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Paper Citation Record · LEDGER

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency

As of 10 August 2026, this Paper Citation Record lists 92 of 92 outbound references and 2 inbound Pith citation observations for arXiv:2502.05028.

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

pith.paper-citation-record.v1
2502.05028 v1

Coverage vector

measured 92 of 92 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T20:42:39.055335Z

measured 94 of 94 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-02T21:46:55.043461Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T04:37:31.889336Z

Reference resolution

92 of 92 outbound references displayed

  • verified exact2
  • verified fuzzy67
  • unresolved23
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1ffd6084-83e9-4e2a-9084-a3369e19c9c9 · outbound

This paper cites write newline.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency write newline

Reference 1

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unresolved
no resolver link, observed 2026-08-08T20:42:38.767840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.767840Z digest=sha256:fd68505277a6e0290faba4f249a02a3f262b1025bdde2723511eed8935dc4873

Observation fd425a4a-04a1-4fd9-b8ae-ea2fae9231ca · outbound

This paper cites Finding approximate local minima faster than gradient descent.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Finding approximate local minima faster than gradient descent

Reference 2

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unresolved
no resolver link, observed 2026-08-08T20:42:38.772412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.772412Z digest=sha256:737ea93397a7bcf9ce78ab99b7ed077e35d6be1f20e2a356b800f50d7fa5b69a

Observation 8afee5fb-b6c2-446b-a0be-ccad8af1d488 · outbound

This paper cites New local search approximation techniques for maximum generalized satisfiability problems.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency New local search approximation techniques for maximum generalized satisfiability problems

Reference 3

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unresolved
no resolver link, observed 2026-08-08T20:42:38.775691Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.775691Z digest=sha256:ebfff80e878c39ba2574150566205da79ae22354b06913ea81fcf7be86f89e74

Observation b347439d-b1d9-4816-bc14-de8c5c90df95 · outbound

This paper cites Decentralized active information acquisition: Theory and application to multi-robot slam.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Decentralized active information acquisition: Theory and application to multi-robot slam

Reference 4

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unresolved
no resolver link, observed 2026-08-08T20:42:38.779186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.779186Z digest=sha256:328b7ddc02c7e7b58e7f48f80456b0b8b9c1577911b474429148eb0f1495b3a8

Observation b0e31e14-e587-47a7-ade5-56722d1c19bf · outbound

This paper cites Diverse client selection for federated learning via submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Diverse client selection for federated learning via submodular maximization

Reference 5

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unresolved
no resolver link, observed 2026-08-08T20:42:38.782581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.782581Z digest=sha256:32583790411611f6220fb5c60c0bc08c2053bcb279d9a7ad0a6da8becf72d969

Observation 85a91d2c-8e24-422f-af13-bdccc53ef75d · outbound

This paper cites Joint and separate convexity of the bregman distance.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Joint and separate convexity of the bregman distance

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-08T20:42:38.786073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.786073Z digest=sha256:f980047899a617d44a9ce857d6058588925b00e9e05056542d444c4bb8300c93

Observation 211ab686-ccf1-4d38-9c35-e57b3fd3f91e · outbound

This paper cites Guarantees for greedy maximization of non-submodular functions with applications.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Guarantees for greedy maximization of non-submodular functions with applications

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-08T20:42:38.789609Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.789609Z digest=sha256:9d873d65778f7a10c7226fb20f6a065200d32f3d8de43152e9d63d94b6fc3dd5

Observation 96b79496-8d8b-4867-a955-b5cb95356640 · outbound

This paper cites Guaranteed non-convex optimization: Submodular maximization over continuous domains.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Guaranteed non-convex optimization: Submodular maximization over continuous domains

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-08T20:42:38.793092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.793092Z digest=sha256:6754841b9c4ebd0fe486e4af7488b87464ab752eb8af4c9beff8239e18b38f10

Observation 735617f8-0527-41f1-a05f-e4ffe588bf87 · outbound

This paper cites Continuous Submodular Function Maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Continuous Submodular Function Maximization

Reference 9

Resolution
verified exact
local_arxiv, observed 2026-08-08T20:42:39.131506Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.796257Z digest=sha256:5276c2bc377689a335704561b22e62f6524312438ceef9a1ac287b96d04116bd

Observation a5d42909-6a14-450f-9129-9da80dbbac1d · outbound

This paper cites An o (n) algorithm for quadratic knapsack problems.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency An o (n) algorithm for quadratic knapsack problems

Reference 10

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unresolved
no resolver link, observed 2026-08-08T20:42:38.800072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.800072Z digest=sha256:1ee2c796f93e6fd0a420823b5fe12ac2e4a5b4604f5c8e3f9dddfc73d8ccf324

