Paper Citation Record · LEDGER

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision

As of 7 August 2026, this Paper Citation Record lists 82 of 82 outbound references and 3 inbound Pith citation observations for arXiv:2506.00807.

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

pith.paper-citation-record.v1
2506.00807 v1

Coverage vector

measured 82 of 82 reference resolution

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measured 85 of 85 standing notices

One-hop event checks from named stored sources.

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measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T16:49:34.980153Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-17T01:58:51.516210Z

Reference resolution

82 of 82 outbound references displayed

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External citation measurements

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Outbound references

Observation 02d533e4-5784-4fef-b65b-c7a1018ded87 · outbound

This paper cites Medformer: A multi-granularity patching transformer for medical time-series classification.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Medformer: A multi-granularity patching transformer for medical time-series classification

Reference 1

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Observation a7974147-cbe4-4f2b-afea-03cbd2c85bb5 · outbound

This paper cites Semi-supervised contrastive learning for time series classification in healthcare.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Semi-supervised contrastive learning for time series classification in healthcare

Reference 2

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This paper cites A comprehensive review on machine learning in healthcare industry: classification, restrictions, opportunities and challenges.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision A comprehensive review on machine learning in healthcare industry: classification, restrictions, opportunities and challenges

Reference 3

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Observation 4cdc84d6-a024-4ba4-8df1-ff8226ad17aa · outbound

This paper cites Improving stock trend prediction through financial time series classification and temporal correlation analysis based on aligning change point.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Improving stock trend prediction through financial time series classification and temporal correlation analysis based on aligning change point

Reference 4

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Observation 899c1248-2f4b-40d8-9c3a-956d49f43445 · outbound

This paper cites Clustering and classification of time series using topological data analysis with applications to finance.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Clustering and classification of time series using topological data analysis with applications to finance

Reference 5

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Observation 861f2bb4-7422-4791-a11d-3d9748a81dfc · outbound

This paper cites V oice2series: Reprogramming acoustic models for time series classification.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision V oice2series: Reprogramming acoustic models for time series classification

Reference 6

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Observation d77b0782-33d6-4e85-ab7f-fe2ca8677eaf · outbound

This paper cites Approaches and applications of early classification of time series: A review.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Approaches and applications of early classification of time series: A review

Reference 7

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This paper cites A systematic review of time series classification techniques used in biomedical applications.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision A systematic review of time series classification techniques used in biomedical applications

Reference 8

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Observation 5acb9146-e6dc-41bf-89a2-78851de630f5 · outbound

This paper cites GPT-4o System Card.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision GPT-4o System Card

Reference 9

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This paper cites GPT-4 Technical Report.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision GPT-4 Technical Report

Reference 10

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Observation 52b1da5e-1dbc-4773-99f3-ed05ea35ae8a · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 11

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This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Gemini: A Family of Highly Capable Multimodal Models

Reference 12

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This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Gemma: Open Models Based on Gemini Research and Technology

Reference 13

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Observation c52fa68d-9ac4-42d6-b0c2-8cb8e7756b60 · outbound

This paper cites Conformalized time series with semantic features.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Conformalized time series with semantic features

Reference 14

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Observation 6b24dea4-e904-4820-aa0d-c23ce75cebd9 · outbound

This paper cites Parsimony or capability? decomposition delivers both in long-term time series forecasting.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Parsimony or capability? decomposition delivers both in long-term time series forecasting

Reference 15

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Observation 9dd6286b-476d-42ad-b3b4-91f6c07d3a41 · outbound

This paper cites Large pre-trained time series models for cross- domain time series analysis tasks.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Large pre-trained time series models for cross- domain time series analysis tasks

Reference 16

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Observation d20ad1d2-72eb-47aa-a590-9691bfe93cfa · outbound

This paper cites Autotimes: Autoregressive time series forecasters via large language models.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Autotimes: Autoregressive time series forecasters via large language models

Reference 17

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Observation 5d96b765-f709-4916-9eab-13acf4e79f40 · outbound

This paper cites Time-ffm: Towards lm- empowered federated foundation model for time series forecasting.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Time-ffm: Towards lm- empowered federated foundation model for time series forecasting

