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Paper Citation Record · LEDGER

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting

As of 9 August 2026, this Paper Citation Record lists 55 of 55 outbound references and 0 inbound Pith citation observations for arXiv:2505.17872.

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

pith.paper-citation-record.v1
2505.17872 v2

Coverage vector

measured 55 of 55 reference resolution

Typed states for the displayed outbound observations.

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measured 55 of 55 standing notices

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measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

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measured 0 of 1 external citation measurements

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Reference resolution

55 of 55 outbound references displayed

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External citation measurements

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Outbound references

Observation 7b5220ba-d973-4371-bddf-595e6206e637 · outbound

This paper cites End-to-end data-driven weather prediction.Nature, pages 1–3, 2025.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting End-to-end data-driven weather prediction.Nature, pages 1–3, 2025

Reference 1

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Observation 7f0ac359-6ff5-49fe-9d97-995938eb10f1 · outbound

This paper cites An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting An Empirical Evaluation of Generic Convolutional and Recurrent Networks for Sequence Modeling

Reference 2

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Observation 0b757c5f-ed2f-46f4-b935-a6d1f812e0d1 · outbound

This paper cites LoRA Learns Less and Forgets Less.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting LoRA Learns Less and Forgets Less

Reference 3

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Observation 6b27247f-0bf6-48a8-8bbd-7f10b3626c6c · outbound

This paper cites John Wiley & Sons, 2015.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting John Wiley & Sons, 2015

Reference 4

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Observation f3a51b1d-bbe3-49a0-9b8b-c92583c81bb0 · outbound

This paper cites Spectral temporal graph neural network for multivariate time-series forecasting.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Spectral temporal graph neural network for multivariate time-series forecasting

Reference 5

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Observation 77aba527-7a4a-458c-99d8-b7194d7df40e · outbound

This paper cites LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting LLM4TS: Aligning Pre-Trained LLMs as Data-Efficient Time-Series Forecasters

Reference 6

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Observation f5f6210c-b668-4e5f-8c60-ac0755446519 · outbound

This paper cites Multi- scale adaptive graph neural network for multivariate time series forecasting.IEEE Transactions on Knowledge and Data Engineering, 35(10):10748–10761, 2023.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Multi- scale adaptive graph neural network for multivariate time series forecasting.IEEE Transactions on Knowledge and Data Engineering, 35(10):10748–10761, 2023

Reference 7

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Observation 5953b7f5-b175-4923-8eec-c3c3309f29d5 · outbound

This paper cites Qlora: Efficient finetuning of quantized llms.Advances in neural information processing systems, 36:10088–10115, 2023.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Qlora: Efficient finetuning of quantized llms.Advances in neural information processing systems, 36:10088–10115, 2023

Reference 8

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Observation bda4a17e-8b4b-4046-9686-83a024d6b536 · outbound

This paper cites Sparse Low-rank Adaptation of Pre-trained Language Models.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Sparse Low-rank Adaptation of Pre-trained Language Models

Reference 9

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Observation 77412835-0d15-4521-bebb-5acdcb81e09c · outbound

This paper cites Tsmixer: Lightweight mlp-mixer model for multivariate time series forecasting.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Tsmixer: Lightweight mlp-mixer model for multivariate time series forecasting

Reference 10

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Observation 0434aadf-7fbc-4ccf-8e42-2e9764bc3fcb · outbound

This paper cites A Note on LoRA.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting A Note on LoRA

Reference 11

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Observation 4b08bfed-6b4a-4e49-a59e-e86628fed15d · outbound

This paper cites Deep learning for time series forecasting: The electric load case.CAAI Transactions on Intelligence Technology, 7(1):1–25, 2022.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Deep learning for time series forecasting: The electric load case.CAAI Transactions on Intelligence Technology, 7(1):1–25, 2022

Reference 12

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Observation fb7ef939-5c21-4a1d-af87-bf16968e097a · outbound

This paper cites Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Cross-Attention is All You Need: Adapting Pretrained Transformers for Machine Translation

Reference 13

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Observation c3ecb730-6f83-452e-9eed-13222963891c · outbound

This paper cites Two-step deep learning framework with error compensation technique for short-term, half-hourly electricity price forecasting.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Two-step deep learning framework with error compensation technique for short-term, half-hourly electricity price forecasting

Reference 14

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Observation cf6ac85c-2532-4c13-ae84-307c054da84b · outbound

This paper cites Low-rank adaptation of time series foundational models for out-of-domain modality forecasting.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Low-rank adaptation of time series foundational models for out-of-domain modality forecasting

Reference 15

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Observation dbcd01c7-67ba-4f08-8101-5afa46e4ca9e · outbound

