Observation 446b5999-efc0-41ce-b0eb-6e8a5785d540 · outbound

This paper cites Fine-grained theoretical analysis of federated zeroth-order optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Fine-grained theoretical analysis of federated zeroth-order optimization

Reference 26

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Observation 64503779-c951-4cb1-ac93-5d253820122f · outbound

This paper cites Distributed zero-order optimization under adversarial noise.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Distributed zero-order optimization under adversarial noise

Reference 27

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source=pdf_text observed=2026-08-11T19:10:52.177894Z digest=sha256:ed95d2f3b384a669e92e687bb29ec2500e810c5ab5c1cd023d01611d660451f0

Observation 6a12aaa5-b3a5-4fa3-8388-f9b5438c48c2 · outbound

This paper cites Distributed zeroth order optimization over random networks: A kiefer-wolfowitz stochastic approximation approach.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Distributed zeroth order optimization over random networks: A kiefer-wolfowitz stochastic approximation approach

Reference 28

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source=pdf_text observed=2026-08-11T19:10:52.182962Z digest=sha256:0f906c9ecf3317da806407703058278b68c8ae76dcdd4b4f8b29b258bfc73e76

Observation 9d4b63d6-dbd8-4462-af00-66909956b8df · outbound

This paper cites Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Federated Zeroth-Order Optimization using Trajectory-Informed Surrogate Gradients

Reference 29

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source=pdf_text observed=2026-08-11T19:10:52.187737Z digest=sha256:a7bd7971cb12ec5d0d8a7c5450a8b24df09a911ea596e882cfe3ae4e550d8cea

Observation 0a3c804c-67ca-4d5e-8c8c-45228f08cb64 · outbound

This paper cites Meta- learning to improve pre-training.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Meta- learning to improve pre-training

Reference 30

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source=pdf_text observed=2026-08-11T19:10:52.192688Z digest=sha256:e442f372699b05a243af60759be9ca33614b41b679a9e76a8efd6eeaf57b6e69

Observation 0a014541-804f-4f6b-bf03-b1035af1edd3 · outbound

This paper cites Learning from mistakes–a framework for neural architecture search.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Learning from mistakes–a framework for neural architecture search

Reference 31

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source=pdf_text observed=2026-08-11T19:10:52.197646Z digest=sha256:9aa471828d0b83b44b962755628a9a8dc15fd5b32e54a1d6d6e9e7727b8e4863

Observation 2250685b-598d-4eb9-8f24-9b32b59f65fd · outbound

This paper cites Convex optimization algorithms.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Convex optimization algorithms

Reference 32

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Observation 1fc6e1c8-babe-44c1-8774-fbebf7de2c08 · outbound

This paper cites Cutting plane methods in machine learning.Optimization for Machine Learning, pages 185–218, 2011.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Cutting plane methods in machine learning.Optimization for Machine Learning, pages 185–218, 2011

Reference 33

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Observation 2d36a900-66c5-42dc-917d-4080c0724fb8 · outbound

This paper cites Distributed robust optimization (DRO), part I: Framework and example.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Distributed robust optimization (DRO), part I: Framework and example

Reference 34

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source=pdf_text observed=2026-08-11T19:10:52.212487Z digest=sha256:4c742b8afba8428223254d58820f1b01b906c7bb40dbe6bb39042438c47e64fa

Observation 177ca8c8-2f8f-4a6b-b670-9b2d30b7ed71 · outbound

This paper cites A polyhedral approximation framework for convex and robust distributed optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A polyhedral approximation framework for convex and robust distributed optimization

Reference 35

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source=pdf_text observed=2026-08-11T19:10:52.217523Z digest=sha256:b81511165983dbb96e4dfd41ee30642d38f2508d91964b878494ea6d11a10a9e

Observation a6c51704-b625-47a7-bda5-0e515ec0d69f · outbound

This paper cites Asynchronous distributed bilevel optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Asynchronous distributed bilevel optimization

Reference 36

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source=pdf_text observed=2026-08-11T19:10:52.222049Z digest=sha256:a9c2ffcd1114cf9f4b6cbc69bf2ee1b44ddf973252a108c9924833f1dac87905

