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Paper Citation Record · LEDGER

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

As of 20 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

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:01:16.632885Z

measured 85 of 85 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

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

No source-named external measurement is stored.

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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Observation 3b48845c-418b-469f-92db-9b0045b2c318 · outbound

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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Source-reported events for the cited work

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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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Source-reported events for the cited work

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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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Source-reported events for the cited work

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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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Source-reported events for the cited work

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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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Observation 02c1c761-54e9-4c64-9ee3-cd183a2c2973 · outbound

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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Observation 4f5edf61-37b4-4be2-8c27-d0c4a78b5c80 · outbound

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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Observation e8bc9468-10ed-4569-8f94-22feecbe188d · outbound

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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Observation d6896a65-efab-40aa-88e5-9e24d7430936 · outbound

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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Source-reported events for the cited work

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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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Source-reported events for the cited work

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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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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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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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation fc0b83a2-d505-42fe-9853-d9de252c5e1b · outbound

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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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d8e50de2-0fcf-430f-86f2-b21a60d6250c · outbound

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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Observation 506c29d5-07ab-4343-8d21-e323afa186bc · outbound

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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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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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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Observation 6d22c550-7122-49b1-8772-654466685dcf · outbound

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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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 5846be6a-6eb6-4aab-8115-d7b336f90182 · outbound

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 7f453d9a-fc4f-4c8f-974c-b4cece47b0b5 · outbound

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 664b204f-c538-493f-922f-95102c8b1ede · outbound

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 025c964c-9f04-4df8-b036-6c8e8edac1cc · outbound

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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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation e9e950fb-1e05-4d7f-a31a-ebfd43efad0d · outbound

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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Observation bc19de4f-f489-4fda-963e-1f34d1f896db · outbound

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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Observation dd32c6fe-edbb-45c9-9c28-f322ab6e0665 · outbound

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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Observation af312b60-de3f-4430-a53e-6b6da877aa8c · outbound

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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Observation 2cf1fd88-961c-4ec2-b192-c9a3432bfce9 · outbound

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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Observation b4b7e064-ed68-4005-b1f4-41092a570634 · outbound

This paper cites Position: What can large language models tell us about time series analysis.

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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source=pdf_text observed=2026-08-07T12:01:12.941699Z digest=sha256:bc1bda8aed70cfabab246691ab18834028f96f9bdd14f1276631d856d804e6ea

Observation 545aab6d-bc5a-49d3-af7e-47e549c1c9e0 · outbound

This paper cites Aditya Prakash.

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

Reference 37

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source=pdf_text observed=2026-08-07T12:01:13.013076Z digest=sha256:3320522878403dcdc4a83efcc0c9a95e4e1e887177c852eb4507032ff83de3cf

Observation 37d9da7c-3294-4911-840c-7e4c92a2e063 · outbound

This paper cites Position: Empowering time series reasoning with multimodal llms, 2025.

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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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:13.061399Z digest=sha256:fa82c82f3e262e4d6bbe1ac9983ee3ca2879220f65197e88d45e4a7434cdf12b

Observation eb8b03d2-a466-49e1-903d-68c9bd3f6b8e · outbound

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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source=pdf_text observed=2026-08-07T12:01:13.176687Z digest=sha256:9dba6abdd8f1c2d9c40415deb48dd21fcf57d6c512ab5e696dc1312d9b6a9ccb

Observation 6e4f4be9-38fb-4fe7-9d6d-d1693e6db8d6 · outbound

This paper cites Chatts: Aligning time series with llms via synthetic data for enhanced understanding and reasoning.

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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source=pdf_text observed=2026-08-07T12:01:13.287630Z digest=sha256:8bfc0b48120906e50d20e5130e3c02c9e0f99afa82f16fa862ca54ccccd96c1e

Observation 2a98dfe1-993a-45e8-9531-8ba255475bc9 · outbound

This paper cites Aditya Prakash.

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

Reference 41

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source=pdf_text observed=2026-08-07T12:01:13.402069Z digest=sha256:3270c626b34ec57d3e7c7793a7dd0aad3e3497f6f7fe3ac8aa685c7c6f5eaf20

Observation f4056644-10b2-4a99-9c6e-fc131e875b7f · outbound

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

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raw_fallback, observed 2026-08-07T12:01:22.065435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:13.517870Z digest=sha256:a5b9d8990f7d1fea9cc4277892a838a3e6ed89b0449457dfec7d97ab6bac4960

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

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raw_fallback, observed 2026-08-07T12:01:21.801921Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:13.630145Z digest=sha256:a57c4a964981a1cd6920bcd666719147a068679e7ebec04cb539150bb779e9df

Observation 560883d8-c893-4a37-a31f-4eb36c8ca289 · outbound

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

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raw_fallback, observed 2026-08-07T12:01:21.579650Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:13.763930Z digest=sha256:36447835b51f8bc0628ec401b225c861edcc5eeaeb3b6710dee92c8b054ca97e

Observation b842a108-ce4f-480a-bd31-6384bc4e83c9 · outbound

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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source=pdf_text observed=2026-08-07T12:01:13.884840Z digest=sha256:8f28455af90132ec8055f91ac17ecea52ba9a95bbadfa995363015c7cfcaa356

Observation 5a3f3208-b409-4e9a-b425-4c352f194fb8 · outbound

This paper cites Timeseriesexam: A time series understanding exam.