This paper cites Sensitivity-aware visual parameter- efficient fine-tuning.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Sensitivity-aware visual parameter- efficient fine-tuning

Reference 16

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Observation 349fad85-5659-4f1a-85ae-adbb24d39c82 · outbound

This paper cites Towards a Unified View of Parameter-Efficient Transfer Learning.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Towards a Unified View of Parameter-Efficient Transfer Learning

Reference 17

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Observation 5d92a13a-8dbb-4d79-9e51-934be9781e90 · outbound

This paper cites MerA: Merging Pretrained Adapters For Few-Shot Learning.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting MerA: Merging Pretrained Adapters For Few-Shot Learning

Reference 18

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Observation f06d13b9-2af3-4926-9599-5c22b8603edd · outbound

This paper cites Parameter-efficient transfer learning for nlp.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Parameter-efficient transfer learning for nlp

Reference 19

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Observation fa9eb68e-5d6b-4694-b425-8b21d0aa6f19 · outbound

This paper cites Parameter-efficient transfer learning for nlp.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Parameter-efficient transfer learning for nlp

Reference 20

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 34c2bbc1-459f-458c-b2b7-9fb5393f684b · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting LoRA: Low-Rank Adaptation of Large Language Models

Reference 21

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Observation 70a810fe-2f3a-4fa1-b087-f37de0792353 · outbound

This paper cites FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting FinTSB: A Comprehensive and Practical Benchmark for Financial Time Series Forecasting

Reference 22

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Observation c22da91f-429f-4fc5-a682-8fa3a9ac4470 · outbound

This paper cites Domain Adaptation for Time series Transformers using One-step fine-tuning.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Domain Adaptation for Time series Transformers using One-step fine-tuning

Reference 23

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Observation 6ab22347-89c9-41f9-981e-125327fc024c · outbound

This paper cites Kingma and Jimmy Ba.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Kingma and Jimmy Ba

Reference 24

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Observation 13d0faa7-065e-490c-aadd-77ebc2bd6bd4 · outbound

This paper cites Conditional adapters: Parameter-efficient transfer learning with fast inference.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Conditional adapters: Parameter-efficient transfer learning with fast inference

Reference 25

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Observation 8ec5543d-6f97-499b-a80c-007b99ec491f · outbound

This paper cites Informer: Beyond efficient transformer for long sequence time-series forecasting.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Informer: Beyond efficient transformer for long sequence time-series forecasting

Reference 26

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Observation 91debe91-8a70-4300-af79-51c24fd523bd · outbound

This paper cites LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting LoftQ: LoRA-Fine-Tuning-Aware Quantization for Large Language Models

Reference 27

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Observation fd170f07-5bc5-4a1e-9ec5-9373760ad8d9 · outbound

This paper cites Parameter-Efficient Fine-Tuning without Introducing New Latency.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Parameter-Efficient Fine-Tuning without Introducing New Latency

Reference 28

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Observation bb46e58a-f64a-42b0-a7f6-24f417c464ad · outbound

This paper cites SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting SparseTSF: Modeling Long-term Time Series Forecasting with 1k Parameters

Reference 29

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Observation f8ef571e-be57-4c57-aa33-4aa09fd2ed8c · outbound

This paper cites SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting SegRNN: Segment Recurrent Neural Network for Long-Term Time Series Forecasting

Reference 30

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Observation cee4850c-7a70-49ac-9df1-8734e7721cd9 · outbound

This paper cites Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning.Advances in Neural Information Processing Systems, 35:1950–1965, 2022.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Few-shot parameter-efficient fine-tuning is better and cheaper than in-context learning.Advances in Neural Information Processing Systems, 35:1950–1965, 2022

Reference 31

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Observation dc50b2e6-a931-4e87-9017-2d3272f06f4a · outbound

This paper cites Scinet: time series modeling and forecasting with sample convolution and interaction.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Scinet: time series modeling and forecasting with sample convolution and interaction

Reference 32

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 671b0ae4-14ab-494d-886a-2ff97cf8e6e2 · outbound

This paper cites itrans- former: Inverted transformers are effective for time series forecasting.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting itrans- former: Inverted transformers are effective for time series forecasting

Reference 33

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No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation 54c041c4-4ab6-45e3-8530-5a3ae1225112 · outbound

This paper cites Scaling transformer neural networks for skillful and reliable medium-range weather forecasting.Advances in Neural Information Processing Systems, 37:68740–68771, 2024.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Scaling transformer neural networks for skillful and reliable medium-range weather forecasting.Advances in Neural Information Processing Systems, 37:68740–68771, 2024

