Pith. sign in

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

Resolution
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=sha256:7b003a82146df1aed9984cc4ac8df4e05f3d65773886335168af203c239d8196

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

Resolution
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=sha256:1eb9a5b65cb14b463b1b8aacfbc129793107fd219110e36f85cfe1388e8a06e3

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

Resolution
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=sha256:2eb6cf0022e66470c7df057cb534dee168e239be74d111b11c04b9aa678142a9

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

Resolution
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:b5e7368a493dc648ae9056e9d679050b411f013fb84fb0f85deed7e5bd49dde9

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

Resolution
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:acd82aa2ed2632449ebccdfa2092625e005b1387877f4ffa06c3dcb296088224

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=sha256:80b36db0e28e4cba1f8be50704aef283c9a20b84578d02f4ab353dcfc8599b1b

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=sha256:2a0fd8cb1ac6f831632e21f0e26bc1b95fba0549c2730176fa8409855c257b3d

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=sha256:815da25d02c0fd6ecb4789c8bcd270099c39fb7ef46685390a6dd66009a194ad

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=sha256:5bd6590704453ad1e9560e5b1a0c58c8cec7514c9a297a1eeb219ccacb896afe

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

Resolution
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=sha256:0f92fde24b3017d210bcb6a55bbc55372367f4a19028e4d20a8d8c3bf0a14a99

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

Resolution
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=sha256:866c6a480e083ae386b8233356b15c9ee3a7899970230cd445b83e643494948e

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:afe063eef147b057fd73682411c2b16baabb1887f7f59021d83003bbbaf2fe52

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=sha256:2748a9deec8a5cdd9ad14f30fc74509e4fe750a73031ba5ab649d189fab2e70c

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

Resolution
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:dcf052939fa06087ec3a18524538d5a51574e0fbe9ae333936d90a7706e8222c

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=sha256:204475bc8b86f2a7fd20d01ec9739f042f16d03f5b72e18b00c420cb7a05468c

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=sha256:8810d43eb20d9f106b5ef9dbc53f87f7edbaa8d2f3855430c10748bff0a63827

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=sha256:856df1e053484ee9545c6345c0e5d52c1c656000f0dd1bf0ea0385fd386cdd70

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=sha256:7f04c6a81d32ec8c64abf7652176f6293038bcbdb364e6519d9dfec3dd1ffd93

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

Resolution
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:dc556ffba6b153c1e162a9b8a6d5764111464bf238227d8fa8c0f63570fba4b8

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

Resolution
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=sha256:858798ae0aeea43dccae81aebfbda6c9dab99e8c2e6c5b2c4ee2c65eb7a871f5

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

Resolution
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:c5e610fceb254faad58216ebc21ae23a08e15bad987d51e2c64e044e1ebb52ed

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:df23f203400be9d693da9f8252b0a4a9ca1afcb80e7b9e60a2acb0926860c178

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=sha256:66d085b6bcc9c5ce05969edd7643b0ee18577a7feed197630c98abca17270ce7

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:afd162d79854dc19753fd75657857e8d6851245e58f61c92bf18ae8908ff00fc

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=sha256:61bf6617e6f22dd846cecbc6a39fc65bb6ad9cb63f7a2e9e18805be67dc69279

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:cda30be17a9d7870d6d5dc8df9aa9d194e0fe43f90f53c1dec92b6baee7da1dc

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=sha256:924e6c733b6e9a1c5db68b42188ffca8fb23136cc8da1be6b20225f352568213

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=sha256:6fdc9f4059db126b6c96d1b3d8de47f6c0f987182ad4f2c8ed6a0b121fabbd38

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

Resolution
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=sha256:6925ba73eff1fc43620321594272a2a58bdc4a172a77791a6ee1a052b2477f63

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

Resolution
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=sha256:084bbd188e15decc9a4a123b3a8092ac5d0e8909f3fdd16a672bcf5d0536443e

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

Resolution
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=sha256:577910d01b68156898c6d723903720f64a57bf15ee795ce20294e08514d28e38

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:e224550b521d45282fd9616304dff39cb78f9a19d73a5fb144420769f10d1656

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:bbe7156f1ae0ebf5e8e154e6cb05225fa1bca4690c4ccfddba44dcd68a8bcdb8

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=sha256:95266fb054a476d83440a8d51114120923ec92480a6f589f40b979dca8af95a1

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:b3139a24afff03cd40a553edc4563ead9d0e3cbcd30986c0956a8599ff42a289

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=sha256:0c1b93fe9e5d2d0a91b8e5c4564753dc0f56c530ef4f525832267537921e12fa

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=sha256:7686f21e70de665bcc28f16c57f25712580a6fae12d9b75cbf383340610e1e71

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=sha256:92cb8740a93c4faef6b3a7202160d01548558e2c0cc01b85a79d9cd48a9a318b

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=sha256:260627373fcd25afc319433e01538e3227922cdfa2a970a990b5ebe3801cf5bf

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=sha256:26a48b01423b20f036347d0f0f3103e64b135787387c401b1a9957ce79ddb23d

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:f1638b56dea65856bbccad04a9dbceda8f747d93a2514de16990f9c87d313b26

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=sha256:1f1324ba9cab2fa7376eec43423986f42eb008cf2adafd58b6a24f530588a5bb

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=sha256:5a6d82d09d1cdb82c4e0b21f44d0bc450909983acc8b6bc5a9bed970600545e0

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=sha256:30ad071893ee65101c4e5f74ad623ebe994af5b1f8ebc8ce2f79d40fb31c6c32

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=sha256:8ad0ce32bbd91d5c895176afd65a733ac2631761751558943f0e78b47382e3e7

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=sha256:2e5a1e3d50fc77441e356ea2ed074301ca654cd2b46224292ba19f853aa148ad

