Pith. sign in

Paper Citation Record · LEDGER

Secure Resource Allocation via Constrained Deep Reinforcement Learning

As of 11 August 2026, this Paper Citation Record lists 54 of 54 outbound references and 0 inbound Pith citation observations for arXiv:2501.11557.

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

pith.paper-citation-record.v1
2501.11557 v1

Coverage vector

measured 54 of 54 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-10T18:12:33.406433Z

measured 54 of 54 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

54 of 54 outbound references displayed

  • verified exact3
  • verified fuzzy35
  • unresolved16
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 14a41f60-36ef-4dcb-880e-1280d77aab20 · outbound

This paper cites Efficient par- allel split learning over resource-constrained wireless edge networks,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Efficient par- allel split learning over resource-constrained wireless edge networks,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.609706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.149432Z digest=sha256:229f29d284e8845e7eaa2623168b630ea165627ac680a21e30e16bca22692605

Observation 142fdee3-62b7-4252-bc2b-3f7dee15657b · outbound

This paper cites Constructing 4D Radio Map in LEO Satellite Networks with Limited Samples.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Constructing 4D Radio Map in LEO Satellite Networks with Limited Samples

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.155989Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.155989Z digest=sha256:49818c45fea71c4991d8f9928d2fa61008b515b8352b9d600e9496c14d97ecd4

Observation 14f5558f-2646-4d85-a993-8a200889f7a8 · outbound

This paper cites LEO-Split: A Semi-Supervised Split Learning Framework over LEO Satellite Networks.

Secure Resource Allocation via Constrained Deep Reinforcement Learning LEO-Split: A Semi-Supervised Split Learning Framework over LEO Satellite Networks

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.161216Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.161216Z digest=sha256:a9acd32c39ae6156bc4ea85226cf57ad271032ff94d596e5a390cc286fde685d

Observation 58662088-05f5-41bd-af87-d5c2ce3813f3 · outbound

This paper cites Vulseye: Detect Smart Contract Vulnerabilities via Stateful Directed Graybox Fuzzing.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Vulseye: Detect Smart Contract Vulnerabilities via Stateful Directed Graybox Fuzzing

Reference 4

Resolution
verified exact
local_arxiv, observed 2026-08-10T18:12:33.998710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.166411Z digest=sha256:9f107eeeffdd41c5f1c57c147d309e113010b09a5b4f4e36e0f26b7be396e4ef

Observation b9a4b0bb-f457-4279-aa7c-b3907cabdfff · outbound

This paper cites Graphlearningformulti-satellitebasedspectrumsensing,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Graphlearningformulti-satellitebasedspectrumsensing,

Reference 5

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.592662Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.171834Z digest=sha256:2e878dc54da37cce88f798f728845d5519b0d63df4d2366d34f3902c0d5c9cb6

Observation acd8479d-c395-4ee0-8144-8796dc21909e · outbound

This paper cites Optimizing the learning performance in mobile augmented reality systems with cnn,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Optimizing the learning performance in mobile augmented reality systems with cnn,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.577474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.176665Z digest=sha256:b872f03065ea8cffef253467fe7b9a8dc3fb8d600f8c826bf6b9c1a8b7a9b4bb

Observation 001716cc-562e-4610-a13a-4bbb9da2fe48 · outbound

This paper cites Deep-learning-incorporated aug- mented reality application for engineering lab training,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Deep-learning-incorporated aug- mented reality application for engineering lab training,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.561597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.182319Z digest=sha256:c0a1df04e03f4161b406b0def02542163029b99ee9f9153d8d3426c5785ed2cd

Observation 5de1a033-b75e-4b93-88d2-2e6d71c33a3d · outbound

This paper cites Integrated registration and oc- clusion handling based on deep learning for augmented-reality-assisted assembly instruction,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Integrated registration and oc- clusion handling based on deep learning for augmented-reality-assisted assembly instruction,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.546333Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.186993Z digest=sha256:709097a0c2a8595f9c2f14edddedbf29ac46f72dae69b98cfef5ac6e57802084

