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Paper Citation Record · LEDGER

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling

As of 10 August 2026, this Paper Citation Record lists 87 of 87 outbound references and 1 inbound Pith citation observation for arXiv:2501.12942.

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

pith.paper-citation-record.v1
2501.12942 v2

Coverage vector

measured 87 of 87 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T16:40:59.073705Z

measured 88 of 88 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T05:35:40.449647Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T05:35:41.926170Z

Reference resolution

87 of 87 outbound references displayed

  • verified exact1
  • verified fuzzy47
  • unresolved39
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eb104c3c-88a2-4b61-944c-d205dc9f00b3 · outbound

This paper cites Is Conditional Generative Modeling all you need for Decision-Making?.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Is Conditional Generative Modeling all you need for Decision-Making?

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.578102Z digest=sha256:53a0c56012da137e37b79e99eb67deda6c0d1f69344e21f96ceb5d3d062f8e2d

Observation 36099542-422f-4018-8574-f77ac7206ef5 · outbound

This paper cites Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Deterministic Uncertainty Propagation for Improved Model-Based Offline Reinforcement Learning

Reference 2

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local_arxiv, observed 2026-08-10T16:40:59.511070Z

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=2026-08-10T16:40:58.585733Z digest=sha256:0e54ce911ab0938f3d2af3367b6ec50766632b6f9f43543726cdb85aef9f51b8

Observation 4827e75b-8caa-4d6a-8737-e24bd90971d5 · outbound

This paper cites Lyapunov- based optimization of edge resources for energy-efficient adaptive federated learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Lyapunov- based optimization of edge resources for energy-efficient adaptive federated learning

Reference 3

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source=pdf_text observed=2026-08-10T16:40:58.592310Z digest=sha256:6346ca1b321d369a236752825cf905522f58a4759adaeca9b50798b071a96eb9

Observation 0484aaf9-3369-43cc-897c-b64c00b33c5e · outbound

This paper cites an unresolved cited work.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Unresolved cited work

Reference 4

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source=pdf_text observed=2026-08-10T16:40:58.598271Z digest=sha256:daa5f51e96c426b512989cfca1ef1ba676bdac2bc625bc5ca20ceff18e730255

Observation bbfce0c0-7a29-4e1c-83a6-0308dc660d6a · outbound

This paper cites Score Regularized Policy Optimization through Diffusion Behavior.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Score Regularized Policy Optimization through Diffusion Behavior

Reference 5

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source=pdf_text observed=2026-08-10T16:40:58.603977Z digest=sha256:2af0721e3df34af7c556aa55da492aeb5cb7609d24cf925085245c965ce74896

Observation 74727034-1759-49c4-b9c2-884942bb6f24 · outbound

This paper cites Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Offline Reinforcement Learning via High-Fidelity Generative Behavior Modeling

Reference 7

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.616367Z digest=sha256:763c9fb49f2aaffcca837444de611056716ec3595258f93c5db8cb9c997460df

Observation 8af82131-b180-4117-82e0-606d8b8fda7f · outbound

This paper cites Timely-throughput optimal scheduling with prediction.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Timely-throughput optimal scheduling with prediction

Reference 8

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source=pdf_text observed=2026-08-10T16:40:58.621934Z digest=sha256:66a5b27c279b23bc20edf55f05ded401847b7536bc879aba633a11f69597221b

Observation 0d10936d-99d9-4224-a98b-383dc5179e76 · outbound

This paper cites Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Score Approximation, Estimation and Distribution Recovery of Diffusion Models on Low-Dimensional Data

Reference 9

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source=pdf_text observed=2026-08-10T16:40:58.627339Z digest=sha256:adc2cac375e3321b7553d0fba3c365f52b1639ad63e504ce1d6074882f6a2286

Observation 5c080717-96c1-40f2-be92-b41c935109f4 · outbound

This paper cites Diffusion Policies creating a Trust Region for Offline Reinforcement Learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Diffusion Policies creating a Trust Region for Offline Reinforcement Learning

Reference 10

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source=pdf_text observed=2026-08-10T16:40:58.633334Z digest=sha256:7a91fb1f4a9543fc0c0d9aa91461ab329bfae4fca498538db4923a5fbd94e6be

Observation e4e56800-408c-489e-8eea-e6053d96c63c · outbound

This paper cites The roles of carbon capture, utilization and storage in the transition to a low-carbon energy system using a stochastic optimal scheduling approach.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling The roles of carbon capture, utilization and storage in the transition to a low-carbon energy system using a stochastic optimal scheduling approach

Reference 11

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source=pdf_text observed=2026-08-10T16:40:58.639229Z digest=sha256:5221a914cef01ee49a26bdc82edfb71861b58bdca7486b1affe94b2987e4cc05