Reference 34

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source=pdf_text observed=2026-08-07T14:46:00.834814Z digest=sha256:ab6e04462b0ea6af16565487b25e10a94a47dcd6a0b3445f1c95d8beab422ca0

Observation e0941c14-009c-4de3-a415-33bcba14e02a · outbound

This paper cites Channel-aware low-rank adaptation in time series forecasting.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Channel-aware low-rank adaptation in time series forecasting

Reference 35

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raw_fallback, observed 2026-08-07T14:46:05.509372Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:46:00.963343Z digest=sha256:658e76a73264c36ea377bd98f90e0ceaaa38e4c71bc06a549bcf85d80c03b76c

Observation 388e2729-75c1-4e83-ace2-f37d0666031f · outbound

This paper cites A time series is worth 64 words: Long-term forecasting with transformers.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting A time series is worth 64 words: Long-term forecasting with transformers

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-07T14:46:01.032901Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:46:01.032901Z digest=sha256:98ff1c6a652b5f385c7730a7756e251d482d845b6a791cac7d5eeb1c52d3c1a6

Observation ec54b99c-dcab-45d1-ada4-d038027e88ae · outbound

This paper cites Fredformer: Frequency debiased transformer for time series forecasting.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Fredformer: Frequency debiased transformer for time series forecasting

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:05.342407Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:46:01.095385Z digest=sha256:df176729a1b0191014b2669605950858463da615485073b5b044d4a43f2ebb7c

Observation 462a1303-5ff3-4f62-b471-d0abeecb7727 · outbound

This paper cites Deepar: Probabilistic forecasting with autoregressive recurrent networks.Int.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Deepar: Probabilistic forecasting with autoregressive recurrent networks.Int

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:05.152539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:46:01.176321Z digest=sha256:d8a71d695839963791875e0afd0b52acbfdbc6d4b0ec2872a7cac2a0cb52276e

Observation 91536ca8-5f0b-4c7f-b1c8-38e48d62dc5f · outbound

This paper cites Attention is all you need.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Attention is all you need

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-07T14:46:01.258765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:46:01.258765Z digest=sha256:13a496f3c43125916553734a303316658041dd05368c3e997dfa3172df400c94

Observation 59dc0770-fd62-4355-a418-d53247c975c6 · outbound

This paper cites Efficient fine-tuning of bert models on the edge.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Efficient fine-tuning of bert models on the edge

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:04.945289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:46:01.346242Z digest=sha256:6c097085bc2e755d2853c394e6a998376b2d9692b2e9f76f4767c5437d01c768

Observation c5229750-3512-4077-b02d-df9c24ee4223 · outbound

This paper cites Micn: Multi-scale local and global context modeling for long-term series forecasting.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Micn: Multi-scale local and global context modeling for long-term series forecasting

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:04.776339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:46:01.505313Z digest=sha256:3dfdc4ee9485862046813eac0a477ec1bb2e908c02105d8a36beb358347f24c7

Observation 0fb9abf4-eb18-40d3-ae06-2af941111993 · outbound

This paper cites Timesnet: Temporal 2d-variation modeling for general time series analysis.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Timesnet: Temporal 2d-variation modeling for general time series analysis

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:04.579689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:46:01.631742Z digest=sha256:83d6a8fd48b49bd2a049ff51a94f6f0bd8eaa8001cd5174cabd18b994eae546b

Observation da4ab278-7170-44dc-a4e8-1b375b3c19f5 · outbound

This paper cites Autoformer: Decomposition transformers with Auto-Correlation for long-term series forecasting.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Autoformer: Decomposition transformers with Auto-Correlation for long-term series forecasting

Reference 43

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:04.392037Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:46:01.747565Z digest=sha256:bc2cab5513f89a2325b26b5e2b862b40e5c552f1ba4adb684efe677229028cd6

Observation fd537a85-b282-4731-aec7-96b6677bb8b2 · outbound

This paper cites Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Chain of LoRA: Efficient Fine-tuning of Language Models via Residual Learning

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-07T14:46:01.867719Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:46:01.867719Z digest=sha256:14a17b280cff3915d8a51431009e260084f3c874bf5fb6ac7655689770efa640

Observation f2944a06-a502-4dc7-9b9d-66efb0910dc2 · outbound

This paper cites Parameter- efficient fine-tuning for pre-trained vision models: A survey.arXiv preprint arXiv:2402.02242, 2024.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Parameter- efficient fine-tuning for pre-trained vision models: A survey.arXiv preprint arXiv:2402.02242, 2024

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-07T14:46:01.978668Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:46:01.978668Z digest=sha256:ed9ddff9c0ea488375a098d11b44ebf02dc40ba8af9dfdc7bcee34056167af52