Observation 4efe9ddd-c4ab-4942-b331-c4035039ec07 · outbound

This paper cites Tracking and transmission design in terahertz v2i networks,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Tracking and transmission design in terahertz v2i networks,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.530719Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.191490Z digest=sha256:1e64437b5300b64b74942257044132971d8ce173f67ab4c21f136b49e700591b

Observation 8fefa7cf-e71f-43c4-a95b-3657f32e6d89 · outbound

This paper cites IC3M: In-Car Multimodal Multi-object Monitoring for Abnormal Status of Both Driver and Passengers.

Secure Resource Allocation via Constrained Deep Reinforcement Learning IC3M: In-Car Multimodal Multi-object Monitoring for Abnormal Status of Both Driver and Passengers

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.196029Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.196029Z digest=sha256:6c8b2de6a9c19a26e13a664d4c6595218cdab0799894c8c5be76fcbb7abafd58

Observation 2ce5b163-f1d1-4f15-9e5a-d9f54bb43960 · outbound

This paper cites Channel power gain estimation for terahertz vehicle-to-infrastructure networks,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Channel power gain estimation for terahertz vehicle-to-infrastructure networks,

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.201440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.201440Z digest=sha256:93292849924cbc55c4269554a7385288afbdbf0eb65e2c6166dff8989343de71

Observation ee073f04-3c37-419b-9891-98b5066a419c · outbound

This paper cites Rethinking membership inference attacks against transfer learning,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Rethinking membership inference attacks against transfer learning,

Reference 12

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.505198Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.206445Z digest=sha256:6cd8cb3cf30176b0a8be59e8380288e9f7ca5dc374581d27ac368929c492ee03

Observation a71f5939-1a2f-4bbd-a169-b7490ba4d4c7 · outbound

This paper cites FedAC: An Adaptive Clustered Federated Learning Framework for Heterogeneous Data.

Secure Resource Allocation via Constrained Deep Reinforcement Learning FedAC: An Adaptive Clustered Federated Learning Framework for Heterogeneous Data

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.211405Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.211405Z digest=sha256:753c48a6d0355fe9f0d74bf1d2c5c6bca6142ad564631770e2c0751a7102e837

Observation 6d73016f-b1f3-4c56-ac2b-2df19e454673 · outbound

This paper cites Multi-layer computation offload- ing in distributed heterogeneous mobile edge computing networks,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Multi-layer computation offload- ing in distributed heterogeneous mobile edge computing networks,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.490000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.216597Z digest=sha256:76fea33e0a03e1c5e28b073be518b0bc584a1470747b8a02e454a577b914adb8

Observation 16bfb32c-f89c-4cea-8021-52feac6fdee6 · outbound

This paper cites Secure channel establishment scheme for task delivery in vehicular cloud computing,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Secure channel establishment scheme for task delivery in vehicular cloud computing,

Reference 15

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.474408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.221179Z digest=sha256:d5efdfa33f126f8b8675696e58473e048d3ced5c889fe9a7d53b55c0281f651f

Observation dcc728ca-b186-425c-85e9-eba6cf83e8fb · outbound

This paper cites Hierarchical Split Federated Learning: Convergence Analysis and System Optimization.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Hierarchical Split Federated Learning: Convergence Analysis and System Optimization

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.226075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.226075Z digest=sha256:c4cd755984ca9effb2f062b55cb75bb87a8deac0e8ddd8f4c37c1707a0d15ce3

Observation 4d7163bf-4f00-4ed3-bc5f-0d8cce2649bf · outbound

This paper cites Adaptive resource allo- cation for semantic communication networks,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Adaptive resource allo- cation for semantic communication networks,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.457930Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.231217Z digest=sha256:77afbd2128980e293dbf2f3a51d29364cabb3d5a4f90cae2da8491b6a09e1255