Reference 18

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This paper cites Tiny time mixers (ttms): Fast pre-trained models for enhanced zero/few-shot forecasting of multivariate time series.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Tiny time mixers (ttms): Fast pre-trained models for enhanced zero/few-shot forecasting of multivariate time series

Reference 19

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This paper cites Unified training of universal time series forecasting transformers.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Unified training of universal time series forecasting transformers

Reference 20

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Observation 419312e2-f2a9-41e0-9bff-b1fe33f4b31a · outbound

This paper cites One fits all: Power general time series analysis by pretrained lm.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision One fits all: Power general time series analysis by pretrained lm

Reference 21

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This paper cites Time-LLM: Time series forecasting by repro- gramming large language models.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Time-LLM: Time series forecasting by repro- gramming large language models

Reference 22

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Observation b8bf367f-0c9d-45be-a506-7d2ff41b4f74 · outbound

This paper cites In-context time series predictor.arXiv preprint arXiv:2405.14982, 2024.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision In-context time series predictor.arXiv preprint arXiv:2405.14982, 2024

Reference 23

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This paper cites Can llms understand time series anomalies?, 2024.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Can llms understand time series anomalies?, 2024

Reference 24

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This paper cites Sarad: Spatial association-aware anomaly detection and diagnosis for multivariate time series.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Sarad: Spatial association-aware anomaly detection and diagnosis for multivariate time series

Reference 25

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This paper cites Llm4hrs: Llm-based spatio-temporal imputation model for highly-sparse remote sensing data.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Llm4hrs: Llm-based spatio-temporal imputation model for highly-sparse remote sensing data

Reference 26

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Observation 23a8cbf7-55fb-4add-abc0-d577a8a42db6 · outbound

This paper cites Task-oriented time series imputation evaluation via generalized representers.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Task-oriented time series imputation evaluation via generalized representers

Reference 27

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This paper cites Moment: A family of open time-series foundation models.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Moment: A family of open time-series foundation models

Reference 28

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This paper cites Shedding light on time series classification using interpretability gated networks.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Shedding light on time series classification using interpretability gated networks

Reference 29

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This paper cites Mantis: Lightweight Foundation Model for Time Series Classification.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Mantis: Lightweight Foundation Model for Time Series Classification

Reference 30

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This paper cites Hierarchical multimodal llms with semantic space alignment for enhanced time series classification, 2024.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Hierarchical multimodal llms with semantic space alignment for enhanced time series classification, 2024

Reference 31

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This paper cites A survey on large language model based autonomous agents.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision A survey on large language model based autonomous agents

Reference 32

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This paper cites Chain-of-thought prompting elicits reasoning in large language models.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Chain-of-thought prompting elicits reasoning in large language models

Reference 33

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This paper cites Towards Time Series Reasoning with LLMs.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Towards Time Series Reasoning with LLMs

Reference 34

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Position: What can large language models tell us about time series analysis

Reference 36

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Aditya Prakash

Reference 37

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Position: Empowering time series reasoning with multimodal llms, 2025

Reference 38

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This paper cites Mtbench: A multimodal time series benchmark for temporal reasoning and question answering.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Mtbench: A multimodal time series benchmark for temporal reasoning and question answering

Reference 39

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Chatts: Aligning time series with llms via synthetic data for enhanced understanding and reasoning

Reference 40

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Aditya Prakash

Reference 41

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This paper cites Large language models are zero-shot time series forecasters.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Large language models are zero-shot time series forecasters

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:22.065435Z

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Observation 8f122229-d24a-458f-9242-de569910b8f2 · outbound

This paper cites Are language models actually useful for time series forecasting? Advances in Neural Information Processing Systems , 37: 60162–60191, 2024.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Are language models actually useful for time series forecasting? Advances in Neural Information Processing Systems , 37: 60162–60191, 2024

Reference 43

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:21.801921Z

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This paper cites LSTPrompt: Large language models as zero-shot time series forecasters by long-short-term prompting.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision LSTPrompt: Large language models as zero-shot time series forecasters by long-short-term prompting