Observation b3c2562d-37d5-4b91-b8be-16b7da7ce3e9 · outbound

This paper cites Channel estimation for extremely large-scale mimo: Far-field or near-field? IEEE Transactions on Communications , 70(4):2663–2677, 2022.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Channel estimation for extremely large-scale mimo: Far-field or near-field? IEEE Transactions on Communications , 70(4):2663–2677, 2022

Reference 12

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source=pdf_text observed=2026-08-10T16:40:58.644959Z digest=sha256:1d7c78beb457ab22219268b392f2a6b849c16a1841248a86dc495b4d64a4d6e3

Observation faed407b-ab62-4259-a36f-c5b8fcd219b8 · outbound

This paper cites Data center energy consumption modeling: A survey.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Data center energy consumption modeling: A survey

Reference 13

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source=pdf_text observed=2026-08-10T16:40:58.650354Z digest=sha256:d3f3a44fe7dc3e6dae46836ba22ff4fd89d24f0d3d6d1a808d2eda2216769061

Observation 1103ebb0-abe9-4bb4-8f85-3cf1319db7ac · outbound

This paper cites Channel-aware earliest deadline due fair schedul- ing for wireless multimedia networks.Wireless Personal Communications, 38(2):233–252, 2006.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Channel-aware earliest deadline due fair schedul- ing for wireless multimedia networks.Wireless Personal Communications, 38(2):233–252, 2006

Reference 14

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source=pdf_text observed=2026-08-10T16:40:58.655490Z digest=sha256:7605cbfaa6abc3c8130489aa0f1197dc12adfcb9c5cf37ef328518a42eb4618c

Observation 1d4a351a-c3dd-4cea-ad12-0857b3731924 · outbound

This paper cites One Step Diffusion via Shortcut Models.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling One Step Diffusion via Shortcut Models

Reference 15

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source=pdf_text observed=2026-08-10T16:40:58.660911Z digest=sha256:df07b67c5b7b585143d0c0af70de9d47924256a961dd5f58a8a9122c42aa7954

Observation 0d44e707-aa40-4cb5-bdab-883327d7ad08 · outbound

This paper cites A minimalist approach to offline reinforcement learn- ing.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling A minimalist approach to offline reinforcement learn- ing

Reference 16

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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=2026-08-10T16:40:58.666401Z digest=sha256:22f7682dd487540ab59120267a364ce8480ff257fa15de8caca667656ac3587c

Observation f3a3ebed-635a-4c63-bd92-08d10a7bbe7e · outbound

This paper cites Off-policy deep reinforcement learning with- out exploration.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Off-policy deep reinforcement learning with- out exploration

Reference 17

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

source=pdf_text observed=2026-08-10T16:40:58.671646Z digest=sha256:54ed214288f1506ab3c207509d24eb7acd8ce9618fa80bc4e560e12442a55d9b

Observation 4bc7035a-edd4-4c7c-b780-fc8c49b71bdc · outbound

This paper cites Channel estimation for extremely large-scale massive mimo systems.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Channel estimation for extremely large-scale massive mimo systems

Reference 18

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raw_fallback, observed 2026-08-10T16:41:00.346376Z

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=2026-08-10T16:40:58.677392Z digest=sha256:332ae60858f4cdf9eb97c369d6261bbd1b80ef7868d83c503a76456324cb83b2

Observation 6f7444df-37e3-41af-9a6a-0786ccc7060f · outbound

This paper cites IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling IDQL: Implicit Q-Learning as an Actor-Critic Method with Diffusion Policies

Reference 19

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source=pdf_text observed=2026-08-10T16:40:58.682727Z digest=sha256:5015a8c0e34f4d1c24febd664bb0f0f6d25d72a6493bd0eb71a5c69cba549e72

Observation d456b656-edd8-41d9-bf4e-3fd8decce686 · outbound

This paper cites Double q-learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Double q-learning

Reference 20

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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=2026-08-10T16:40:58.688194Z digest=sha256:ae4d51c47a097ef044a52344bd98e743c746cf38db8faa846d1a31f55d8f7671

Observation 89bebf86-f693-4666-b5a8-d43c9c49fec6 · outbound

This paper cites Denoising diffusion probabilistic models.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Denoising diffusion probabilistic models

Reference 21

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source=pdf_text observed=2026-08-10T16:40:58.693830Z digest=sha256:2565576772473410a9aa0583430bef1858d4b534826f7efe7bb3f565a6852277

Observation e887b3d5-eff8-467f-bdb7-330c0805e2ed · outbound

This paper cites Multi-user delay- constrained scheduling with deep recurrent reinforcement learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Multi-user delay- constrained scheduling with deep recurrent reinforcement learning

Reference 22

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

source=pdf_text observed=2026-08-10T16:40:58.699441Z digest=sha256:0f1d77298d65759447f3f0a6c3627d625ed911e965f425c2cab4767022e48e91