Observation d65650d1-ef5f-4762-b932-379bf497bb8f · outbound

This paper cites Resource allocation and trust computing for blockchain-enabled edge computing system,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Resource allocation and trust computing for blockchain-enabled edge computing system,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.442136Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.235632Z digest=sha256:8e73c5b1c8d4ed3452b0d31ada1586c6422209993ba6dccda3d7124381ba60c4

Observation c78a9129-8bb1-4f4a-b0c1-039e2171c0d9 · outbound

This paper cites Resource Allocation and Workload Scheduling for Large-Scale Distributed Deep Learning: A Survey.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Resource Allocation and Workload Scheduling for Large-Scale Distributed Deep Learning: A Survey

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.240343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.240343Z digest=sha256:15861b971b0339dddd4152d9bc6b550b571b08b450ac7e5163b43066b9e5375a

Observation 3ec7a42c-3de9-412a-aecf-88c2161459ed · outbound

This paper cites Fedsn: A federated learning framework over heterogeneous leo satellite networks,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Fedsn: A federated learning framework over heterogeneous leo satellite networks,

Reference 20

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.423237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.245155Z digest=sha256:139024199e2a11aaf219b868643ead3c31d5429cdece1f5827dbba6b8f93046a

Observation 14a6da1f-75f2-49f6-ae0b-4937b208463b · outbound

This paper cites Privacyeafl: Privacy-enhanced ag- gregation for federated learning in mobile crowdsensing,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Privacyeafl: Privacy-enhanced ag- gregation for federated learning in mobile crowdsensing,

Reference 21

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.405895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.249851Z digest=sha256:ea86db02fa7c2995331e1af6fee08e36fe796a897800e7e371278922ce526f61

Observation 709ac1ef-499c-49d5-8a72-8f06bfc21332 · outbound

This paper cites Distributed task scheduling in serverless edge computing networks for the internet of things: A learning approach,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Distributed task scheduling in serverless edge computing networks for the internet of things: A learning approach,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.388412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.254391Z digest=sha256:2782a0bf34034bcdd04a2c4854cd9fda7e889eb00c33ac49c7cd0fd2a0d6bf0a

Observation 95970bd2-973c-44d1-9d47-353733de15c9 · outbound

This paper cites Performance optimization of serverless edge computing function offloading based on deep reinforcement learning,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Performance optimization of serverless edge computing function offloading based on deep reinforcement learning,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.372618Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.258855Z digest=sha256:3be5382a08d07a377ecc7129b6b2e0de911c933fa203fa6c8613b7675e44e415

Observation f79209d8-1d40-4daf-9ceb-e47a8d318aee · outbound

This paper cites Learning-based privacy-aware offloading for healthcare iot with energy harvesting,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Learning-based privacy-aware offloading for healthcare iot with energy harvesting,

Reference 24

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.357892Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.264681Z digest=sha256:a2cdbfd5ac9bae87980d0f0f2d4266aed8fc0f27dfd6cedd9a5428ccdf72e3d7

Observation ec09e4bb-f49c-42e1-984b-45e3c0f4869d · outbound

This paper cites Security modeling and efficient computation offloading for service workflow in mobile edge computing,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Security modeling and efficient computation offloading for service workflow in mobile edge computing,

Reference 25

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.342196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.269324Z digest=sha256:bbddb49a2da8b65f2d0f2a4a2379c56b781ef388f630f637be331ff4a17a7f56

Observation a9ed7a0f-a53c-4e06-a9a5-e8d652b0d461 · outbound

This paper cites Performance optimization of serverless comput- ing for latency-guaranteed and energy-efficient task offloading in energy-harvesting industrial iot,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Performance optimization of serverless comput- ing for latency-guaranteed and energy-efficient task offloading in energy-harvesting industrial iot,

Reference 26

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.326546Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.274009Z digest=sha256:7bea6930adfc12175c8d69fb9721c286be890564c5b754b34c8544445c33d9d3