Observation 35945458-1ca9-4449-a0d0-f08fba5c52e4 · outbound

This paper cites Robust beamforming for downlink multi-cell systems: A bilevel optimization perspective.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Robust beamforming for downlink multi-cell systems: A bilevel optimization perspective

Reference 37

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source=pdf_text observed=2026-08-11T19:10:52.226485Z digest=sha256:c8a485754b53a4e593c3142c5057718f24ee097cb97ade1497cb2ac8cb515f5c

Observation 43fde2c8-8d8e-430f-afdc-df3c5bd08e70 · outbound

This paper cites Centralized and federated learning for predictive vnf autoscaling in multi-domain 5g networks and beyond.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Centralized and federated learning for predictive vnf autoscaling in multi-domain 5g networks and beyond

Reference 38

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source=pdf_text observed=2026-08-11T19:10:52.230865Z digest=sha256:5fd33fc8387a16293409fc64ac77f100fbf3e4031640a215753b1175873ddf14

Observation 1a4eb86a-9415-43e1-ae33-8bbb6c413d8f · outbound

This paper cites Advances in asynchronous parallel and distributed optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Advances in asynchronous parallel and distributed optimization

Reference 39

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source=pdf_text observed=2026-08-11T19:10:52.235122Z digest=sha256:14f3327c2004f6adf34d45b46bf86f0d7e0e84b0c2b529138188309360090c88

Observation a2839503-0acf-4e0a-b55d-8f2763514b04 · outbound

This paper cites ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence ScaleBiO: Scalable Bilevel Optimization for LLM Data Reweighting

Reference 40

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source=pdf_text observed=2026-08-11T19:10:52.240086Z digest=sha256:defdf687e6e489d71fc71d4c9dc2e0af2a8254778f3a99706d1ad554cc184587

Observation 3fb56f0b-d90b-4fcc-aee2-fd306626a22c · outbound

This paper cites A fully first-order method for stochastic bilevel optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A fully first-order method for stochastic bilevel optimization

Reference 41

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source=pdf_text observed=2026-08-11T19:10:52.245107Z digest=sha256:2dc3a079cd4860113a5c8ae04a8ef9e9e3bd3fca0991679e791f28482ccfa234

Observation befdbec5-229b-4aa4-9d93-91c3cda78df9 · outbound

This paper cites A conditional gradient- based method for simple bilevel optimization with convex lower-level problem.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A conditional gradient- based method for simple bilevel optimization with convex lower-level problem

Reference 42

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source=pdf_text observed=2026-08-11T19:10:52.249313Z digest=sha256:4ab9aa6b8aa3080c1609d1c50754900f81276556ab3b76dbcc15d40f2878650e

Observation a34d5197-1eb8-43e7-bd28-1cf447dc4cf1 · outbound

This paper cites Darts: Differentiable architecture search.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Darts: Differentiable architecture search

Reference 43

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source=pdf_text observed=2026-08-11T19:10:52.253800Z digest=sha256:07fcc822d5256bb1c43fa9d99742771c1b6733d835ac3320e4151dcf1cbea53a

Observation c76eeb77-ee35-4b5e-b907-fae673b6dd58 · outbound

This paper cites A general stochastic approach to solving problems with hard and soft constraints.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A general stochastic approach to solving problems with hard and soft constraints

Reference 44

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source=pdf_text observed=2026-08-11T19:10:52.258011Z digest=sha256:7ad9194961716688499bd6d8900737db6f4350a0f4b44e80072eb636c9516ae5

Observation 5e75c618-5750-4f87-b3f7-37ab56dcfeef · outbound

This paper cites An algorithm with optimal dimension-dependence for zero-order nonsmooth nonconvex stochastic optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence An algorithm with optimal dimension-dependence for zero-order nonsmooth nonconvex stochastic optimization

Reference 45

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source=pdf_text observed=2026-08-11T19:10:52.262159Z digest=sha256:7f2d7d00976c5806c3f11eacf34786fb5510cf59075002462d5226e92fbed77e

Observation 10e48051-f924-46b6-b842-264595a2ccc2 · outbound

This paper cites Stochastic first-and zeroth-order methods for nonconvex stochastic program- ming.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Stochastic first-and zeroth-order methods for nonconvex stochastic program- ming