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

Reference 46

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raw_fallback, observed 2026-08-07T12:01:21.373175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:14.014265Z digest=sha256:77f9df1e830733ee3bf8b71cc554be1a4439f7d92e614ba305d2d81601966b6d

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
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raw_fallback, observed 2026-08-07T12:01:21.257032Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:14.139639Z digest=sha256:e76c447aaba2d736398652384d6cf296f808e8317eb2bf61372aa87d6b8f5452

Observation 270397ca-295d-4efd-a443-46c6c997a7b4 · outbound

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

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raw_fallback, observed 2026-08-07T12:01:21.034886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:14.226302Z digest=sha256:1a801c23a0aaf925f4f19d9b4543b86bdcc7c58f3c3cf195c4c57265ebe1bad1

Observation 1b79b558-1103-487d-9862-eb36f1694ac6 · outbound

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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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:14.307157Z digest=sha256:c3a9d04e8b18aec3f03f0ac5fd027ff06b546b19161ebeae55c76d86708fb48c

Observation 67d0840f-6770-4fa8-a99b-763b9a709be5 · outbound

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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source=pdf_text observed=2026-08-07T12:01:14.392026Z digest=sha256:c77b613110f74606405ffd5358f5833201fecdb8454ed7827bb82f301082413a

Observation f7d07232-5f45-42c1-90d5-b666245d712e · outbound

This paper cites Qwen2.5 Technical Report.

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

Reference 51

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source=pdf_text observed=2026-08-07T12:01:14.493988Z digest=sha256:32d6e973422b8f2634550c409e30c74f4e653163f884676dd4759f0e5fb15416

Observation 8fb6ecaa-8ee7-4919-9041-ebbc47285c55 · outbound

This paper cites The Llama 3 Herd of Models.

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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source=pdf_text observed=2026-08-07T12:01:14.564561Z digest=sha256:93bdf8fef5e9d55a1547efba1ae74aacc153d95a6c95197214fecd6b3a9e9ac5

Observation 6d27028a-febf-46f4-9491-b99f4a76d1c4 · outbound

This paper cites The ucr time series archive.

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

Reference 53

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source=pdf_text observed=2026-08-07T12:01:14.624674Z digest=sha256:fa9a458b639dbbf8afdd8aec804c62dacf80d388f48da7aee2626cfcae0b2901

Observation f8fbd19e-2a93-4dc1-abbf-a3fa21dad1d3 · outbound

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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source=pdf_text observed=2026-08-07T12:01:14.695875Z digest=sha256:2b0b891e569b41c60b0f8791fe6a22e6432ed948ae7109aa89e80ff44d75644d

Observation 600a007c-abe4-426c-a2dc-0b6c8986dd16 · outbound

This paper cites Time series analysis.

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

Reference 55

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raw_fallback, observed 2026-08-07T12:01:20.663342Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:14.796927Z digest=sha256:c52ba73f8b684f1982cb6c28d7ad9926510faadeca9c7dda6d09f17a5a5b72d5

Observation c16c484f-3aef-444c-92b0-f1eabfc5864f · outbound

This paper cites Promptcast: A new prompt-based learning paradigm for time series forecasting.

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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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:14.852588Z digest=sha256:40a6cb3358ae15188b2e95f5c1361b74ace487fe62850c7f4e30e20254c0d174

Observation de16c287-a55a-4cc9-a357-ee769ce78e26 · outbound

This paper cites Time series forecasting with llms: Understanding and enhancing model capabilities.

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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raw_fallback, observed 2026-08-07T12:01:20.355739Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:14.919015Z digest=sha256:7db355ce893e638515fb4080198b93cfaeef3fbdfb64dd8f008940931ca14342

Observation 69b8e795-6177-4d53-bed0-6f7888c7c1d5 · outbound

This paper cites Timer: Generative pre-trained transformers are large time series models.

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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source=pdf_text observed=2026-08-07T12:01:15.022178Z digest=sha256:36f13f886d9c4a6eee6bd3ac3912bdf74c09c2f60bb679495b52bb61fd7d043a

Observation e6fb1e67-83f7-4c5e-baa1-5acda0dcd045 · outbound

This paper cites A decoder-only foundation model for time-series forecasting.

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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source=pdf_text observed=2026-08-07T12:01:15.073762Z digest=sha256:ff5ab84d6ae7ee21f67b5cf4fe76b0f92cfdb8f58e1b63c7ebefadf6af9c0ece

Observation 2151c95e-65ee-4ac4-84ab-8ef0901f3753 · outbound

This paper cites Iot-llm: Enhancing real-world iot task reasoning with large language models.