Observation 26ef9fee-dfbe-40a6-9f29-86d5ed30babe · outbound

This paper cites When backpressure meets predictive scheduling.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling When backpressure meets predictive scheduling

Reference 23

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

source=pdf_text observed=2026-08-10T16:40:58.704782Z digest=sha256:82efe4db5af23fac75c43377b8780cdf01e7d51ec25f37604b9f19370c5ed964

Observation d9978b55-8426-4dac-8dda-d9ddf05f7280 · outbound

This paper cites Planning with Diffusion for Flexible Behavior Synthesis.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Planning with Diffusion for Flexible Behavior Synthesis

Reference 24

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source=pdf_text observed=2026-08-10T16:40:58.710473Z digest=sha256:20e64b9154d724947b26693d1081feb6825bf863698499d45302727b5a221ec8

Observation e1b04afe-d38c-46ff-8339-9dc2bb8820a4 · outbound

This paper cites A review of power consumption models of servers in data centers.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling A review of power consumption models of servers in data centers

Reference 25

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

source=pdf_text observed=2026-08-10T16:40:58.716235Z digest=sha256:14dca13e3657813e6359a7e4858067fe94a3aefb88167b8ff038ccc1cd128465

Observation fbaff9f2-2a9a-40f6-b029-e1fe6a3b0c1b · outbound

This paper cites Joint message-passing and convex optimization framework for energy-efficient surveillance uav scheduling.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Joint message-passing and convex optimization framework for energy-efficient surveillance uav scheduling

Reference 26

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

source=pdf_text observed=2026-08-10T16:40:58.723006Z digest=sha256:dec8cd399eee55446a0a6e9daa25a5f00034e0886f13bd8fafc63c113a342513

Observation 7b0ea0a7-8470-4233-a8d5-66d4da652555 · outbound

This paper cites Factors influencing user satisfaction with information systems: A systematic review.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Factors influencing user satisfaction with information systems: A systematic review

Reference 27

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

source=pdf_text observed=2026-08-10T16:40:58.729342Z digest=sha256:9a6b6248c717e9c8338beaa37de04ebf4b14513fbaec0a90a48161251854642e

Observation 654d3078-4350-4a1f-a2a3-ee14c9ac217b · outbound

This paper cites Efficient diffusion policies for offline reinforcement learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Efficient diffusion policies for offline reinforcement learning

Reference 28

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raw_fallback, observed 2026-08-10T16:41:00.229034Z

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=2026-08-10T16:40:58.734764Z digest=sha256:93bb35f7790409b43432b63985e79d9feabb61e907aaf8391fe7faa78565fcc0

Observation 3b6f7418-db3f-4326-903a-dbde703a09ed · outbound

This paper cites Understanding diffusion objectives as the elbo with simple data augmentation.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Understanding diffusion objectives as the elbo with simple data augmentation

Reference 29

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raw_fallback, observed 2026-08-10T16:41:00.213827Z

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=2026-08-10T16:40:58.740296Z digest=sha256:62eb3419e185d730464c9bfa3fecea673872ff79496846d37edefb3aed816f97

Observation ac142bea-a9d7-49be-b880-8c11c7855f2f · outbound

This paper cites Variational diffusion models.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Variational diffusion models

Reference 30

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verified fuzzy
raw_fallback, observed 2026-08-10T16:41:00.198780Z

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=2026-08-10T16:40:58.745949Z digest=sha256:fc2d12a4539adf2be71d35cafbe33f0b3c6b196c0433a10d9f830cacd42caa9f

Observation d9e344b9-e39f-409a-a729-65b7af7b2344 · outbound

This paper cites Auto-Encoding Variational Bayes.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Auto-Encoding Variational Bayes

Reference 31

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.752517Z digest=sha256:ad372b9aad23cc1fe4668681a69eaa161dab5f4b81f56ccb72b15283a9c0a86c

Observation acd96393-adb9-462a-be53-5e87cfda4227 · outbound

This paper cites Optimization energy consumption with multiple mobile sinks using fuzzy logic in wireless sensor networks.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Optimization energy consumption with multiple mobile sinks using fuzzy logic in wireless sensor networks

Reference 32

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raw_fallback, observed 2026-08-10T16:41:00.183705Z

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=2026-08-10T16:40:58.758495Z digest=sha256:e8acbf7b52994a4e32504f4f318620036eec11a5640d929982281d020965b5ad

Observation 672d1320-f40f-4d34-b1d0-4503b38792b7 · outbound

This paper cites Offline reinforcement learn- ing with fisher divergence critic regularization.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Offline reinforcement learn- ing with fisher divergence critic regularization