Reference 46

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source=pdf_text observed=2026-08-11T19:10:52.266285Z digest=sha256:c7415b94615f6b692ec0cc56cf6e167abbddecfc987e30d8562d8b1bee79a670

Observation 2854534e-0f42-4680-82a1-34c88f10a155 · outbound

This paper cites On Penalty-based Bilevel Gradient Descent Method.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence On Penalty-based Bilevel Gradient Descent Method

Reference 47

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source=pdf_text observed=2026-08-11T19:10:52.270404Z digest=sha256:e4bdc9e63d48e56771f5b36c4a756e91e73239ac7129403e64b784a5f3bb2551

Observation add83a98-344e-49fe-b7a1-9daf9de9dda8 · outbound

This paper cites Improved penalty method via doubly stochastic gradients for bilevel hyperparameter optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Improved penalty method via doubly stochastic gradients for bilevel hyperparameter optimization

Reference 48

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source=pdf_text observed=2026-08-11T19:10:52.274861Z digest=sha256:11cbc8e8d21e18a91e638ddc2b738fed904eccd2c9714124f5768412b5a2a818

Observation 0b1642bf-c7d0-43ad-9b73-6df2e592da73 · outbound

This paper cites Convex optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Convex optimization

Reference 49

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source=pdf_text observed=2026-08-11T19:10:52.278973Z digest=sha256:6a39e7d5412c33b85beea1f728ffcd2c8adfa3f0576b4eb4d566cb606c6f0bc4

Observation 62feb05b-f170-438b-8319-15d70eb37edf · outbound

This paper cites A Unified Single-loop Alternating Gradient Projection Algorithm for Nonconvex-Concave and Convex-Nonconcave Minimax Problems.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A Unified Single-loop Alternating Gradient Projection Algorithm for Nonconvex-Concave and Convex-Nonconcave Minimax Problems

Reference 50

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source=pdf_text observed=2026-08-11T19:10:52.283877Z digest=sha256:47bbe732dae8fb24f0ff8af985e2d661d131f62bf9a83119b223a72f56b74bde

Observation 22240d80-2a64-4205-8bdc-329d1deaaa4d · outbound

This paper cites Complexities in projection-free stochastic non-convex minimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Complexities in projection-free stochastic non-convex minimization

Reference 51

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source=pdf_text observed=2026-08-11T19:10:52.288596Z digest=sha256:9d1d831de7d48464ce0d30a72eb9dcddb1156fade416f305d0ba0952e896452a

Observation bc1e3bb3-65aa-498a-8bb4-0aff7ccf6d01 · outbound

This paper cites Enhancing the resilience of llms against grey-box extractions.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Enhancing the resilience of llms against grey-box extractions

Reference 52

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source=pdf_text observed=2026-08-11T19:10:52.292730Z digest=sha256:589a5908e3f48cfb4e375ee2ff39233cfd6cd57f9d8f58a593f8769cdc9b5b5c

Observation e39f098e-59b8-431f-8503-18b321d2b920 · outbound

This paper cites Random gradient-free minimization of convex functions.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Random gradient-free minimization of convex functions

Reference 53

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source=pdf_text observed=2026-08-11T19:10:52.296823Z digest=sha256:754e58dd4819b3dc593eab6f36359801106b655fd6315bd92a40002d6e30b440

Observation c1240d61-38d7-42a6-ba24-6a97c5e965dd · outbound

This paper cites Accelerated zeroth-order method for non-smooth stochastic convex optimization problem with infinite variance.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Accelerated zeroth-order method for non-smooth stochastic convex optimization problem with infinite variance

Reference 54

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source=pdf_text observed=2026-08-11T19:10:52.301308Z digest=sha256:73811de2fa7d242bd5797025576f51efc57ff25fc3c6188abfbbb75087ebc41c

Observation 1f898507-b49d-4995-ba54-16912c1d3a99 · outbound

This paper cites Distributionally robust federated averaging.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Distributionally robust federated averaging

Reference 55

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T19:10:52.305408Z digest=sha256:01fc33ed9e55ed0dac545555ed0826f4cc44d7b199037debdf26cfc544122cc2