Observation 08bdf84b-4e0e-4a41-a396-f8192ae1ffe8 · outbound

This paper cites Maximizing a monotone submodular function subject to a matroid constraint.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Maximizing a monotone submodular function subject to a matroid constraint

Reference 11

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unresolved
no resolver link, observed 2026-08-08T20:42:38.803183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.803183Z digest=sha256:551c6ac43ef67378fe76e84422d76e701e963c3f067d271bc89667286ea82cc6

Observation e7616ff2-9492-4119-bbdf-347547b834d8 · outbound

This paper cites Submodular function maximization via the multilinear relaxation and contention resolution schemes.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Submodular function maximization via the multilinear relaxation and contention resolution schemes

Reference 12

Resolution
unresolved
no resolver link, observed 2026-08-08T20:42:38.806560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.806560Z digest=sha256:f57880cf8dc20fd52d779f428001086c8bc4709a4ca540ba5f78db8931517209

Observation 1e9f560a-aa89-4edb-8f0e-e5dfe34b589a · outbound

This paper cites Convergence analysis of a proximal-like minimization algorithm using bregman functions.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Convergence analysis of a proximal-like minimization algorithm using bregman functions

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-08T20:42:38.809851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.809851Z digest=sha256:a3247f7e85526e3c5a5d07002f1a4bcf27b7a841bfac7cc69bb6dd19442fba8f

Observation 56610edd-6f0c-4a33-bc28-5603509efba6 · outbound

This paper cites Online continuous submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Online continuous submodular maximization

Reference 14

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verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.821388Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.812818Z digest=sha256:8f07298b6e17e567d4985aec4cb65fa4fd875332521a45fe09b31c472597b1ba

Observation 91f28cb1-a94e-41e7-811f-f617e784076e · outbound

This paper cites Submodular set functions, matroids and the greedy algorithm: tight worst-case bounds and some generalizations of the rado-edmonds theorem.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Submodular set functions, matroids and the greedy algorithm: tight worst-case bounds and some generalizations of the rado-edmonds theorem

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.811958Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.816041Z digest=sha256:b8dab405d3897bb12b77b0f80422fd8dde72a89b6943e3f50c0b9ae125a0f39a

Observation b54dc5ee-2cbd-4aaf-b4f4-4453d021a780 · outbound

This paper cites Scalable distributed planning for multi-robot, multi-target tracking.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Scalable distributed planning for multi-robot, multi-target tracking

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.801841Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.819215Z digest=sha256:ccc86175be5c5781ba83c3601dcdc2ae9401f31f82d9e1d76e4681f81dbc4273

Observation 405bef8a-8cb0-4609-8ec1-f99f9494fce8 · outbound

This paper cites Approximate submodularity and its applications: Subset selection, sparse approximation and dictionary selection.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Approximate submodularity and its applications: Subset selection, sparse approximation and dictionary selection

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.792253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.822214Z digest=sha256:24865c3167b8e184e646fca249b1a27860db5179c437b2e42ed4a6980125235d

Observation 9d7a75bf-aacc-4082-97a4-10ce12be01d8 · outbound

This paper cites Jacobi-style iteration for distributed submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Jacobi-style iteration for distributed submodular maximization

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.782903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.825110Z digest=sha256:429709642e0ca0653795ce70b6ecc2973fb52e0a18eb2e27651011fec6dd8d74

Observation fad66a8d-3036-4844-acd3-85fc0d6a9319 · outbound

This paper cites Turning down the noise in the blogosphere.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Turning down the noise in the blogosphere

Reference 19

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verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.773133Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.828193Z digest=sha256:d29ef30d866793595235357b1065c898643274bcec654db0b3ac3f9e20715ad0

Observation 5e582203-b46d-40d3-887c-1c9575593b0f · outbound

This paper cites Combatting dimensional collapse in llm pre-training data via diversified file selection.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Combatting dimensional collapse in llm pre-training data via diversified file selection

Reference 20

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verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.763796Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.831561Z digest=sha256:1affb430b0dedebfb487dbd3856e5d1a3732f2e41145b302ed6c66cffd166036

Observation 3ac6586e-240b-4d57-be7b-afc2ffa7e280 · outbound

This paper cites Spider: Near-optimal non-convex optimization via stochastic path-integrated differential estimator.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Spider: Near-optimal non-convex optimization via stochastic path-integrated differential estimator

Reference 21

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unresolved
no resolver link, observed 2026-08-08T20:42:38.834528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.834528Z digest=sha256:08baa73c1e8ffb4f11c0e7b80031fc227cc96bc275bc312b502624dcb47bb479