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=sha256:2f0899c93f3ee4ce5d412364a1bb699672c0921dc8c6b3af674f7bff7e4e3dcd

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=sha256:37f2d73cd4b185370f476e02ba8b09d158c500a9885a7faf1025f23af6c0debc

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:d466f61634370ee37ec328cef56686107939ec159437a947cd8fac59bae5e3cc

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=sha256:42e3345b2bbb88c3defa740a16d33a4e9ddfd00198de8f30b6a873b71d87e381

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:d98f0c4cac62f904673bf1d942ead21f19d09911d1bbff18ee73037307dcc8cd

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:ff3c82e1fb619cfe450d393a653663b04e74e8c956dfd8660e4fd3216ae69636

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=sha256:5096d595bd714420322f646d5d408f4604a4c1995b21f0cfeedac96e84bdee54

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:c5decb25d435e0ff36998ae2d8da17fab8a0b4f78236fee51b787ef4ffa8296a

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:a5c2950003350fdab8bd7cec49056a52ce78354754b128a7d22e728e5610f160

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=sha256:2720f74072c049063fbc75b0a827c4dc5fbd440bfcf097f85a78f47a689bd144

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=sha256:3d75b23ec89151bc9132560111cdb4e796b1732c01522daabb0b71e4f581cd22

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=sha256:24339ea6a221d3016cefa6aa21aa1ac2c33ecc6f2b54892b5fe9d1fafa9036fb

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:efc9e272d5adc884268d65a50addfc2e22819b79119eec6efc1ce7c158a6e5ac

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=sha256:0a2f82b17f96db2ee23d9a50d75f53b6707cb79006c7dcd3360591b3d0abea70

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:a48a363a3c17f33bf2f5820bfe551a841eb93e3985f50900b270ae22aeb9a4fe

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:e0efc1ec9fb1d94e001df42b5f5920175c149e67ea948dbf3071ca512f8fea02

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:caf3b73ec96601fb40a9087aa456233c65a4cd7725a7424fc9c53e80edc704ff

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:d20bd7f9a117598a5c78c7682bba7526aced1e84cb09db8153e6454970f25691

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=sha256:452c9fe0700f7e7f4f08f9876e1f1a302cbbf84d6d2ca2c311e22414013511be

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:a1b4cf289cebfc8582f73eca879667cdae667c37a34773690564b794648dadb4

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:db8fecfb75a0c37859a430542cf05085ccfda4129b414327c37b214f30f5f0b6

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:fcd65c7530a3656e929ee5fb30770364b852e1ca5a863263354b611738933ad2

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=sha256:3c67c4291b9d158d8d5bcc290f9bbf69ec8e01e73610b42076906c3cbe7e2b18

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=sha256:6e8e4f6ddabe5f3d5ed2c7423dd345310fce452721ac87f5d85ee927a6043320

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=sha256:5579ca1ca2b9e90e7bc68be567d6dc5714be383ebd90e4d684242e2e5300eac3

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=sha256:6ed9ed1caef83a50f0c1e10faecc4262afeb1b3c82dcdd717949f67b461b1d8a

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=sha256:72fdf1608a74c7821e2bed61aa0f34418219e7d1df4d3e148b67e5d727fb96a9

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:f51cf7a4cee86fb57a0d0c4152c6eeea2d2b4b5637970d27dcd94baa4b62abad

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=sha256:296341deef56801fdb65926c45051f3d1429aee29ded69576da910233fa8340b

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=sha256:9848789785bdad40e27f8d856b42e0d80ce5213654f8afd0dec726a779d8ecbf

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=sha256:75436619f2e6cb5feff117d3dadef8a1cd033d61d568ab11a98f6a8675d4191f

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=sha256:8bf980932602ac82ace253f1eb9bfa7ae46e0dfcd985a7aa75c46c23eb539110

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=sha256:5b13cd7a850fff70a43db2ebb2fa5e8292a91aa3e788e0fe866ebfe0f63b5bec

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:c136803d434af97a1a47950bfaf8e35d1b126e59474bf9b3456cb707b902c806

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=sha256:4869b57c20943577d1e00b74656d1cc2082fcad9fd2e024c06e2c059038f86d9

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=sha256:377b3c23eed250367ed2d3eb74e87c9bee066eb0d3ca5f07abb709eaf68d2035

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:cc1968d931d9026f0ef2a8d28e064ac6640853d5d72b7a41196908829ea00d96

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=sha256:2e08a90679b6a5b6cbb0d7e2d622ecabee427c586f947417c22fa966924e9ab7

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=sha256:948343167a1deaafa89ad2ab9e3f8a707403277cd48cc36d1a8c9789db576a19

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:f0a9a0f8d1bd47a37f5778dd69fde86844bffa0b3707c63508418b424110d629

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:a9afd9f0e83897f0c8a51b63e1e593cf8530f5e18716b68ee4a7aaea35b8db3f

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:d1fea31cfc78bc07e4127ee0a111c2db69889413448f24aa0ab256cc5c4fcf08

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:f9d50dd7ebf4e4b4a4e2cb42dee1246f0454accff34e00414cbe59be1e8fd38c

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=sha256:88b5e29e63ffeb39b6fae868178171ba587a9978e01711505963db8c5432632b

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=sha256:5003a87ad5007fd4168955e9965855d63dd5760c57a76409458caea298fa52fe

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=sha256:32a423d2b0a056725f69994add872e1ff351e8ad1b3e5d835829835f4379063c

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=sha256:18a94d0cff5ed8da768ebfe87c7e855411350027ba5694d44329319280a6ecb7

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:fcf7a1a338ab570f0ef9a829c255a08f5797c946d08ebb6f857f83d893b353f7