Observation 18db01f0-37ed-4feb-8bb1-18893a931826 · outbound

This paper cites Robust optimization over multiple domains.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Robust optimization over multiple domains

Reference 56

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

source=pdf_text observed=2026-08-11T19:10:52.309510Z digest=sha256:1a86e32ab7c13e484105c7d9bc3ca8bb34097baeabab2f79b28e6aefd436085e

Observation 7f1c78f3-fb9f-468e-8d7b-9c184a0bdda6 · outbound

This paper cites Stochastic composite mirror descent: Optimal bounds with high probabilities.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Stochastic composite mirror descent: Optimal bounds with high probabilities

Reference 57

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source=pdf_text observed=2026-08-11T19:10:52.313591Z digest=sha256:4e0440bc94b14c6bd6313cb50e644c7a91e3a3bf99bc3ceb3873de58c24b9877

Observation 97673eae-14ed-4c3e-82b7-4f87aa37961a · outbound

This paper cites Asynchronous stochastic gradient descent with delay compensation.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Asynchronous stochastic gradient descent with delay compensation

Reference 58

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source=pdf_text observed=2026-08-11T19:10:52.317674Z digest=sha256:342cba1e478c8ccce7915519ac70a29babf2cf55f4dcd869370df7895d1ed93c

Observation 0f07b1fa-770f-49c8-aa03-47cc462e6b4f · outbound

This paper cites Momentum-based variance reduction in non-convex sgd.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Momentum-based variance reduction in non-convex sgd

Reference 59

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source=pdf_text observed=2026-08-11T19:10:52.321987Z digest=sha256:309c5708d9522a03ef04082d82950a3451c0e29be0118a7353f3af024d25e677

Observation 46157436-cc4f-42f7-8731-722ed96dc2f9 · outbound

This paper cites Conflict-averse gradient descent for multi-task learning.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Conflict-averse gradient descent for multi-task learning

Reference 60

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source=pdf_text observed=2026-08-11T19:10:52.326077Z digest=sha256:58502893a829938cd4a112e9493b9092f1f1cdc4171900642227604eb8aee8c2

Observation f81eac78-1ed7-4fbf-813e-766f57c558c1 · outbound

This paper cites Truncated back-propagation for bilevel optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Truncated back-propagation for bilevel optimization

Reference 61

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-11T19:10:52.331046Z digest=sha256:05c641f5fe315f46551770796fba2330239659288b7517800f6d82002c1d6849

Observation 641843ad-7bd0-4a94-89bd-78df95454bb0 · outbound

This paper cites Decentralized stochastic bilevel optimization with improved per-iteration complexity.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Decentralized stochastic bilevel optimization with improved per-iteration complexity

Reference 62

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source=pdf_text observed=2026-08-11T19:10:52.335822Z digest=sha256:ac486e8a08195a88fcdeaf0c40987e5ab2cacac17a232084aeb8498f0935553d

Observation ff36d036-0dad-4aaa-a832-5c79754f81ed · outbound

This paper cites Non-convex bilevel optimization with time-varying objective functions.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Non-convex bilevel optimization with time-varying objective functions

Reference 63

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source=pdf_text observed=2026-08-11T19:10:52.340029Z digest=sha256:9ab3a031c2aba197fe7c2aa5ab206074844728e6a6efcc33927fcaa1a025cddf

Observation 0539c1b5-b516-43d6-87e0-6a49efc0e3e4 · outbound

This paper cites Revisiting zeroth-order optimization for memory-efficient llm fine-tuning: A benchmark.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Revisiting zeroth-order optimization for memory-efficient llm fine-tuning: A benchmark

Reference 64

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

source=pdf_text observed=2026-08-11T19:10:52.344844Z digest=sha256:8a49b2c6da60a1707f199d9882ed9f1d737c0263b66bb0d44fdad3984c17780e

Observation 60ffe417-3390-479f-9f70-79422fdadedb · outbound

This paper cites Subspace selection based prompt tuning with nonconvex nonsmooth black-box optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Subspace selection based prompt tuning with nonconvex nonsmooth black-box optimization

Reference 65

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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=2026-08-11T19:10:52.348926Z digest=sha256:efc8bd0386ecd3e90ff2ec2b49b55482719806ecb3af50fc83cdaaad53850075