Observation a614f48d-abb6-444a-9bef-3d3172f5d676 · outbound

This paper cites The power of local search: Maximum coverage over a matroid.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency The power of local search: Maximum coverage over a matroid

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.747913Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.837627Z digest=sha256:408fe8307b0df6a38ab60c0bef370eaab8b634695174aba304b064e1455dd4f1

Observation b739f55c-1de4-4fe2-ba30-57a22f3d249c · outbound

This paper cites Monotone submodular maximization over a matroid via non-oblivious local search.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Monotone submodular maximization over a matroid via non-oblivious local search

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.739033Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.840630Z digest=sha256:06f9948f3623642ca631e46d950ba3c6f1406d73363860b5bbc633e13fd4e5cc

Observation d577e217-d436-4412-84d3-45e6f6e7fb18 · outbound

This paper cites An analysis of approximations for maximizing submodular set functions—ii.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency An analysis of approximations for maximizing submodular set functions—ii

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.726876Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.843715Z digest=sha256:97618c85d353438880608c55d96dcc7b0d544d47b7ac8072b3ab6b3910aeb673

Observation 5099a28a-370a-4538-8726-46d02f2f27e8 · outbound

This paper cites On the convergence of distributed stochastic bilevel optimization algorithms over a network.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency On the convergence of distributed stochastic bilevel optimization algorithms over a network

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.716494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.846800Z digest=sha256:d6575978255b5b28c45156de2ebb757d6a34c3377232f301f4b3a0776e419ca2

Observation 55ff0fca-0707-4a24-b20a-aaf5d80041c8 · outbound

This paper cites Distributed submodular maximization with limited information.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed submodular maximization with limited information

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.706977Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.849989Z digest=sha256:7abe80fbb5635f41ffff3ad84a0c5b68adf6681c59666b7c9817f97c0603d583

Observation b2a74da4-7946-4ef8-ae9a-74df38d0de01 · outbound

This paper cites Cvx: Matlab software for disciplined convex programming, version 2.1, 2014.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Cvx: Matlab software for disciplined convex programming, version 2.1, 2014

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.697216Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.852943Z digest=sha256:76139dd6a41204531f7e37e7ccbf79d04bfd864a29491d2aaee9d5aa4cb3c6d8

Observation 65e95097-b2a3-4efc-9c20-b3d81c62d959 · outbound

This paper cites The impact of information in distributed submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency The impact of information in distributed submodular maximization

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.688144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.857113Z digest=sha256:abee501385150e088cb4684f221297dea5c8606bfb82b4d71eb228ead9457467

Observation e178d3cc-693a-4ae9-9a49-e1f677848996 · outbound

This paper cites Gradient methods for submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Gradient methods for submodular maximization

Reference 29

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verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.678783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.860098Z digest=sha256:2e6117c67aee12c7eb6c0fc3e0469582df16652fff7704d3734fe1a878bf785c

Observation 80e102ef-1adf-4214-b993-dfaad01ef345 · outbound

This paper cites Introduction to online convex optimization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Introduction to online convex optimization

Reference 30

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unresolved
no resolver link, observed 2026-08-08T20:42:38.862951Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.862951Z digest=sha256:c447f002a65d1c4d62afb9543a37517a4119fd1ae9bbab398e6ec52b98632e37

Observation a1ef63ba-e763-44f9-9724-4f76bacb80d8 · outbound

This paper cites Matrix analysis.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Matrix analysis

Reference 31

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unresolved
no resolver link, observed 2026-08-08T20:42:38.866000Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.866000Z digest=sha256:27bb2e9124e51d34598209a39420a15510fa9a006f4bf31c7fe104c05023fa30

Observation 0f3de1c3-26bf-4bc6-b2d7-8cac6049c977 · outbound

This paper cites Online optimization: Competing with dynamic comparators.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Online optimization: Competing with dynamic comparators

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.657892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.868886Z digest=sha256:5926dd6f3e1d19c5a96089bbe38f22c7c73d3578968655daaa37508c53205cdb

Observation 61a76936-4fd3-465b-bbee-b604093b4c65 · outbound

This paper cites Metaxas, and Marco Pavone.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Metaxas, and Marco Pavone

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.648337Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.871663Z digest=sha256:a8da0ba4fd442f0820267fecb79278d5feee48b0c38615b4cdf9a1a701210c8e

Observation 72cfd201-d0a8-4e82-843b-a0bd0dcbd67a · outbound

This paper cites Visual prompting upgrades neural network sparsification: A data-model perspective.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Visual prompting upgrades neural network sparsification: A data-model perspective