Observation 681b7147-b76c-4d02-9102-72a050aa2834 · outbound

This paper cites Architecture and performance evalu- ation of distributed computation offloading in edge computing,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Architecture and performance evalu- ation of distributed computation offloading in edge computing,

Reference 27

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.308569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.278541Z digest=sha256:6f5c55a1fdc87f7d129279da0fd91b34393a388d46ac34fdac247d8f8759f28a

Observation cc5886d3-b200-4547-89e7-d1a68860465d · outbound

This paper cites Multi-cloud provisioning and load distribution for three- tier applications,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Multi-cloud provisioning and load distribution for three- tier applications,

Reference 28

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.292252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.283163Z digest=sha256:c7973ff198dbc2b683212f4573260291c3230fa77e21181a287b83a3f447a61e

Observation 9a8e1c54-b598-476f-a6d1-fd6bf02fe335 · outbound

This paper cites Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Automated Federated Pipeline for Parameter-Efficient Fine-Tuning of Large Language Models

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.287905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.287905Z digest=sha256:318c675fd3ad7ef2eda4ec90e511d61600002f732b49018ee623eccff4355a67

Observation 99d29b04-55cc-40e8-be9d-0e464ce6ad3c · outbound

This paper cites Security computing resource allocation based on deep reinforcement learning in serverless multi-cloud edge computing,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Security computing resource allocation based on deep reinforcement learning in serverless multi-cloud edge computing,

Reference 30

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.275488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.292799Z digest=sha256:73c28f60029bd36fd48b3739af1166770c3a92b560651f19dc2b7352dcdc00a6

Observation ec709280-c27e-4a2a-bc99-aef055583e2a · outbound

This paper cites Efficientand secure multi-user multi-task computation offloading for mobile-edge computing in mobile iot networks,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Efficientand secure multi-user multi-task computation offloading for mobile-edge computing in mobile iot networks,

Reference 31

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.257168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.297789Z digest=sha256:5635e885e86b85175b20e2e7b71fc978d30ab31f71b3afb08796e33c7eefe717

Observation cebf93dd-128e-425f-982c-38df68543434 · outbound

This paper cites Service offloading with deep q-network for digital twinning-empowered internet of vehicles in edge computing,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Service offloading with deep q-network for digital twinning-empowered internet of vehicles in edge computing,

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.240129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.302449Z digest=sha256:74ca327ca66767f7c7d7863122edb15ee8cedaef4e9e6d2495a566b5320aaff6

Observation e6cfcdd1-c9d1-43fd-b49b-852c551e02d1 · outbound

This paper cites Multiuser computation offloading and resource allocation for cloud–edge heterogeneous network,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Multiuser computation offloading and resource allocation for cloud–edge heterogeneous network,

Reference 33

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.224429Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.306958Z digest=sha256:079cd39fe77b0d9bcba524a7434991667d413c6068f8ee7bc70420f45073b794

Observation 7f0ef7e4-1db6-41bf-a809-458e8d5a51ce · outbound

This paper cites Echohand: High accu- racy and presentation attack resistant hand authentication on commodity mobile devices,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Echohand: High accu- racy and presentation attack resistant hand authentication on commodity mobile devices,

Reference 34

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.209699Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.311377Z digest=sha256:f3d4c7f2bbfa0fe1f4a238703e17c67744c6d1ad913170bcacb18579c63f16e2

Observation 35b444d7-b80f-4084-ae03-0a74427f5d4a · outbound

This paper cites Rethinking Adversarial Attacks in Reinforcement Learning from Policy Distribution Perspective.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Rethinking Adversarial Attacks in Reinforcement Learning from Policy Distribution Perspective

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.315816Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.315816Z digest=sha256:ee7ab8314271bf435dae7eedeed9b751ae78b974c15c8f615c2305bbc58e88de

Observation 65529fd0-9a55-478d-adbf-204790ed2999 · outbound

This paper cites Toward robust detection of pup- pet attacks via characterizing fingertip-touch behaviors,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Toward robust detection of pup- pet attacks via characterizing fingertip-touch behaviors,