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:21.579650Z

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This paper cites Understanding llms: A comprehensive overview from training to inference.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Understanding llms: A comprehensive overview from training to inference

Reference 45

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Timeseriesexam: A time series understanding exam

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:21.373175Z

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Observation 540afef0-44a6-4ca3-8782-9b80d31f8cdf · outbound

This paper cites Implicit reasoning in deep time series forecasting.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Implicit reasoning in deep time series forecasting

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:21.257032Z

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This paper cites Supervised knowledge makes large language models better in-context learners.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Supervised knowledge makes large language models better in-context learners

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T12:01:21.034886Z

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This paper cites Maddix, Michael W.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Maddix, Michael W

Reference 49

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This paper cites Qwen Technical Report.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Qwen Technical Report

Reference 50

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Qwen2.5 Technical Report

Reference 51

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision The Llama 3 Herd of Models

Reference 52

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision The ucr time series archive

Reference 53

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This paper cites The UEA multivariate time series classification archive, 2018.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision The UEA multivariate time series classification archive, 2018

Reference 54

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Time series analysis

Reference 55

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Promptcast: A new prompt-based learning paradigm for time series forecasting

Reference 56

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Time series forecasting with llms: Understanding and enhancing model capabilities

Reference 57

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Timer: Generative pre-trained transformers are large time series models

Reference 58

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision A decoder-only foundation model for time-series forecasting

Reference 59

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Iot-llm: Enhancing real-world iot task reasoning with large language models

Reference 60

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Instructime: Advancing time series classification with multimodal language modeling

Reference 61

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Domain-oriented time series inference agents for reasoning and automated analysis, 2024

Reference 62

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Olivares, Michał Wili ´nski, Nina ˙Zukowska, and Artur Dubrawski

Reference 63

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Implicit reasoning in deep time series forecasting, 2024

Reference 64

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Language Models Still Struggle to Zero-shot Reason about Time Series

Reference 65

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision itrans- former: Inverted transformers are effective for time series forecasting

Reference 66

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Timexer: Empowering transformers for time series forecasting with exogenous variables

Reference 67

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Foundation models for time series analysis: A tutorial and survey

Reference 68

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Llm4ts: Aligning pre-trained llms as data-efficient time-series forecasters

Reference 69

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Unitime: A language-empowered unified model for cross-domain time series forecasting

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision TEMPO: Prompt-based generative pre-trained transformer for time series forecasting

Reference 71

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Timesnet: Tem- poral 2d-variation modeling for general time series analysis

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Autoformer: Decomposition transformers with Auto-Correlation for long-term series forecasting

Reference 73

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision FEDformer: Frequency enhanced decomposed transformer for long-term series forecasting

Reference 74

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

Reference 75

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Nguyen, Phanwadee Sinthong, and Jayant Kalagnanam

Reference 76

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Unresolved cited work

Reference 77

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This paper cites Are transformers effective for time series forecasting? Proceedings of the AAAI Conference on Artificial Intelligence, 37(9):11121–11128, Jun.

Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Are transformers effective for time series forecasting? Proceedings of the AAAI Conference on Artificial Intelligence, 37(9):11121–11128, Jun

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Unresolved cited work

Reference 79

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision – Amplitude Differences: 1

Reference 80

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision – Amplitude Differences: 1

Reference 81

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision Random fluctuations are minimal and consistent across categories

Reference 82

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Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision – Structural Break Differences: 1

Reference 83

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Pith citing papers

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A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models cites this paper.

A Survey of Reasoning and Agentic Systems in Time Series with Large Language Models Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision

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RAG-HAR: Retrieval Augmented Generation-based Human Activity Recognition cites this paper.

RAG-HAR: Retrieval Augmented Generation-based Human Activity Recognition Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision

Reference 46

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TRACE-TS: Attribution-Grounded and Traceable Sensor-Language Reasoning for Human Activity Understanding cites this paper.

TRACE-TS: Attribution-Grounded and Traceable Sensor-Language Reasoning for Human Activity Understanding Enhancing LLM Reasoning for Time Series Classification by Tailored Thinking and Fused Decision

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