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.638941Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.874534Z digest=sha256:eed5bc62fcee8cdd89455cc36a4dc181f968961806dff5b657fec9f354d5a085

Observation fd4e926d-5de4-415c-afbc-953b5cd03ac8 · outbound

This paper cites APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency APEER: Automatic Prompt Engineering Enhances Large Language Model Reranking

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-08T20:42:38.877409Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.877409Z digest=sha256:33ee5ad66895e508ba0725ec9616defcc764a7e7e02771602447a9323bcce172

Observation b1d732c1-175b-4700-be27-9baa2c0e9a13 · outbound

This paper cites How to escape saddle points efficiently.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency How to escape saddle points efficiently

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-08T20:42:38.881036Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.881036Z digest=sha256:26ba30ba0b7e44ac64b9effb866867449fd3550a5b6c57157abfbfe82e72c800

Observation 4e4093bb-bac0-4b9a-a8ac-0e3f0e058444 · outbound

This paper cites Playing games with approximation algorithms.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Playing games with approximation algorithms

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.624003Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.884050Z digest=sha256:c8dde24dc7a447220015f9bd3d3c5073fe7bf0672af5fbaee4de9bb8184a063f

Observation d3416e02-59b7-449a-826b-fa8c5ef6af12 · outbound

This paper cites Maximizing the spread of influence through a social network.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Maximizing the spread of influence through a social network

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.614990Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.887016Z digest=sha256:3af8218c40db171891a4d01c9976a27a2c25cc13ea1b0a13ea022ba4d867b3f2

Observation 3c7fb20d-a036-43e9-b4a2-e5c4ad4d21ee · outbound

This paper cites On syntactic versus computational views of approximability.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency On syntactic versus computational views of approximability

Reference 39

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.605625Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.890126Z digest=sha256:1f12b01fa29a9b5eb826f9f97e678a49870c2b777fca729d7b00d428df863357

Observation 25755990-8aa5-443c-8f02-eb2b54615a31 · outbound

This paper cites Near-optimal sensor placements in gaussian processes: Theory, efficient algorithms and empirical studies.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Near-optimal sensor placements in gaussian processes: Theory, efficient algorithms and empirical studies

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.596584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.892986Z digest=sha256:ee952d9d48add0694191ed3bb8468829482d4be955de83349b875ca4337d3344

Observation de3ecbf3-94d9-4672-bb94-101055ab04ab · outbound

This paper cites An end-to-end submodular framework for data-efficient in-context learning.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency An end-to-end submodular framework for data-efficient in-context learning

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.587636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.896095Z digest=sha256:1bdb11ac53c290b025cd77613d41096024d397bb85631adba0806e98b77127fb

Observation efec36ff-7a33-4551-bf1d-c5088b04b380 · outbound

This paper cites Convergence Rate of Frank-Wolfe for Non-Convex Objectives.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Convergence Rate of Frank-Wolfe for Non-Convex Objectives

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-08T20:42:38.899009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.899009Z digest=sha256:3c0385b9cc2bcaae1f6231dfac79ac78f6e3cca9471b39368cf265c47f8b9cc8

Observation c75a0072-e53f-4d07-b8c4-961235d0a931 · outbound

This paper cites Functional analysis.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Functional analysis

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.578488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.902555Z digest=sha256:8bc9e0772ec184fe574a5d086f3b4b0d1af997f5134589f22b9dab0e1f879b35

Observation 2970570c-bba9-41c5-a2dd-38d6cc47f3e7 · outbound

This paper cites Submodularity of optimal sensor placement for traffic networks.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Submodularity of optimal sensor placement for traffic networks

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.569450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.905863Z digest=sha256:edd11ba0f76ad5f0ea4d0e822b20ef00e5a053d3c97dc339a5427c50f7caa6cc

Observation 9b9be261-c349-4d23-ae51-167feb4682ff · outbound

This paper cites Improved Projection-free Online Continuous Submodular Maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Improved Projection-free Online Continuous Submodular Maximization

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-08T20:42:38.909277Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.909277Z digest=sha256:ea1018bc128143524f4322403908f2384ec7df9bf1f16a0781acde4db5d5b0de

Observation 0d41207c-081f-425f-8896-a3e663e321c4 · outbound

This paper cites Multi-document summarization via budgeted maximization of submodular functions.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Multi-document summarization via budgeted maximization of submodular functions

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.559929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.912727Z digest=sha256:3f6d9fad3deb83acafab4c731ad6ed231918a1d720431e52397feed6da49dab8

Observation 93ba6f4e-e2d8-41d4-a822-73b4400c9a83 · outbound

This paper cites A class of submodular functions for document summarization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency A class of submodular functions for document summarization