Reference 33

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verified fuzzy
raw_fallback, observed 2026-08-10T16:41:00.168904Z

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=2026-08-10T16:40:58.763909Z digest=sha256:7a29089425a37737e074f9fcf654233a835c5f82e8c6664d69f8a49d643f22b9

Observation d8e7385d-8502-470f-a2ca-5b12e7b3c5c0 · outbound

This paper cites Offline Reinforcement Learning with Implicit Q-Learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Offline Reinforcement Learning with Implicit Q-Learning

Reference 34

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.770062Z digest=sha256:519e7c70680df29e5f2a52b42535fc1849b38d36b84983d97178e92a396abf89

Observation 3c62c3c6-bd08-47b8-b207-1267545e8b04 · outbound

This paper cites Stabilizing off- policy q-learning via bootstrapping error reduction.Advances in Neural Information Processing Systems, 32, 2019.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Stabilizing off- policy q-learning via bootstrapping error reduction.Advances in Neural Information Processing Systems, 32, 2019

Reference 35

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raw_fallback, observed 2026-08-10T16:41:00.153687Z

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=2026-08-10T16:40:58.776041Z digest=sha256:984f3d90ee305db096693b202b8f9b6665619bea5ecfe5fe5dfa0345c02ffa8d

Observation 1ddf8937-d414-44c8-a2cc-31856573c654 · outbound

This paper cites Conservative q-learning for offline reinforcement learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Conservative q-learning for offline reinforcement learning

Reference 36

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verified fuzzy
raw_fallback, observed 2026-08-10T16:41:00.137391Z

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=2026-08-10T16:40:58.781584Z digest=sha256:fb83c767b175235c2a52c64348b63ba8af6dfdf0cfeb5a507e20d44c0525adbb

Observation 38192390-e2ee-44c9-ab8a-1814ded3ad23 · outbound

This paper cites Batch reinforcement learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Batch reinforcement learning

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:41:00.122001Z

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=2026-08-10T16:40:58.786942Z digest=sha256:56dd14ca07b2d272c2d228a9f9dba22f3a4aeb8aa6877386a7c0ddbaf26d8b1c

Observation cc3b6395-d751-462e-8673-4a0b431a6ecb · outbound

This paper cites Graph colouring meets deep learning: Effective graph neural network models for combinatorial problems.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Graph colouring meets deep learning: Effective graph neural network models for combinatorial problems

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:41:00.105830Z

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=2026-08-10T16:40:58.792094Z digest=sha256:a4aebe88ec15c8ca301ece3ed653a2a4bfb8ab2135bd893ea10fbd121441652c

Observation 2dacc0a2-94b0-43fd-b8f6-cfa10a5dc082 · outbound

This paper cites Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Offline Reinforcement Learning: Tutorial, Review, and Perspectives on Open Problems

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T16:40:58.797435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.797435Z digest=sha256:3026fdfdf9e23314926d30a1b7aa31a6cceab0b4154b1a5435224cbbacb0a11b

Observation a1928940-b3ac-4414-9416-21b3b53b738b · outbound

This paper cites Low-carbon optimal learning scheduling of the power system based on carbon capture system and carbon emission flow theory.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Low-carbon optimal learning scheduling of the power system based on carbon capture system and carbon emission flow theory

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:41:00.088182Z

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=2026-08-10T16:40:58.802727Z digest=sha256:d3b0d93bd772338b07fcd8b08073cb231053ce7494309afd72407b69be648ade

Observation bdd5e070-d793-436b-a6ac-f2bbe715c980 · outbound

This paper cites Delay-aware vnf scheduling: A rein- forcement learning approach with variable action set.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Delay-aware vnf scheduling: A rein- forcement learning approach with variable action set

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:41:00.072716Z

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=2026-08-10T16:40:58.807989Z digest=sha256:e624756726d359e569ff1c563d4c3a3b9bb28776ece41d1c5c96b3de9830ce41

Observation 716d4f33-3d6a-4541-b088-438ae89425ae · outbound

This paper cites Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Towards an Information Theoretic Framework of Context-Based Offline Meta-Reinforcement Learning

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-10T16:40:58.813895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.813895Z digest=sha256:f25b85541fba5e537667c3bd1302b82f793290d4c31a73bb76a498c19d0ad967

Observation e1bdf852-3303-467d-9218-25a062571e51 · outbound

This paper cites Offline learning-based multi-user delay-constrained scheduling.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Offline learning-based multi-user delay-constrained scheduling

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:41:00.056482Z

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=2026-08-10T16:40:58.819785Z digest=sha256:f52f5251968f07a3529c2b4b36c5d3cc7d49b7721520b51fed99cd7f5aee7b33

Observation edc0878e-8664-48fc-9b74-1918e49aa937 · outbound

This paper cites Learning to schedule tasks with deadline and throughput constraints.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Learning to schedule tasks with deadline and throughput constraints