Observation 40b136e8-984d-4954-88a7-9721feffdd23 · outbound

This paper cites Optimal rates for zero-order convex optimization: The power of two function evaluations.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Optimal rates for zero-order convex optimization: The power of two function evaluations

Reference 66

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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=2026-08-11T19:10:52.353171Z digest=sha256:114b1d215dc6fb1a07fa7dd600299ed4d9d966875e446d7bf97ce45ccd32ab0d

Observation 89d8bf18-8c08-4e4a-9ad8-7dde7f40117f · outbound

This paper cites Black-box tuning for language- model-as-a-service.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Black-box tuning for language- model-as-a-service

Reference 67

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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=2026-08-11T19:10:52.357549Z digest=sha256:8325723e8e6aa50ff31bb1cb7eafbb100efa6ffab004838bf40ef097d0cfe3b3

Observation b6312f70-8ccd-43d1-ae72-9be0442b6c14 · outbound

This paper cites Fairness-guided few-shot prompting for large language models.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Fairness-guided few-shot prompting for large language models

Reference 68

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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=2026-08-11T19:10:52.361763Z digest=sha256:3fa9a1126f01a166dc0b85a2bccb218aa9543809f3418a2d1a48d4a5fb650f23

Observation 163473f0-3ba3-4333-b45c-e8835ae0f464 · outbound

This paper cites Grammar prompting for domain-specific language generation with large language models.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Grammar prompting for domain-specific language generation with large language models

Reference 69

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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=2026-08-11T19:10:52.366148Z digest=sha256:5ff3bf515fbbb94cf4b8d50c59a24a36d51bef97c3e6ecdfc6c02c99dd07176a

Observation 565d5bd5-28c4-4e5b-9e01-a9ed8eace726 · outbound

This paper cites Black-box prompt learning for pre-trained language models.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Black-box prompt learning for pre-trained language models

Reference 70

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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=2026-08-11T19:10:52.370063Z digest=sha256:b5065bc0044965bc60e4f56b15a1c19e061863fb2b1714c53aebd10650eddd53

Observation f2fdcbe9-ae00-497b-8a61-50c2cc82b891 · outbound

This paper cites Poisonprompt: Backdoor attack on prompt-based large language models.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Poisonprompt: Backdoor attack on prompt-based large language models

Reference 71

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source=pdf_text observed=2026-08-11T19:10:52.374209Z digest=sha256:584c452c7fa68e13c824569d12846bb79152b1013ea810646af92307f19e4243

Observation 8e08e1c3-bf9a-418f-b90b-967c268911cb · outbound

This paper cites Qwen Technical Report.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Qwen Technical Report

Reference 72

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source=pdf_text observed=2026-08-11T19:10:52.378394Z digest=sha256:c4f9737b705aad992a8eaa7dec203e8381386e914bc4ddc1a56f475e66c2a8f5

Observation 8e42a5d5-b01f-45f4-931b-e6e3443dc5b3 · outbound

This paper cites Glue: A multi-task benchmark and analysis platform for natural language understanding.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Glue: A multi-task benchmark and analysis platform for natural language understanding

Reference 73

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source=pdf_text observed=2026-08-11T19:10:52.382930Z digest=sha256:786ef433552d9f3890c2d1cbc78aa8e5f558bdc6d692e003486d6ce5c2d37eaf

Observation c793e8bf-abd5-49bd-8eae-8139099fc72f · outbound

This paper cites Discriminative feature alignment: Improving transferability of unsupervised domain adaptation by gaussian-guided latent alignment.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Discriminative feature alignment: Improving transferability of unsupervised domain adaptation by gaussian-guided latent alignment

Reference 74

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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=2026-08-11T19:10:52.388180Z digest=sha256:495956c00f0a6217bcca572fb17c77d492d0cdbf4ffd214834786b89c3fa6d78

Observation df9a19a2-fd6c-4430-82bd-8a9ea6430753 · outbound

This paper cites Gradient-based learning applied to document recognition.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Gradient-based learning applied to document recognition

Reference 75

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source=pdf_text observed=2026-08-11T19:10:52.393825Z digest=sha256:dc7f7f6005356626798e5db83e042847b99117626dcc3d43068304357fd42217