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.550593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.915916Z digest=sha256:4ab0da95098cc357b92ce90ad54806b7385450229176f9418ee829a4e7aa0038

Observation 952b41f3-5ab8-4877-b798-e97763032a19 · outbound

This paper cites Distributed resilient submodular action selection in adversarial environments.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed resilient submodular action selection in adversarial environments

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.541253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.918908Z digest=sha256:1353e0d0d934d90b78b1d45cc1c88701978d15401a9ecf7f12be5ac6d33478c6

Observation 6cd4e9ab-2e39-4f25-a598-f2fcc2dfd15d · outbound

This paper cites The role of information in distributed resource allocation.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency The role of information in distributed resource allocation

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.531412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.921995Z digest=sha256:0a24fa0b8f91853aa608df972336d4df0b5103278ada01dcfad0e2eee7498d42

Observation 3b81af62-9da5-434c-8fa4-c32aa2ac8b55 · outbound

This paper cites Fast constrained submodular maximization: Personalized data summarization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Fast constrained submodular maximization: Personalized data summarization

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.521755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.925032Z digest=sha256:bda55f48d5e81656ef92e91a70b367119af9ba7d27a6ca4423ce326056c4a4dc

Observation c244cf97-5c5b-4a08-9e10-3d509888f9e9 · outbound

This paper cites Distributed submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed submodular maximization

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.511527Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.928187Z digest=sha256:dc96b77bbfd75a2ce3a32795348c1058424f4d84652ad0decf43f11c1f30e064

Observation 343b0202-8e02-4a9c-b6b4-d5a016f6d8c0 · outbound

This paper cites Decentralized submodular maximization: Bridging discrete and continuous settings.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Decentralized submodular maximization: Bridging discrete and continuous settings

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.501741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.931552Z digest=sha256:372d23566e37d8f6b71de0ae4a1108777e171bdd56d8dcbabb0defa19a5d05a0

Observation 47eea9fb-c388-49e0-b219-e91059290cf8 · outbound

This paper cites Distributed optimization over time-varying directed graphs.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed optimization over time-varying directed graphs

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.492345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.934749Z digest=sha256:b548bef7edc71b1fe73c7163b9ae54a13d33ef71463ef572b6e891b034b3af78

Observation d7999030-76ac-4330-b15e-281130eff157 · outbound

This paper cites Distributed subgradient methods for multi-agent optimization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed subgradient methods for multi-agent optimization

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.482660Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.937889Z digest=sha256:8eb897c68d87106c7540363d360e54e3d29c9188839d2435677ca9e87b608206

Observation 08e6250b-cb19-45e3-bbdb-67633e58965d · outbound

This paper cites Achieving geometric convergence for distributed optimization over time-varying graphs.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Achieving geometric convergence for distributed optimization over time-varying graphs

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.473087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.940957Z digest=sha256:f9e6ea2baa9ac2442558b93d171d9c9ae5e6d4a5eccfa68818ae88814fd91e73

Observation 0ed2c420-13c1-489a-98bc-4e02c6e74ded · outbound

This paper cites An analysis of approximations for maximizing submodular set functions—i.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency An analysis of approximations for maximizing submodular set functions—i

Reference 56

Resolution
unresolved
no resolver link, observed 2026-08-08T20:42:38.943939Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:38.943939Z digest=sha256:80818e68ee6de5b36315dbe040d95fe476757e10ea9881d1834c4e1961017b25

Observation 769073b7-c2bd-4f74-a363-16d796cb66ca · outbound

This paper cites Nemirovsky and D.B.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Nemirovsky and D.B

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.457633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.946937Z digest=sha256:ae298d37ee0804f62f236f77fa704df8b002d78e8af023c5db9231671f377a88

Observation 01b9bc97-406c-43c3-8629-1f640822e928 · outbound

This paper cites Introductory Lectures on Convex Optimization: A Basic Course, volume 87.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Introductory Lectures on Convex Optimization: A Basic Course, volume 87

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.448556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.950013Z digest=sha256:235dfadc22a66ebbb4b878812d9698f1ed8349c2706f08ee84dd1db9e48edea6

Observation 5464934d-13b4-49e5-925c-4ae3d0db540d · outbound

This paper cites An algorithm for a singly constrained class of quadratic programs subject to upper and lower bounds.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency An algorithm for a singly constrained class of quadratic programs subject to upper and lower bounds

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.439316Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.953179Z digest=sha256:35a1f7b6d9bd50ce08718714928d4cb5ffb43850c6e5dc6ab49e9034f3823a2d