Reference 44

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:41:00.038843Z

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=2026-08-10T16:40:58.825320Z digest=sha256:37c72471b1e79c484195c95cc84da1faa4d0e37c2e589134ee07035a956286e5

Observation 13a0e78d-5d79-4644-a5df-13194e1e92ac · outbound

This paper cites Off-Policy Policy Gradient with State Distribution Correction.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Off-Policy Policy Gradient with State Distribution Correction

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-10T16:40:58.830677Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.830677Z digest=sha256:30a68bcf1c7a8a9ab9b69c2f6bac9490556e766af05c211e01e24f7085836ef9

Observation cc15a9e8-b67c-423d-a4f3-e712625eb00d · outbound

This paper cites an unresolved cited work.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Unresolved cited work

Reference 46

Resolution
unresolved
raw_fallback, observed 2026-08-10T16:41:00.021500Z

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=2026-08-10T16:40:58.836197Z digest=sha256:687248314052372f5231625baaa5e905b9e66ffdbc7d0fc8409892a8d5a28f64

Observation 1808da20-46da-4dda-977d-0d80b12d9684 · outbound

This paper cites Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-10T16:40:58.841613Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.841613Z digest=sha256:d627726c56bd56fe4bac27c65537471c7d9281454b5158ec02baa6d6e8300f7e

Observation 7d699583-982f-4f7d-b994-5376fdfd6079 · outbound

This paper cites Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-10T16:40:58.846992Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.846992Z digest=sha256:c01324b8671fe1aab8b9ffba2f2661eac5f1b71ba2ae5e107e1fd24e14479440

Observation 2b3ec48e-a301-407f-ba99-194f8a084100 · outbound

This paper cites Contract and lyapunov optimization-based load scheduling and energy management for uav charging stations.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Contract and lyapunov optimization-based load scheduling and energy management for uav charging stations

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.991204Z

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=2026-08-10T16:40:58.851959Z digest=sha256:fef5e7817e6905667f379a9bfbcdea05a32c566eda05b8cece79922987e90bff

Observation 10b05c39-daa2-4ce8-aba0-af038accb5cf · outbound

This paper cites Iteratively refined behavior regularization for offline reinforcement learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Iteratively refined behavior regularization for offline reinforcement learning

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.974884Z

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=2026-08-10T16:40:58.857824Z digest=sha256:0a4e5ed31cc514591fc11f56a7e497890045c2ecfe38a72c3d3090fe00a0bfdf

Observation 715cca1e-79e6-4341-acac-0269429a0c07 · outbound

This paper cites Neural adaptive video streaming with pensieve.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Neural adaptive video streaming with pensieve

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.958337Z

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=2026-08-10T16:40:58.863316Z digest=sha256:2499b418571007ad7e3141a679131e69608ad0540a7561e7548067c7df98f903

Observation baea1345-ff25-4361-b65d-eb11689dab01 · outbound

This paper cites A queuing theory model for fog computing.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling A queuing theory model for fog computing

Reference 52

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.941046Z

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=2026-08-10T16:40:58.868898Z digest=sha256:52cd1623b8484e2a40ce0c54052a258d6eb8bdbce562cde93adbd7e819cdd199

Observation 7478aea4-ebb0-40a2-892e-6cf35439073a · outbound

This paper cites Power allocation in multi-user cellular networks: Deep reinforcement learning approaches.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Power allocation in multi-user cellular networks: Deep reinforcement learning approaches

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.924972Z

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=2026-08-10T16:40:58.874203Z digest=sha256:95664eca59eea6a5421ce1e745c2387aa96f253901912639c0d2fb1dc9a94f0c

Observation 7f6f0cae-dab6-4f0e-a775-87e0cb76c850 · outbound

This paper cites AlgaeDICE: Policy Gradient from Arbitrary Experience.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling AlgaeDICE: Policy Gradient from Arbitrary Experience

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-10T16:40:58.879382Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.879382Z digest=sha256:4eda2c7cac98dd742d53c2bb2cfbe67b1d50bf8ac6f05afd4c141485db313951

Observation e0a0a6ad-a5f4-4081-8b7c-3ee819c78dc8 · outbound

This paper cites AWAC: Accelerating Online Reinforcement Learning with Offline Datasets.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling AWAC: Accelerating Online Reinforcement Learning with Offline Datasets

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-10T16:40:58.885002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.885002Z digest=sha256:d83296e180056a7cd862dfa822590ef357593b5bdcf5cbc47295935e8a53703d

Observation c85ed8bd-6c63-436e-812e-c01670288bca · outbound

This paper cites Multi-agent deep reinforcement learning for dynamic power allocation in wireless networks.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Multi-agent deep reinforcement learning for dynamic power allocation in wireless networks