Observation f27c5e95-fb1d-41d3-a8e3-73ee46f6ec6b · outbound

This paper cites Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Fashion-MNIST: a Novel Image Dataset for Benchmarking Machine Learning Algorithms

Reference 76

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:10:52.398123Z digest=sha256:848585348376be55db84b83717256cbf51634760da3a4d345d927d2934d4baef

Observation 20be34c0-2a01-4f4b-95bd-3a472c06acec · outbound

This paper cites Cold case: The lost mnist digits.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Cold case: The lost mnist digits

Reference 77

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raw_fallback, observed 2026-08-11T19:10:53.501228Z

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=2026-08-11T19:10:52.402572Z digest=sha256:fe151588ff90031e513b4e3ae5d73f958be7f6baaf201995b314ee95874f5c21

Observation 9b383205-7306-4fe3-998e-b6136a3c7027 · outbound

This paper cites A primer on zeroth-order optimization in signal processing and machine learning: Principals, recent advances, and applications.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A primer on zeroth-order optimization in signal processing and machine learning: Principals, recent advances, and applications

Reference 78

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raw_fallback, observed 2026-08-11T19:10:53.486108Z

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=2026-08-11T19:10:52.406893Z digest=sha256:5520ad6a5e1ac94ce4f12526f7ba90b356f1f7eaad18f2fd5b76f8ac98d62ff5

Observation fd34abbb-0c55-407c-95ea-83938f5d8bb4 · outbound

This paper cites Using hard constraints for representing soft constraints.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Using hard constraints for representing soft constraints

Reference 79

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raw_fallback, observed 2026-08-11T19:10:53.471639Z

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=2026-08-11T19:10:52.411579Z digest=sha256:60bae7618a64ba5885c050a21e7c72780ec5936c30457682f72c250c677f1d32

Observation a9ffa79d-36bc-4b0d-ba03-42208ffcab99 · outbound

This paper cites Combining hard and soft constraints in quantum constraint- satisfaction systems.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Combining hard and soft constraints in quantum constraint- satisfaction systems

Reference 80

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raw_fallback, observed 2026-08-11T19:10:53.456469Z

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=2026-08-11T19:10:52.416041Z digest=sha256:d4c22839a4e3d28fce6d7b89956a106ca46d7b7321ca5f817e5ff1ee8b6ccec4

Observation bffaaca4-b0f9-41c1-a97a-6454edd8a38b · outbound

This paper cites Bilevel optimization: Convergence analysis and enhanced design.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Bilevel optimization: Convergence analysis and enhanced design

Reference 81

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raw_fallback, observed 2026-08-11T19:10:53.440419Z

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=2026-08-11T19:10:52.420514Z digest=sha256:f12983cd1fc78a62ca2fafb8db595f77d94b1cfe1804f08e7fed55cee8d0c548

Observation 929f43d3-1f01-4207-942f-ee31d8fd0564 · outbound

This paper cites Model-agnostic meta-learning for fast adaptation of deep networks.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Model-agnostic meta-learning for fast adaptation of deep networks

Reference 82

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:10:52.425458Z digest=sha256:49c064d1d48d40aa7d8c28228eb1fc46bee1268e80a7e7b78ff2ca95e1d74dfd

Observation ee49a28b-9d09-44cb-bd7d-22a9aba75db9 · outbound

This paper cites Towards deep learning models resistant to adversarial attacks.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Towards deep learning models resistant to adversarial attacks

Reference 83

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:10:52.429948Z digest=sha256:eaa99af45ab0e59a3bdd1c9eb5eef78dd675b4c9f53a7d91adcb987be1b422a6

Observation 95d3da26-dc08-467d-87ee-b0303a81b7e9 · outbound

This paper cites Revisiting and advancing fast adversarial training through the lens of bi-level optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Revisiting and advancing fast adversarial training through the lens of bi-level optimization

Reference 84

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raw_fallback, observed 2026-08-11T19:10:53.405740Z

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=2026-08-11T19:10:52.434144Z digest=sha256:a4136e0869d4506d245bec7cd49df52cb1a3d23b6a4967caa4e179d142f15030

