Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T10:40:51.693935Z
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 50 of 50 outbound references and 0 inbound Pith citation observations for arXiv:2508.00938.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T10:40:51.693935Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
50 of 50 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 7fa0f461-c2bb-405d-b748-fc50df069362 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Accurate medium-range global weather forecasting with 3d neural networks,
Reference 1
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Observation e45b6e88-2271-4a69-b841-bf579eda3eca · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning A survey on time-series pre-trained models,
Reference 2
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Observation dba89d86-951c-4e01-94c8-fa4c9cc29796 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Spatial-Temporal Data Mining for Ocean Science: Data, Methodologies, and Opportunities
Reference 3
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Observation c531a12e-4e98-4b3f-8711-1e29356f75ce · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Ocean currents show global intensification of weak tropical cyclones,
Reference 4
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Observation 655b24e5-1787-4c33-9b67-fade82a491c4 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning El ni˜no–southern oscillation complexity,
Reference 5
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Observation 17c0e7e1-22cc-49ad-a49c-7f66b5f85de9 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning The circulation of the eastern tropical pacific: A review,
Reference 6
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Observation 9a68a1a2-25ba-4fca-ad5c-cd03cfb1d2d9 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Improving language understanding by generative pre-training,
Reference 7
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Observation 649061eb-d988-4893-870b-506ee17b77fc · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning LLaMA: Open and Efficient Foundation Language Models
Reference 8
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Observation 8a4f2237-bf8a-49a7-ba47-4954c25eeb42 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning DeepSeek-V3 Technical Report
Reference 9
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Observation 7b3bd770-77e9-415c-aadb-e83673708502 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Mixed-order relation-aware recurrent neural networks for spatio-temporal forecast- ing,
Reference 10
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Observation 9069ec98-a6fa-4035-984c-a0f315e36a88 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning One fits all: Power general time series analysis by pretrained lm,
Reference 11
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Observation 21b8521d-5693-431b-8ac1-39ed5b3964e9 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Unitime: A language-empowered unified model for cross-domain time series forecasting,
Reference 12
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Observation 816d11de-965f-4a58-b08e-2afe3b807163 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Time-LLM: Time series forecasting by reprogramming large language models,
Reference 13
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Observation 064fc0cf-b6cb-4fb9-a494-c82e57a30ec4 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Position paper: What can large language models tell us about time series analysis,
Reference 14
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Observation 8e445b05-2952-4566-9a9c-6c701ab8af8b · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Tempo: Prompt-based generative pre-trained transformer for time series forecasting,
Reference 15
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Observation c5288431-2af2-4521-b5e4-35863a5b83f2 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Higrn: a hierarchical graph recurrent network for global sea surface temperature prediction,
Reference 16
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Observation ed3206fa-63c2-4baa-a569-7fe3b638526d · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Cross- region graph convolutional network with periodicity shift adaptation for wide-area sst prediction,
Reference 17
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Observation f493f6a7-c2fd-4513-b40a-c896a0901dab · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Mustc: A multi-stage spatio–temporal clustering method for uncovering the regionality of global sst,
Reference 18
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Observation 96ab927a-77d9-48f5-b1d5-771b4a8e6598 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Physical knowledge-enhanced deep neural network for sea surface temperature prediction,
Reference 19
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Observation 1808d597-5d9c-49d2-ad22-20756fb7cd09 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Multi-scale adaptive graph neural network for multivariate time series forecasting,
Reference 20
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Observation f2b7d3a6-4dd7-4c4c-969b-9a1904e856f2 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Causal- former: An interpretable transformer for temporal causal discovery,
Reference 21
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Observation be7e15de-8cee-4b2d-981f-af25bfc50122 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning On evaluating the predictability of sea surface temperature using entropy,
Reference 22
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Observation da85a5f2-fbe1-4d86-8a07-a161fedfa330 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning The ecmwf ensemble prediction system: Methodology and validation,
Reference 23
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Observation 257e9cdf-58e1-4c41-8782-89c3490dc4f4 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Spatiotemporal attention network for chl-a prediction with sparse multifactor observations,
Reference 24
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Observation 31fc4410-0cb0-43dc-b4ed-ef26a37d8270 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Multivariate time series forecasting with dynamic graph neural odes,
Reference 25
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Observation 5598f90b-7fc7-482e-9993-711875271d21 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Informer: Beyond efficient transformer for long sequence time-series forecasting,
Reference 26
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Observation 00bd3a27-7c15-42b9-902d-880c88f2d8ae · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Fedformer: Frequency enhanced decomposed transformer for long-term series fore- casting,
Reference 27
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Observation 1c5cbdfd-baae-475b-b8fb-fd14e9ee585f · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Timemixer++: A general time series pattern machine for universal predictive analysis,
Reference 28
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Observation 466ca20e-51f0-4041-af06-bfc228cc5b06 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Are transformers effective for time series forecasting?