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.909548Z

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=2026-08-10T16:40:58.898176Z digest=sha256:a2d96f7c69b59d4c88bfc7836536ef8a9c44efa475763176287909263bac5862

Observation 6287a856-fb44-4764-a4d6-d41d3da53147 · outbound

This paper cites Plan better amid conservatism: Offline multi-agent reinforcement learning with actor rectification.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Plan better amid conservatism: Offline multi-agent reinforcement learning with actor rectification

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.894039Z

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=2026-08-10T16:40:58.904171Z digest=sha256:c7ecd68843bada374cf11f407cc476d092d1791efd373f41bd7189489e316071

Observation d8845541-7245-4451-a686-35401b5bf420 · outbound

This paper cites Energy-optimal scheduling of mobile cloud computing based on a modified lyapunov optimization method.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Energy-optimal scheduling of mobile cloud computing based on a modified lyapunov optimization method

Reference 58

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.876244Z

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=2026-08-10T16:40:58.910065Z digest=sha256:fc35eccac9db352dc392fd9167559110c46f7cd5c94988caf27c1eeeaec98c9f

Observation a902bbbb-a3b9-416e-bfd3-8fb425cb0310 · outbound

This paper cites Energy-optimal scheduling of mobile cloud computing based on a modified lyapunov optimization method.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Energy-optimal scheduling of mobile cloud computing based on a modified lyapunov optimization method

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.858448Z

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=2026-08-10T16:40:58.915583Z digest=sha256:502ba78ee2316936fe43de6e4fe5bbe894525127bfb08fe50aab359358632284

Observation ee382915-9493-4040-b19d-5e364864e4ee · outbound

This paper cites Is Value Learning Really the Main Bottleneck in Offline RL?.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Is Value Learning Really the Main Bottleneck in Offline RL?

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-10T16:40:58.920844Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.920844Z digest=sha256:e2f1193f6e7b2bb21e4900932c037888046212208bc432eb5b0f1f61b4234865

Observation 75f07e48-7d15-4081-a532-2a1f6a126b8e · outbound

This paper cites Online convex optimization for caching networks.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Online convex optimization for caching networks

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.842918Z

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=2026-08-10T16:40:58.926481Z digest=sha256:8afe6ff816f6888c9b7d05096f8527f658734bf301de1818d91d3165e4550de8

Observation 27169377-e99f-4a47-b7e5-63db85401bc8 · outbound

This paper cites Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Advantage-Weighted Regression: Simple and Scalable Off-Policy Reinforcement Learning

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-10T16:40:58.931781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.931781Z digest=sha256:36d8cb8780e42b63ee8d2926ceb9568fdbef677ebcafd17faf33820394af9fef

Observation 3477d877-8561-4ea9-83fd-54a1b6bef99a · outbound

This paper cites Youtube live and twitch: a tour of user-generated live streaming systems.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Youtube live and twitch: a tour of user-generated live streaming systems

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.827064Z

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=2026-08-10T16:40:58.937285Z digest=sha256:4e1b47eab5daab7333bbd718439aecd510a1ea4b3f638a8ef2a1e4b6020a872e

Observation 60707021-027c-4a18-9d48-821e35b4b6f8 · outbound

This paper cites Learn- ing to solve np-complete problems: A graph neural network for decision tsp.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Learn- ing to solve np-complete problems: A graph neural network for decision tsp

Reference 64

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.811515Z

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=2026-08-10T16:40:58.942687Z digest=sha256:3c431ea8200e50309c7bbc71449b479b226929ee14167abd8323fe147547d241

Observation 3b828ae6-80a8-404e-a356-1c6b08dd9732 · outbound

This paper cites Class-balancing diffusion models.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Class-balancing diffusion models

Reference 65

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.794331Z

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=2026-08-10T16:40:58.948157Z digest=sha256:a62b7c3a6cbf750dcaaf0c43901af6e31716bbfcd3deb561fcf65d3d79e800e1

Observation d2346cf3-6fde-4b68-b25e-fec4eb91a6dc · outbound

This paper cites Random features for large-scale kernel machines.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Random features for large-scale kernel machines

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-10T16:40:58.953805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.953805Z digest=sha256:1dabfb88d1d0375bfba8c2a7c3da450298bf513ba66a2dd38f93d446106d197e

Observation 3079ee55-f0ac-45b6-9904-474566542cbc · outbound

This paper cites Searching for Activation Functions.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Searching for Activation Functions

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-10T16:40:58.958862Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.958862Z digest=sha256:66c665d5f8143cc7cb2d72eb0eac3f3f95074077cd84a388f2289a74912cef09

Observation c5f76dce-ddc7-4719-a28b-8e2922728989 · outbound

This paper cites Hierarchical Text-Conditional Image Generation with CLIP Latents.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Hierarchical Text-Conditional Image Generation with CLIP Latents