Observation a2c4bc43-5e3e-4583-a9a6-9958a21ef20e · outbound

This paper cites Distributed distributionally robust optimization with non-convex objectives.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Distributed distributionally robust optimization with non-convex objectives

Reference 85

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raw_fallback, observed 2026-08-11T19:10:53.389653Z

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=2026-08-11T19:10:52.438334Z digest=sha256:d84a2af81a67df6c7cc8d7feeeebcff0e304cd65ce756d31307f7cc752ba40a4

Observation 7f7c4393-204e-475c-9f45-81ce97965a42 · outbound

This paper cites Provably faster algorithms for bilevel optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Provably faster algorithms for bilevel optimization

Reference 86

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no resolver link, observed 2026-08-11T19:10:52.442411Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:10:52.442411Z digest=sha256:9aec3f382d6d03df1010a4509c27275f6a8b655ad2652ea19aa9ce73d4407536

Observation 20ae0d95-291b-4a4f-95e5-f4ea1d5fa2d5 · outbound

This paper cites Bilevel programming for hyperparameter optimization and meta-learning.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Bilevel programming for hyperparameter optimization and meta-learning

Reference 87

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source=pdf_text observed=2026-08-11T19:10:52.446552Z digest=sha256:1a1d969e7090860b92e7bb6f1f36de51a2e31b8164a08bb2bee3222d25e94595

Observation c821d092-9333-42a9-a1e5-8cb5db9c49a6 · outbound

This paper cites Investigating bi-level optimization for learning and vision from a unified perspective: A survey and beyond.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Investigating bi-level optimization for learning and vision from a unified perspective: A survey and beyond

Reference 88

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raw_fallback, observed 2026-08-11T19:10:53.355376Z

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=2026-08-11T19:10:52.450857Z digest=sha256:3d9ce6e0c4794dd3a6a65c8c28830746e87480bd11ac15f00085ae357e7edf75

Observation 695db97f-a203-40a6-8ffc-a272dd794531 · outbound

This paper cites Self-tuning networks: Bilevel optimization of hyperparameters using structured best-response functions.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Self-tuning networks: Bilevel optimization of hyperparameters using structured best-response functions

Reference 89

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raw_fallback, observed 2026-08-11T19:10:53.341215Z

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=2026-08-11T19:10:52.454917Z digest=sha256:0e7b3767422a181d1694cb708ffb776f2e71af8ea6e4bf64d7781c7f4fa6fc78

Observation d19c0783-471b-4231-b534-07080a5eedc6 · outbound

This paper cites Timeautoad: Autonomous anomaly detection with self- supervised contrastive loss for multivariate time series.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Timeautoad: Autonomous anomaly detection with self- supervised contrastive loss for multivariate time series

Reference 90

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raw_fallback, observed 2026-08-11T19:10:53.326892Z

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=2026-08-11T19:10:52.459252Z digest=sha256:896375d53b676002e247e735a30d66a4ad07f40ca5705a26d2b99b57972142c4

Observation 5d462cb2-b08a-466b-bab7-aed47192056a · outbound

This paper cites Fedal: Black-box federated knowledge distillation enabled by adversarial learning.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Fedal: Black-box federated knowledge distillation enabled by adversarial learning

Reference 91

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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=2026-08-11T19:10:52.463818Z digest=sha256:a1ae568a25039ab1afb4515dbf58d1526b0ca33fc7b89fe3ab63fed7bba3564c

Observation af6c0fdd-aec8-4e58-9b93-b740efb8bb90 · outbound

This paper cites Deep Learning for Classical Japanese Literature.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Deep Learning for Classical Japanese Literature

Reference 92

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T19:10:52.468158Z digest=sha256:c653e97786b1f55aef6235a32c176b5e801e6dfc79cd49f878aada045b0df040

Observation 93f8898e-a0da-4f3c-825a-21ed255b05b5 · outbound

This paper cites Adadelay: Delay adaptive distributed stochastic optimization.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Adadelay: Delay adaptive distributed stochastic optimization

Reference 93

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raw_fallback, observed 2026-08-11T19:10:53.298064Z

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=2026-08-11T19:10:52.473292Z digest=sha256:dfd61f0eb90eacdb1f60edf67c8842428040fcbaa9cbd2564c986a6f5046e6da