Reference 36

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.193866Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.320383Z digest=sha256:c165a772fc39328f8d646bd233dc2bf469316dd9cac59163fb4f85a22dbb20b8

Observation d0480588-75b1-4298-8bb4-5f14cee7c77c · outbound

This paper cites Sok: Comprehensive Security Overview, Challenges, and Future Directions of Voice-Controlled Systems.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Sok: Comprehensive Security Overview, Challenges, and Future Directions of Voice-Controlled Systems

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.324945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.324945Z digest=sha256:44abfa7d1a93bb63ac6fc6a3939930a9bd3a4c6dbb70cbea828d157bee611ae8

Observation 9ae5155f-877a-4739-98e4-17c163995138 · outbound

This paper cites Liveness is not enough: Enhancing fingerprint authentication with behavioral biometrics to defeat puppet attacks,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Liveness is not enough: Enhancing fingerprint authentication with behavioral biometrics to defeat puppet attacks,

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.178128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.329557Z digest=sha256:636d71a49e8e5405c46de0317473c874f1a5a3ee9bec042008c4f8a74d25db39

Observation 97e167d4-b737-4c35-a045-291a5268a5a2 · outbound

This paper cites Pushing Large Language Models to the 6G Edge: Vision, Challenges, and Opportunities.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Pushing Large Language Models to the 6G Edge: Vision, Challenges, and Opportunities

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.334140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.334140Z digest=sha256:150bfe27e42a66a20a935a0540acfd9b33e3dd8a7e38de87a29755b5e69ba45f

Observation 09dde82a-7d00-4909-adfd-f8bdfe6148df · outbound

This paper cites Semantic sleuth: Identifying ponzi contracts via large language models,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Semantic sleuth: Identifying ponzi contracts via large language models,

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.162098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.339210Z digest=sha256:709ba63e683f166c59dfd6487065362556263d8801ab52bc1542f487a4eaa187

Observation 75694066-c9e1-4593-999f-66ddf282e8d1 · outbound

This paper cites AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks.

Secure Resource Allocation via Constrained Deep Reinforcement Learning AdaptSFL: Adaptive Split Federated Learning in Resource-constrained Edge Networks

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.343977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.343977Z digest=sha256:1c865e17b3a7d1afcc7d410e876da2423bf9a3030b5b480c458f359d3dde4e64

Observation 54ae8711-834c-43bd-8a40-d0073a54adf2 · outbound

This paper cites LCFed: An Efficient Clustered Federated Learning Framework for Heterogeneous Data.

Secure Resource Allocation via Constrained Deep Reinforcement Learning LCFed: An Efficient Clustered Federated Learning Framework for Heterogeneous Data

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.348628Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.348628Z digest=sha256:9bea63ba46a31c539670f349701ee1d643e5a119c39b559f704f9e0c91fc2ae6

Observation 4ebe8645-3068-4174-92e8-153fcac3caac · outbound

This paper cites Split learning in 6g edge networks,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Split learning in 6g edge networks,

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.145890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.353509Z digest=sha256:04512bb77b5e4247f6463a515cbcc6c003bf43c0f6ed9166b291ddabaed267c7

Observation a541410d-acd2-46a5-8e34-2c462750e48f · outbound

This paper cites Source Code Summarization in the Era of Large Language Models.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Source Code Summarization in the Era of Large Language Models

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.358386Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.358386Z digest=sha256:b5c9a8bbf899c967b76ee69097f94847921a49367fc5d93a2bf46082a3b90d7d

Observation a115d82f-56b4-4585-b2b4-12893888ab5b · outbound

This paper cites A survey of source code search: A 3-dimensional perspective,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning A survey of source code search: A 3-dimensional perspective,

Reference 45

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.127948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.363643Z digest=sha256:d18ea1e23d03964475741c9ae8d86f771472c52ae016399d901bb7807a265c31