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-10T16:40:58.964581Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.964581Z digest=sha256:38f366ac3d806838d0f0cc63bec265450948ca42da5b985d01c6b0d0ceb426b5

Observation f83ec46b-f3ff-4b33-9283-d55b0603c44e · outbound

This paper cites Offline reinforcement learning as anti-exploration.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Offline reinforcement learning as anti-exploration

Reference 69

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.767787Z

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=2026-08-10T16:40:58.970169Z digest=sha256:17230a0f9077b8ede06a5f9eb137c047b3198e838b7bea156f8567332d706de6

Observation 4ca6f296-4bbf-4d52-8db4-2915e48c5f4b · outbound

This paper cites Simple near-optimal scheduling for the m/g/1.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Simple near-optimal scheduling for the m/g/1

Reference 70

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.751498Z

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=2026-08-10T16:40:58.975630Z digest=sha256:75bb7f4ac978e693cfa466efd2c0f3f2e9e582c2a70c6cd0f50d65213997f13c

Observation b3654b1a-bf95-4193-866f-8d1f87e5cc99 · outbound

This paper cites Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Keep Doing What Worked: Behavioral Modelling Priors for Offline Reinforcement Learning

Reference 71

Resolution
unresolved
no resolver link, observed 2026-08-10T16:40:58.980888Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.980888Z digest=sha256:c481a287345826fd716ab1f274f87f42105248f1e366cac0525bea023233cc60

Observation 155b2081-36ce-4ed5-9bae-03935ffcafd0 · outbound

This paper cites an unresolved cited work.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Unresolved cited work

Reference 72

Resolution
unresolved
raw_fallback, observed 2026-08-10T16:40:59.735764Z

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=2026-08-10T16:40:58.986341Z digest=sha256:f826b0f3e1db069d75c6b7958bc241395850aaa1a847d4d7f76d5de34b942111

Observation 6a4740bd-2ef7-4c2c-8718-8cd00c051684 · outbound

This paper cites Deep unsuper- vised learning using nonequilibrium thermodynamics.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Deep unsuper- vised learning using nonequilibrium thermodynamics

Reference 73

Resolution
unresolved
no resolver link, observed 2026-08-10T16:40:58.991479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:58.991479Z digest=sha256:4c3d1ca42ba346ebcf2c53b2f9b6391dc3776adf24f443d1e8983dc155da0c92

Observation 31a4bea0-2260-4282-9c83-976d571a5418 · outbound

This paper cites Denoising Diffusion Implicit Models.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Denoising Diffusion Implicit Models

Reference 74

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source=pdf_text observed=2026-08-10T16:40:58.997183Z digest=sha256:36c09193681898293287381166fcc70bf2fe839f5614dbd85edbd4e6394e77de

Observation 2ba50498-f344-4bc4-ad93-00a77705a96b · outbound

This paper cites Generative modeling by estimating gradients of the data distribution.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Generative modeling by estimating gradients of the data distribution

Reference 75

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no resolver link, observed 2026-08-10T16:40:59.002715Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:59.002715Z digest=sha256:3bbce0def3c1ad7863b9077bcfab85e0b952edb1a07b15b3f1905236d4a851dc

Observation d679a13a-7d1a-4ec2-853e-f057dfc106c2 · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Score-Based Generative Modeling through Stochastic Differential Equations

Reference 76

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unresolved
no resolver link, observed 2026-08-10T16:40:59.008316Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:59.008316Z digest=sha256:efa77bcf36d8908a5204d72ccac20c1e1e7d507b51f98bfa23210c7f531920a3

Observation a472f1b7-239b-4f79-9aff-ae00314396b7 · outbound

This paper cites Batch learning from logged bandit feed- back through counterfactual risk minimization.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Batch learning from logged bandit feed- back through counterfactual risk minimization

Reference 77

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verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.695269Z

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=2026-08-10T16:40:59.013751Z digest=sha256:afb8c64bdae6b724a3f339b6988738fea9668e9c57a245072d3f796f07719c27

Observation 97bd790a-496e-49a8-939c-75451e36270d · outbound

This paper cites Minimizing age of information with power constraints: Multi-user opportunistic scheduling in multi-state time-varying channels.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Minimizing age of information with power constraints: Multi-user opportunistic scheduling in multi-state time-varying channels

Reference 78

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verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.678183Z

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=2026-08-10T16:40:59.019238Z digest=sha256:54f0bdf769dc7258aca10fdeec030fd9f61a0bd234638e5749d8f30f5f4bae69

Observation 531f037a-cb62-40f1-a0fc-d8b5e5acf91e · outbound

This paper cites Taotao, X.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Taotao, X

Reference 79

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verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.661960Z