Observation 5e0745ab-0a36-40d9-889d-38670f9dc41e · outbound

This paper cites A unified approach for maximizing continuous dr-submodular functions.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency A unified approach for maximizing continuous dr-submodular functions

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.429666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.956437Z digest=sha256:ddcba1d31580d6553916dd76e3a1603f2b99df1d8263ebe63b7c4f87dba3c50a

Observation ef4d7b7b-b4e3-4574-81c7-79e37babf088 · outbound

This paper cites Nadew, Christopher John Quinn, and Vaneet Aggarwal.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Nadew, Christopher John Quinn, and Vaneet Aggarwal

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.420401Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.959516Z digest=sha256:07e0a86a256be2c4d2b55c06e70a12264f5b5573418b16014efa74d38ef5d68e

Observation 3de148ae-2b4a-480f-a274-d1c9b4d3b639 · outbound

This paper cites Near-optimal multi-agent learning for safe coverage control.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Near-optimal multi-agent learning for safe coverage control

Reference 62

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.409205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.962561Z digest=sha256:4c0a6a7d74a2de7e53240cc5e0aaf73aefc303a8349f4e76b312900b037588f1

Observation a534abec-dede-4844-83af-69c53fa12daa · outbound

This paper cites Distributed stochastic gradient tracking methods.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed stochastic gradient tracking methods

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.400284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.965613Z digest=sha256:d80510352ec09ff6e1c71a1583a586683042d5c81298e2de46c72e43d7f6b82e

Observation a02ab6c3-7de3-4071-9fcb-61c0f912bc87 · outbound

This paper cites Distributed greedy algorithm for multi-agent task assignment problem with submodular utility functions.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed greedy algorithm for multi-agent task assignment problem with submodular utility functions

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.391111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.968748Z digest=sha256:efcc7173f9cad301e699dc2dd64e1aa6c5484f7bc5494bb209214f2451408c18

Observation 744237cc-eb0c-446e-af8d-0231fce5c808 · outbound

This paper cites Decomposable submodular maximization in federated setting.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Decomposable submodular maximization in federated setting

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.381884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.971791Z digest=sha256:b5d2e474c3db4afea1346d62063f779b344b0c2530aa513d434b58bf73a17d45

Observation 96d1b86f-e970-4f08-8734-16ac7be9466c · outbound

This paper cites Distributed strategy selection: A submodular set function maximization approach.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed strategy selection: A submodular set function maximization approach

Reference 66

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.372780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.974810Z digest=sha256:10704a4adbe16bc588e013544c429da7ba32321ad633c06d2e603e26b47635d3

Observation 037ef1dd-3247-4adc-9273-b4a1bb7450f4 · outbound

This paper cites Optimal algorithms for submodular maximization with distributed constraints.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Optimal algorithms for submodular maximization with distributed constraints

Reference 67

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.363198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.977876Z digest=sha256:c41821511a1887d48762f9859aa63efda76d5b46253e5e2fe4325e1fedb80fdf

Observation 12eeba83-c695-430d-ba04-21c61a704207 · outbound

This paper cites Resilient active information acquisition with teams of robots.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Resilient active information acquisition with teams of robots

Reference 68

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.353200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.981142Z digest=sha256:7c5a6bcc38793e1bb7458ea1a3bc7e8346a0015012322bf9398eca2aa8501459

Observation 9c4b6291-764c-4c0b-bf88-1327da1685c0 · outbound

This paper cites Distributed online optimization in dynamic environments using mirror descent.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Distributed online optimization in dynamic environments using mirror descent

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.344256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.984032Z digest=sha256:593322125e355615e1a6dbfbf01819eac3530a7df622bd70201f8075ff4f50c4

Observation d5cb0708-3c15-453a-b90b-4e5e75b58e1e · outbound

This paper cites Efficient informative sensing using multiple robots.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Efficient informative sensing using multiple robots

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.334819Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.987104Z digest=sha256:aa56a31eb20187b7a6e7a5dceef1577e0b05f18a5ed897bdfbcd42006908983b

Observation 5f03b3d5-56fc-4b84-b731-17b1d26ca220 · outbound

This paper cites An online algorithm for maximizing submodular functions.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency An online algorithm for maximizing submodular functions

Reference 71

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.325996Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.990129Z digest=sha256:291500c32e0824668dfe09776219e9846d2e7501e05b8ac275f7d95bbc6768a8

Observation a081e94d-f102-41dc-8f1b-8d194b61d124 · outbound

This paper cites Submodularity and curvature: The optimal algorithm (combinatorial optimization and discrete algorithms).