Observation 3070b3a5-2f2d-4932-99f7-86baf7b559c6 · outbound

This paper cites An extractive-and-abstractive framework for source code summarization,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning An extractive-and-abstractive framework for source code summarization,

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.110162Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.368264Z digest=sha256:9ecda388ce2621916653d5363c84c11df3480fd918a1a6f4cf2af76a7326ffdc

Observation bcfe4d23-988a-4418-b4c2-ed62ea4adb18 · outbound

This paper cites Esale: Enhancing code-summary alignment learning for source code summarization,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Esale: Enhancing code-summary alignment learning for source code summarization,

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.094576Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.373045Z digest=sha256:24e86da5a4ad20fb0399c4b4d8552ba91827ca7a1cfef6b591ce84d179f31d88

Observation cec5c2f7-a067-4aed-8bdd-007c65a43cc0 · outbound

This paper cites Abstract Syntax Tree for Programming Language Understanding and Representation: How Far Are We?.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Abstract Syntax Tree for Programming Language Understanding and Representation: How Far Are We?

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.377782Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.377782Z digest=sha256:55cc454cc3218d4531c2d11422311bb1a6fc18afbdee529ec214cd1f5bc0ba86

Observation 88d9c00b-a0ad-473b-87bc-73edabb64dd6 · outbound

This paper cites Maf: Method-anchored test fragmentation for test code plagiarism detection,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Maf: Method-anchored test fragmentation for test code plagiarism detection,

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.078406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.382507Z digest=sha256:1c23eaecc4e7bcd5848f1497a7ac88ed6e3086b0922466fd7c400618e890423c

Observation d1fb795d-8d99-407c-9cec-23454e593381 · outbound

This paper cites Backdooring neural code search,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Backdooring neural code search,

Reference 50

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.062002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.387067Z digest=sha256:d2326e35b842f84e211736d01ba844ae84a0c688f6bfbe2b4fce38274cf794c2

Observation 70e3764c-98a3-470d-8a09-da720d6f47fe · outbound

This paper cites Eliminating Backdoors in Neural Code Models for Secure Code Understanding.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Eliminating Backdoors in Neural Code Models for Secure Code Understanding

Reference 51

Resolution
verified exact
local_arxiv, observed 2026-08-10T18:12:33.797652Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.391579Z digest=sha256:d5815fb9761a48b84f3e4ccabc16dcd4621f82c5836bbd395de87c1ba94c6f79

Observation fbef4f13-fa52-44b5-b536-f9d10a51f61c · outbound

This paper cites Mu- tual information guided backdoor mitigation for pre-trained encoders,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning Mu- tual information guided backdoor mitigation for pre-trained encoders,

Reference 52

Resolution
verified exact
raw_fallback, observed 2026-08-10T18:12:33.770411Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.396607Z digest=sha256:5b1bb63e44d728f98acbf33d5b80404a7e68cb47fade9730f4664a0a7d93f3cb

Observation 6e91c037-313a-4e6b-9c09-fe5de4159889 · outbound

This paper cites On the effectiveness of distillation in mitigating backdoors in pre-trained encoder,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning On the effectiveness of distillation in mitigating backdoors in pre-trained encoder,

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-10T18:12:33.401777Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T18:12:33.401777Z digest=sha256:43c2c6c9a622491e46fc615cf1b8df9aaf377d3fe3b47c075ece3a1676ace8ac

Observation 97fa974c-51b5-4e7e-8a9c-bdb42d77217e · outbound

This paper cites RULER: discriminative and iterative adversarial training for deep neural network fairness,.

Secure Resource Allocation via Constrained Deep Reinforcement Learning RULER: discriminative and iterative adversarial training for deep neural network fairness,

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-10T18:12:34.045645Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

source=pdf_text observed=2026-08-10T18:12:33.406433Z digest=sha256:dbf88d10df13192f1493e3c7384390636f4c495b445f9ab650e0d2d9305f858f

Pith citing papers

No inbound Pith citation observations are available.