Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:51:22.001700Z
Paper Citation Record · LEDGER
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series
As of 18 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 0 inbound Pith citation observations for arXiv:2505.11902.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+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
Reference resolution
18 of 18 outbound references displayed
- verified exact2
- verified fuzzy3
- unresolved13
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 37f94947-7015-4882-9a6c-2d386f43f2f3 · outbound
This paper cites Mai-unet: A multi-scale attention interactive network for multivariate long-term time series forecasting.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series Mai-unet: A multi-scale attention interactive network for multivariate long-term time series forecasting
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:51:22.319525Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 73e924ca-6cfa-4e44-b3b6-a3dbae6465b8 · outbound
This paper cites Trace: Time series parameter efficient fine-tuning.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series Trace: Time series parameter efficient fine-tuning
Reference 9
- Resolution
- verified exact
- raw_fallback, observed 2026-08-15T20:51:22.227430Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation e9bca0be-c7a9-4635-9484-faac0393fdc1 · outbound
This paper cites Learning Fast and Slow for Online Time Series Forecasting.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series Learning Fast and Slow for Online Time Series Forecasting
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:51:21.971408Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8fc79008-3fe3-43ba-a15e-485a93f61171 · outbound
This paper cites Tent: Fully Test-time Adaptation by Entropy Minimization.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series Tent: Fully Test-time Adaptation by Entropy Minimization
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:51:21.980349Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3bc481af-26b6-4ac0-a9df-90ed9fb01655 · outbound
This paper cites Transformers in Time Series: A Survey.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series Transformers in Time Series: A Survey
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:51:21.984849Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation be0f216b-8730-4a09-ab2d-a4c946e4f2c3 · outbound
This paper cites Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series Bitfit: Simple parameter-efficient fine-tuning for transformer-based masked language-models
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:51:21.992979Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 20e586ac-b827-4b3a-86c7-6b1ea9b08787 · outbound
This paper cites TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series TimeRAF: Retrieval-Augmented Foundation model for Zero-shot Time Series Forecasting
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:51:21.997274Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 44403c5b-298d-4b21-b327-c192d0675590 · outbound
This paper cites By definition, the dynamic hypothesis space is the union over time: Hdyn = [ t∈[0,T] Vt = K[ i=1 Fi, whereFi :=S t∈[ti−1,ti)Vt denotes the function class active in segmenti.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series By definition, the dynamic hypothesis space is the union over time: Hdyn = [ t∈[0,T] Vt = K[ i=1 Fi, whereFi :=S t∈[ti−1,ti)Vt denotes the function class active in segmenti
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:51:22.294501Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 7664b5da-2713-4d1b-bf77-f63409266022 · outbound
This paper cites On First-Order Meta-Learning Algorithms.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series On First-Order Meta-Learning Algorithms
Reference 2013
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:51:21.966744Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b9603a38-0bd4-4731-a568-1b1211ad8c43 · outbound
This paper cites An Efficient Continual Learning Framework for Multivariate Time Series Prediction Tasks with Application to Vehicle State Estimation.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series An Efficient Continual Learning Framework for Multivariate Time Series Prediction Tasks with Application to Vehicle State Estimation
Reference 2014
- Resolution
- verified exact
- local_arxiv, observed 2026-08-15T20:51:22.270566Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation d337f313-d371-4602-87f5-fe7049f90f83 · outbound
This paper cites An Overview of Multi-Task Learning in Deep Neural Networks.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series An Overview of Multi-Task Learning in Deep Neural Networks
Reference 2015
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:51:21.976045Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1925d21e-8824-4188-813c-dbf5e100450c · outbound
This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series Prefix-Tuning: Optimizing Continuous Prompts for Generation
Reference 2016
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:51:21.958117Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8fd847cd-c725-4ef3-8d17-ba97a6c72438 · outbound
This paper cites Language models are few-shot learners.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series Language models are few-shot learners
Reference 2018
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:51:21.924827Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5b879605-eba4-4681-a0e6-6e9f78ac83ad · outbound
This paper cites LoRA: Low-Rank Adaptation of Large Language Models.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series LoRA: Low-Rank Adaptation of Large Language Models
Reference 2019
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:51:21.949213Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1b581287-8e92-4577-a26e-c3b1a203c888 · outbound
This paper cites Context Matters: Leveraging Contextual Features for Time Series Forecasting.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series Context Matters: Leveraging Contextual Features for Time Series Forecasting
Reference 2020
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:51:21.929527Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7be5bdde-52c0-4c56-8094-d9ece4fe3912 · outbound
This paper cites TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series TimeFilter: Patch-Specific Spatial-Temporal Graph Filtration for Time Series Forecasting
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:51:21.953227Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9af5aea5-65e5-4315-9e47-54842a5a64f2 · outbound
This paper cites Kernel-u-net: Mul- tivariate time series forecasting using custom kernels.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series Kernel-u-net: Mul- tivariate time series forecasting using custom kernels
Reference 2022
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-08-15T20:51:22.306326Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation f1c6f1dd-ca5e-4a4a-8ef5-7f73904e41ff · outbound
This paper cites Context Matters: Leveraging Contextual Features for Time Series Forecasting.
Dynamic Perturbed Adaptive Method for Infinite Task-Conflicting Time Series Context Matters: Leveraging Contextual Features for Time Series Forecasting
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:51:21.934229Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Pith citing papers
No inbound Pith citation observations are available.