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Submodularity and curvature: The optimal algorithm (combinatorial optimization and discrete algorithms)

Reference 72

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.317063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.992943Z digest=sha256:02b99e88ac0f8a2fdebf7981bd43347fe73914c885ec5097c3c6f6ca3fb15907

Observation 5634f4bb-1c57-42ec-9068-fef4651d1f9c · outbound

This paper cites Symmetry and approximability of submodular maximization problems.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Symmetry and approximability of submodular maximization problems

Reference 73

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.304685Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.996095Z digest=sha256:981641222c756feea09d5eb4e73019f6959be54b499a27cbced3e970c323ca9a

Observation ccd2855a-fbf5-43a1-9b50-44aa8ddab693 · outbound

This paper cites Bandit multi-linear dr-submodular maximization and its applications on adversarial submodular bandits.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Bandit multi-linear dr-submodular maximization and its applications on adversarial submodular bandits

Reference 74

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.295573Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:38.999374Z digest=sha256:2b8971584e7c32fdc2f190e60a72b8d226295e1b093ba82803c7241054425c8b

Observation 9a3ce273-cfc4-4d2b-9489-5b5910891bdd · outbound

This paper cites An empirical study of user engagement in influencer marketing on weibo and wechat.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency An empirical study of user engagement in influencer marketing on weibo and wechat

Reference 75

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.286537Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:39.002420Z digest=sha256:ac1c4245e0ffade6f80013f2c38c391ee342548d569e03b49c6312f1edeb17cd

Observation 72138928-c1ba-423c-8a50-7ae9403c82ce · outbound

This paper cites Using document summarization techniques for speech data subset selection.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Using document summarization techniques for speech data subset selection

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.277421Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:39.005807Z digest=sha256:bc23e09621640e9677426057f8638de7c98aafafda00bb037307720393b839a8

Observation 1b078945-549a-43ed-93f0-818653e920aa · outbound

This paper cites Submodularity in data subset selection and active learning.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Submodularity in data subset selection and active learning

Reference 77

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.267719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:39.008921Z digest=sha256:b4af589165594afe358b51afc365adb9fa07490f174075ef2a762304dda8a77b

Observation d101e4b3-6a11-4fd6-8d57-7b80bfc2120d · outbound

This paper cites Decentralized gradient tracking for continuous dr-submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Decentralized gradient tracking for continuous dr-submodular maximization

Reference 78

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.258072Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:39.011930Z digest=sha256:0f8eca658b76f83df413a35f5208d3a1f7f6b14d9e56f5d80fc02f36962aabde

Observation 30c025bf-45e4-4255-9b41-8d5ec57c0788 · outbound

This paper cites Online submodular coordination with bounded tracking regret: Theory, algorithm, and applications to multi-robot coordination.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Online submodular coordination with bounded tracking regret: Theory, algorithm, and applications to multi-robot coordination

Reference 79

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.248936Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:39.014913Z digest=sha256:cc12d615b669ee9af6beef7eb6178b123bc52ecf2e3dc5fe91546bcf211e70e5

Observation 0b093079-da53-4bd8-a4d4-7f4afc25a554 · outbound

This paper cites On the convergence of decentralized gradient descent.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency On the convergence of decentralized gradient descent

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.239716Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:39.017786Z digest=sha256:96a1eb94b66453d3d48e9b674d96c3d437ccaac0cd39ac94443e4a6f3b22fb16

Observation 69b3962d-015d-4a97-9eda-69fe94c06c08 · outbound

This paper cites Stochastic continuous submodular maximization: Boosting via non-oblivious function.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Stochastic continuous submodular maximization: Boosting via non-oblivious function

Reference 81

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.230108Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:39.020826Z digest=sha256:02118d2be4e23b235b94e789406d4bc10f1775b2aeab6585422ff5a1395d2ae2

Observation b936baff-8a86-42c1-9efb-266385226909 · outbound

This paper cites Communication-efficient decentralized online continuous dr-submodular maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Communication-efficient decentralized online continuous dr-submodular maximization

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.220782Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:39.023950Z digest=sha256:a487f32fb21ad92759cd9acd65917fce1c83f65e281c72b9bba88437156783b9

Observation d145699e-4209-4e17-b01a-5e04ddec62cb · outbound

This paper cites Boosting Gradient Ascent for Continuous DR-submodular Maximization.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Boosting Gradient Ascent for Continuous DR-submodular Maximization

Reference 83

Resolution
verified exact
local_arxiv, observed 2026-08-08T20:42:39.090502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:39.027006Z digest=sha256:6bb63bfccb1ba6e4d074fb2366660c182b6cd8e112f5154c517cc4912c589c5b