Observation 8c6d8ed8-5966-45a3-ab25-76dcda0e0378 · outbound

This paper cites Rethinking fourier transform from a basis functions perspective for long-term time series forecasting.Advances in Neural Information Processing Systems, 37:8515–8540, 2024.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Rethinking fourier transform from a basis functions perspective for long-term time series forecasting.Advances in Neural Information Processing Systems, 37:8515–8540, 2024

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:04.211878Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:46:02.089468Z digest=sha256:bc9d56a6f11cffcc1dde73a961c033047e5109733a5996e71a38956a378503ac

Observation 2f493e84-cfa3-421a-aeb8-3ff8ab0d795b · outbound

This paper cites LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting LoRETTA: Low-Rank Economic Tensor-Train Adaptation for Ultra-Low-Parameter Fine-Tuning of Large Language Models

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-07T14:46:02.191493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:46:02.191493Z digest=sha256:e21e378a2a5d31aac3170d7403069de6adbba14430fd8ebd2665a9bc4ea3bd03

Observation 7712c3cf-5198-4e20-95dc-2493caffffc6 · outbound

This paper cites Fouriergnn: Rethinking multivariate time series forecasting from a pure graph perspective.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Fouriergnn: Rethinking multivariate time series forecasting from a pure graph perspective

Reference 48

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:04.031696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:46:02.242442Z digest=sha256:6d9329882a7d3d0bf26624e3143fe4bc52ee4cf15d446345ceb37144f7909bc6

Observation f4666578-039e-4d5a-883c-c4b8aea3f3cf · outbound

This paper cites Frequency-domain mlps are more effective learners in time series forecasting.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Frequency-domain mlps are more effective learners in time series forecasting

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:03.798494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:46:02.357550Z digest=sha256:620668b7626cefba39d449056d52442e786096db78d9a2f785a713a5713d8220

Observation fad19337-a79d-4cab-9522-6fc3b4c7a7ee · outbound

This paper cites Are transformers effective for time series forecasting? InAAAI, 2023.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Are transformers effective for time series forecasting? InAAAI, 2023

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-07T14:46:02.442537Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:46:02.442537Z digest=sha256:9ae009e74e977331b5046d9b8aa9131d3ea5e41394e68094bd25a1292fb5151e

Observation 91124070-ec00-44b5-9101-16b823ea45e4 · outbound

This paper cites Solar forecasting with hourly updated numerical weather prediction.Renewable and Sustainable Energy Reviews, 154:111768, 2022.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Solar forecasting with hourly updated numerical weather prediction.Renewable and Sustainable Energy Reviews, 154:111768, 2022

Reference 51

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:03.575379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:46:02.494515Z digest=sha256:b91bd6936adb598d522d61bbe98c4eb982a133c86f61adf61470465fc64d73b4

Observation 70003de8-e4da-491d-b5d3-eb5560362470 · outbound

This paper cites AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting AdaLoRA: Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T14:46:02.602480Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:46:02.602480Z digest=sha256:61d9b7ec0e92c7a47db5896fbea9406f67139aa74686147e42b9f44c8cf6b7a3

Observation 3f131f2f-52f0-41b2-819b-8f598d916fee · outbound

This paper cites Film: Frequency improved legendre memory model for long-term time series forecasting.Advances in neural information processing systems, 35:12677–12690, 2022.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting Film: Frequency improved legendre memory model for long-term time series forecasting.Advances in neural information processing systems, 35:12677–12690, 2022

Reference 53

Resolution
unresolved
no resolver link, observed 2026-08-07T14:46:02.641800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:46:02.641800Z digest=sha256:a7b2ed3d71e90681f04f7c9f2279cc2fd85775aa754b3278d9ee164f5fe4704a

Observation 22603d55-07a5-4c75-8686-8ecadbc2d58a · outbound

This paper cites FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:03.311929Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:46:02.739606Z digest=sha256:d1a4242d44bb52b8cc8d8446be96116419fcaf570e0796e8e30b2860efee60a5

Observation bf79b479-e9b9-4154-93b7-b45f7a74289d · outbound

This paper cites One fits all: Power general time series analysis by pretrained lm.Advances in neural information processing systems, 36:43322–43355, 2023.

Mixture of Low Rank Adaptation with Partial Parameter Sharing for Time Series Forecasting One fits all: Power general time series analysis by pretrained lm.Advances in neural information processing systems, 36:43322–43355, 2023

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T14:46:03.097908Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-08-07T14:46:02.816284Z digest=sha256:995d6647c0b02e42147c4aa61a596f7bdd7ae15982393e2aea5174c680dfeb5b

Pith citing papers

No inbound Pith citation observations are available.