Reference 29
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Observation 6925735d-2204-45d9-a061-de2eacd8f59c · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Frequency-domain mlps are more effective learners in time series forecasting,
Reference 30
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Observation 4494b860-5d53-48c9-a90a-c4a0f6f0c396 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Llm4hrs: Llm-based spatiotemporal imputation model for highly sparse remote sensing data,
Reference 31
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Observation 6ac5705b-2bc2-4699-a73c-5447d3ef3c21 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning PromptCast: A New Prompt-based Learning Paradigm for Time Series Forecasting
Reference 32
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Observation 4e142d2a-7164-401c-bf24-bf75756edf90 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Urbangpt: Spatio-temporal large language models,
Reference 33
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Observation 144597f8-90f9-48ec-bff2-e1950bc48d82 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning A foundation model of transcription across human cell types,
Reference 34
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Observation cecf5d40-385c-4da9-bd2d-cbfe24d7d7f9 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Protgpt2 is a deep unsupervised language model for protein design,
Reference 35
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Observation 1891bfe6-206e-4160-a905-8b6cb0133796 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning K2: A foundation language model for geoscience knowledge understanding and utilization,
Reference 36
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Observation 710b5ef2-1c87-4894-8824-d9d416703bea · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Foundation model for material science,
Reference 37
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Observation bb933f05-7407-4b0f-aa4a-0cb7e993dcbd · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Leveraging network structure for efficient dynamic negative sampling in network embedding,
Reference 38
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Observation cdb21201-f691-4c42-ad4f-8e115885c0f4 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Fathomgpt: A natural language interface for interactively exploring ocean science data,
Reference 39
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Observation c0a9daf1-9118-4383-9702-c13a151f3599 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Oceangpt: A large language model for ocean science tasks,
Reference 40
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Observation cd2dfd36-1ed8-4602-a9ad-7e731fe60e27 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Knowledge graph quality management: a compre- hensive survey,
Reference 41
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Observation 7f14bfd6-083f-4639-9bc3-6b861bcd077e · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Unifying large language models and knowledge graphs: A roadmap,
Reference 42
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Observation 1c01a8f1-e6cc-4b78-83b2-dc9839407c94 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Beyond Scaleup: Knowledge-aware Parsimony Learning from Deep Networks
Reference 43
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Observation f8d52724-afbb-4014-8199-04f107f4aa7c · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Knowledge graphs: Opportunities and challenges,
Reference 44
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Observation e87f5a1c-4fee-46d1-8ade-5a61a5af14b8 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Uukg: Unified urban knowledge graph dataset for urban spatiotemporal prediction,
Reference 45
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Observation 4c7b53c9-d699-48c2-b8ed-73a56e033ad9 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning From Local to Global: A Graph RAG Approach to Query-Focused Summarization
Reference 46
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Observation b5c7eafe-4f00-4d31-882b-df63e7a8a9e5 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Knowledge Graph-Guided Retrieval Augmented Generation
Reference 47
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Observation 67986563-3c4f-4e55-ba4c-3dfdebe05f5d · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Reversible instance normalization for accurate time-series forecasting against distri- bution shift,
Reference 48
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Observation d2707f32-ae3e-4572-a057-93e7b1ebacc7 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning Making large language models perform better in knowledge graph completion,
Reference 49
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Observation 23f363c9-5b53-4459-9305-c42703a90179 · outbound
Trusted Routing for Blockchain-Empowered UAV Networks via Multi-Agent Deep Reinforcement Learning A decoder-only foundation model for time-series forecasting,
Reference 50
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No inbound Pith citation observations are available.