Observation 7f104d94-0a9f-4c5c-bbdc-a4cfe3227ba0 · outbound

This paper cites Distributed Zeroth-Order Stochastic Optimization in Time-varying Networks.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Distributed Zeroth-Order Stochastic Optimization in Time-varying Networks

Reference 94

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local_arxiv, observed 2026-08-11T19:10:52.705038Z

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=2026-08-11T19:10:52.477297Z digest=sha256:2463e7a8e268243b823ed41e10f759aa9edaca341bdc7a3de9762a5a302cdf06

Observation 4d092559-1342-47af-92a2-c12a229c6064 · outbound

This paper cites Projection- free methods for stochastic simple bilevel optimization with convex lower-level problem.Advances in Neural Information Processing Systems, 36, 2024.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Projection- free methods for stochastic simple bilevel optimization with convex lower-level problem.Advances in Neural Information Processing Systems, 36, 2024

Reference 95

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raw_fallback, observed 2026-08-11T19:10:53.285101Z

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=2026-08-11T19:10:52.481611Z digest=sha256:61ad35effaea9b85390eeb0acec776c4b746d4e9158cc52245b7d8baa26ddaef

Observation 3dfd6886-d1e4-4165-914c-af0a17e16e18 · outbound

This paper cites signsgd via zeroth-order oracle.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence signsgd via zeroth-order oracle

Reference 96

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raw_fallback, observed 2026-08-11T19:10:53.270791Z

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=2026-08-11T19:10:52.485604Z digest=sha256:3ab8941fa3957372cce53f2563b930942316a078ee102f88d6009c13f1e64c89

Observation 7135e7db-5192-4a1e-92d4-94721f80349d · outbound

This paper cites Bome! bilevel optimization made easy: A simple first-order approach.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Bome! bilevel optimization made easy: A simple first-order approach

Reference 97

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raw_fallback, observed 2026-08-11T19:10:53.256189Z

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=2026-08-11T19:10:52.489748Z digest=sha256:b65982f4b87d6ccfdc812e338ec6a85c00d6fe1b72c1893cdf0071edae2befaa

Observation 71cab522-8bd3-48ea-bba8-fef0cbd0b8b0 · outbound

This paper cites A novel chattering-free discrete sliding mode controller with disturbance compensation for zinc roasting temperature distribution control.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence A novel chattering-free discrete sliding mode controller with disturbance compensation for zinc roasting temperature distribution control

Reference 98

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raw_fallback, observed 2026-08-11T19:10:53.242224Z

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=2026-08-11T19:10:52.493857Z digest=sha256:ed6ac940ebf31bec66076c1d96113868fdf431f77ba588515dc6c7b69e2d0703

Observation 675f19e5-a81e-4273-ad0a-a68cab53892d · outbound

This paper cites Decentralized multi-level compositional optimization algorithms with level-independent convergence rate.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence Decentralized multi-level compositional optimization algorithms with level-independent convergence rate

Reference 99

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raw_fallback, observed 2026-08-11T19:10:53.226906Z

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=2026-08-11T19:10:52.498517Z digest=sha256:48061b8b4ebe1d9c3a9c97e0955f115a23536906140c7689c55864acddc62712

Observation f6e58254-7e82-4beb-a751-739a5f5d296a · outbound

This paper cites On the convergence of local stochastic compositional gradient descent with momentum.

Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence On the convergence of local stochastic compositional gradient descent with momentum

Reference 100

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raw_fallback, observed 2026-08-11T19:10:53.212223Z

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=2026-08-11T19:10:52.503291Z digest=sha256:55612484517ff1d86c9f6baa20fcc33cfdb895caef58d486f1d3dca883aa0cf4

Pith citing papers

Observation cf9f12a2-180c-477f-9633-25b649cb63b2 · inbound

CHAL: Council of Hierarchical Agentic Language cites this paper.

CHAL: Council of Hierarchical Agentic Language Unlocking TriLevel Learning with Level-Wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-Asymptotic Convergence

Reference 82

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arxiv_id, observed 2026-05-14T19:59:25.753484Z

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=2026-05-14T19:59:13.378797Z digest=sha256:b99514b8a26fce1bb3919ea5496d90bbc3a9e9cfe116d46e88254fd1d6c917b7