Observation 92c29081-f9a6-42ec-a93d-909dd6e1137d · outbound

This paper cites Minimax optimal q learning with nearest neighbors.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Minimax optimal q learning with nearest neighbors

Reference 84

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.210706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:39.030439Z digest=sha256:38e602b411887328d82b665f62b8891f4e7f19cabeaca48abaf5dc09dfb17282

Observation 2275dcd2-74af-4d7f-a531-0882a8996bb0 · outbound

This paper cites A huber loss minimization approach to mean estimation under user-level differential privacy.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency A huber loss minimization approach to mean estimation under user-level differential privacy

Reference 85

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.200008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:39.033489Z digest=sha256:056aa27a874f0778e2f4f679f2c6160e25634e0a4978a55c83c0ff8fa9b30211

Observation a77bdfe1-0252-4252-8029-4630fc454c92 · outbound

This paper cites A huber loss minimization approach to byzantine robust federated learning.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency A huber loss minimization approach to byzantine robust federated learning

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.190000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:39.036526Z digest=sha256:dd6457cb3a268c3bec15a6d751b939bd0db3c29fd3479c308ecbd3580d703c42

Observation b6ffbbb7-e452-4769-ac7b-6029cdff8eee · outbound

This paper cites Risk-aware submodular optimization for multirobot coordination.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Risk-aware submodular optimization for multirobot coordination

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.179681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:39.039538Z digest=sha256:6dfdea3110eed5c99ae216293a5e2cf633664a5abaa374b6af40f0a35e27d3c7

Observation 96adf695-67a3-475a-b829-b78233b009d1 · outbound

This paper cites Resilient active target tracking with multiple robots.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Resilient active target tracking with multiple robots

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.170012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:39.042636Z digest=sha256:b6c01c7a7d90f89707f981f59172b0cd99f4789372ffcfccda759be4cbb7375d

Observation a057bfe9-2922-4601-8280-b26c071515d7 · outbound

This paper cites Projection-free decentralized online learning for submodular maximization over time-varying networks.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Projection-free decentralized online learning for submodular maximization over time-varying networks

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T20:42:39.160071Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-08-08T20:42:39.045683Z digest=sha256:6345beb4da3e84e47eb229079f731da8cf9e41ae1610d5af047332289bcafed1

Observation ea9b0420-23f4-4496-a3ef-9db5593e49ca · outbound

This paper cites @esa (Ref.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency @esa (Ref

Reference 90

Resolution
unresolved
no resolver link, observed 2026-08-08T20:42:39.048767Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:39.048767Z digest=sha256:d36fb0fa86272d771f9a7f5e994507c4499ae185cd22574da25682d8c1a4bde9

Observation 5cd28cc2-acfe-4c47-a71e-bdb330904553 · outbound

This paper cites an unresolved cited work.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Unresolved cited work

Reference 91

Resolution
unresolved
no resolver link, observed 2026-08-08T20:42:39.052045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:39.052045Z digest=sha256:315beceb8dee52013a7b544d2fbdf7843430c2cf5c5c74d804abac6521133c4f

Observation 46e34410-7dd1-48af-8a8f-222e1848cd6f · outbound

This paper cites an unresolved cited work.

Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency Unresolved cited work

Reference 92

Resolution
unresolved
no resolver link, observed 2026-08-08T20:42:39.055335Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:42:39.055335Z digest=sha256:328005c66251d3d8539798e4108fea928b7b32254c868b8dabc4845418bb737d

Pith citing papers

Observation 3c9f5127-ffff-4c9b-be23-4dc9e2d7505d · inbound

RankFlow: A Multi-Role Collaborative Reranking Workflow Utilizing Large Language Models cites this paper.

RankFlow: A Multi-Role Collaborative Reranking Workflow Utilizing Large Language Models Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency

Reference 75

Resolution
verified exact
arxiv_id, observed 2026-05-23T04:37:31.892450Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-23T04:36:32.897387Z digest=sha256:fd1c2f93eb9d06e4e8cdb4a3bd1a608c88f8a7fdc5c1c67dbca327dda53e8054

Observation 841b139f-0f3e-4f7d-9973-78346f07a5b2 · inbound

Self-Configurable Mesh-Networks for Scalable Distributed Submodular Bandit Optimization cites this paper.

Self-Configurable Mesh-Networks for Scalable Distributed Submodular Bandit Optimization Near-Optimal Online Learning for Multi-Agent Submodular Coordination: Tight Approximation and Communication Efficiency

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-02T21:46:55.043461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T21:46:55.043461Z digest=sha256:f823823a5b25dba380eb3e7b943d0b61e05bb161db4952f77a48ca3ab7a6973a