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=2026-08-10T16:40:59.024473Z digest=sha256:7a0246814b3a7ac6107a472d86f12e99137290364ba5c5d4c147a792b5d6058d

Observation 6dfcf16c-fcf9-4b8b-bd50-75a27378687b · outbound

This paper cites Learning combinatorial optimization on graphs: A survey with applications to networking.IEEE Access, 8:120388–120416, 2020.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Learning combinatorial optimization on graphs: A survey with applications to networking.IEEE Access, 8:120388–120416, 2020

Reference 80

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verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.646262Z

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=2026-08-10T16:40:59.029699Z digest=sha256:ca78b072ec5bf4374feac6137f6046c404df83508b77c71b825f8d54e69b7176

Observation 896443db-3b0a-4039-a882-2aee1f53b849 · outbound

This paper cites Scheduling real-time wireless traffic: A network-aided offline reinforcement learning approach.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Scheduling real-time wireless traffic: A network-aided offline reinforcement learning approach

Reference 81

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verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.629238Z

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=2026-08-10T16:40:59.034952Z digest=sha256:e1f78c970385c88dec779bbd2ad796520b1b984563bd5476adac1fe21d8f5bd2

Observation b679d4b7-349c-4b7c-ab55-bb7b16450d45 · outbound

This paper cites Logistics-involved task scheduling in cloud manufacturing with offline deep reinforcement learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Logistics-involved task scheduling in cloud manufacturing with offline deep reinforcement learning

Reference 82

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verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.611236Z

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=2026-08-10T16:40:59.040575Z digest=sha256:745ac9da7a05169b453cabc323baf4c9a3c0608acc7dc5e04fabe22fa44a058e

Observation aad60dac-a116-4642-b486-1529543fe211 · outbound

This paper cites Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning

Reference 83

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no resolver link, observed 2026-08-10T16:40:59.046141Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:59.046141Z digest=sha256:24249337743c4b3ffe9a844612d13b453c8eed525eb1250aa1fa4528d11109f5

Observation 337eb5b7-8272-46fe-b0b7-2dc0357b8d8c · outbound

This paper cites Pro- lificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Pro- lificdreamer: High-fidelity and diverse text-to-3d generation with variational score distillation

Reference 84

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verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.595003Z

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=2026-08-10T16:40:59.051730Z digest=sha256:0998a8737ca04d504aed53b8996bc091cc73181d4e05b4b6a13ba7729e5dbbcf

Observation d3af3dad-5843-4e3a-8d2c-39a438ec8b83 · outbound

This paper cites Behavior Regularized Offline Reinforcement Learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Behavior Regularized Offline Reinforcement Learning

Reference 85

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no resolver link, observed 2026-08-10T16:40:59.057244Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T16:40:59.057244Z digest=sha256:7ad4cb41b60107068a54735369aaf3fbd15464e1d71b9fd247cfe0e131c12dbc

Observation 02fe5a04-1f6a-4738-82cd-92d1976399d8 · outbound

This paper cites Understanding instant messaging traffic characteristics.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Understanding instant messaging traffic characteristics

Reference 86

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.578295Z

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=2026-08-10T16:40:59.062825Z digest=sha256:4709bca106782d88dd54d615e3b95a3d8b1ec7bc466103ac8e24b9862eda64fb

Observation 1f6a8f42-2456-482d-9ba8-8fc1436aa01c · outbound

This paper cites Offline reinforcement learning for wireless network optimization with mixture datasets.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Offline reinforcement learning for wireless network optimization with mixture datasets

Reference 87

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.561972Z

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=2026-08-10T16:40:59.068106Z digest=sha256:63af63105e6622a1037780bc77dfe101c75cc5241187c05f4387cb6714a43744

Observation 57dc52da-0a73-4d4d-8da5-0c082b2265f2 · outbound

This paper cites Reles: A neural adaptive multipath scheduler based on deep reinforcement learning.

Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling Reles: A neural adaptive multipath scheduler based on deep reinforcement learning

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T16:40:59.545078Z

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=2026-08-10T16:40:59.073705Z digest=sha256:183a2412884117f765f0295dfaf455dd035c3c5a147344cde322081e6651c616

Pith citing papers

Observation b4528eaa-c0ac-4312-ab8e-bea7a54b166c · inbound

Censored Sampling for Topology Design: Guiding Diffusion with Human Preferences cites this paper.

Censored Sampling for Topology Design: Guiding Diffusion with Human Preferences Offline Diffusion Policy for Multi-User Delay-Constrained Scheduling

Reference 222

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verified exact
local_arxiv, observed 2026-08-06T05:35:41.976756Z

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=2026-08-06T05:35:40.449647Z digest=sha256:e3a0d6a76a8c067bf18d59040d6a7823ab59a60d279456f751503051c540d7d9