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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source=pdf_text observed=2026-08-07T12:01:15.136283Z digest=sha256:82d991d715e5c3f9cb577f5abd8999ecd62ac82a134db9d467f46be84fc4362f

Observation 37354cb1-903d-4c30-b099-1d80d74fcde3 · outbound

This paper cites Instructime: Advancing time series classification with multimodal language modeling.

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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source=pdf_text observed=2026-08-07T12:01:15.177553Z digest=sha256:faa24a984eb8765d5217f2b13c1bd50c9442037898b365c91fbe56dc37e1974d

Observation cb1f7b63-ed64-4c9b-903d-102a289be5cb · outbound

This paper cites Domain-oriented time series inference agents for reasoning and automated analysis, 2024.

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:15.224774Z digest=sha256:58f2be9e47077b1b0c02cd5f032334bdf6d0f76e433a9c6b3c4bdea44253ea02

Observation b0f7888b-1847-4302-8983-802bcea9e0b9 · outbound

This paper cites Olivares, Michał Wili ´nski, Nina ˙Zukowska, and Artur Dubrawski.

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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raw_fallback, observed 2026-08-07T12:01:19.967511Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:15.291557Z digest=sha256:53332d032b31b60e1fb1b18edf7a7e5bf0237474882649cb4ca2ce1bbdc1e244

Observation 883d414f-7525-4800-a25e-6f11f1ac0adb · outbound

This paper cites Implicit reasoning in deep time series forecasting, 2024.

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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raw_fallback, observed 2026-08-07T12:01:19.779234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:15.362560Z digest=sha256:c30b1cbff70efb5a72b61b65ac963ba6ea87f38ee9d5e40ec34310bf95f76f48

Observation d1908bb1-d7ed-42aa-b452-5cdbe66b79cf · outbound

This paper cites Language Models Still Struggle to Zero-shot Reason about Time Series.

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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source=pdf_text observed=2026-08-07T12:01:15.404563Z digest=sha256:3eba5000904095d659d8fa68b2a87aee7a45bf0c9226de6a86f39ffd2ac77087

Observation 40bc6708-6255-4f01-a506-bb2c5125afba · outbound

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

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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raw_fallback, observed 2026-08-07T12:01:19.590285Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:15.454281Z digest=sha256:44248434307d962128d7b0994976dde6f6579b9e41cd03ccd0804a152f6dea6b

Observation d6445c26-fdb3-438d-9930-4dc6c69df112 · outbound

This paper cites Timexer: Empowering transformers for time series forecasting with exogenous variables.

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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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:15.495197Z digest=sha256:da9c2769521f9ade7d6f2a95b25fa3c907522212b1e0e7976f4bfbb79dd4e836

Observation af53ce9c-b30f-452d-988f-e31b5d29e50f · outbound

This paper cites Foundation models for time series analysis: A tutorial and survey.

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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source=pdf_text observed=2026-08-07T12:01:15.557891Z digest=sha256:a61cb239ac2e77485a38dfab2494346dafc04278fc5dc5b8ddd57dd3ff59383a

Observation d1021769-cfc9-4dfd-83a2-aebabc1889b3 · outbound

This paper cites Llm4ts: Aligning pre-trained llms as data-efficient time-series forecasters.

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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source=pdf_text observed=2026-08-07T12:01:15.622099Z digest=sha256:997e4bffdd8c0464fa8d3b2b4e1307d82142036fac240912501355106daea8dc

Observation 7214e942-6c56-4fa2-8942-5210da97fe14 · outbound

This paper cites Unitime: A language-empowered unified model for cross-domain time series forecasting.

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

Reference 70

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-07T12:01:15.703005Z digest=sha256:9c5af3c3f9f109e990825ab867303a12cd70c0e053a13f1680234f9a5ec19116

Observation d18f3290-06f3-4e76-81dc-9384091d127a · outbound

This paper cites TEMPO: Prompt-based generative pre-trained transformer for time series forecasting.

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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raw_fallback, observed 2026-08-07T12:01:19.062234Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation b53a4c6b-6575-4d45-ab07-8f3038fefe3e · outbound

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

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

Reference 72

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation b9315365-e8d9-4de3-b80e-a15dc0a15574 · outbound

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

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 57bec804-9384-420f-93ad-2bd33c6ae8c0 · outbound

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

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 365939c0-4d5e-4abf-8878-e0913474440e · outbound

This paper cites iTransformer: Inverted Transformers Are Effective for Time Series Forecasting.

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 8ea02ee3-25ad-48ce-ad1f-1444984d6a94 · outbound

This paper cites Nguyen, Phanwadee Sinthong, and Jayant Kalagnanam.

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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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 23ead614-cdaa-48e0-ac3d-e875b03b6e7f · outbound

This paper cites an unresolved cited work.

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

Reference 77

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 0cc203b4-f3d1-42bd-a1f2-0e9f4ef657db · outbound

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

Reference 78

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 776599d1-7e2c-44ea-b3ca-baaf56bc7ed3 · outbound

This paper cites an unresolved cited work.

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

Reference 79

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation d8d3cb57-1835-481a-a52e-73491f2d6f24 · outbound

This paper cites – Amplitude Differences: 1.

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

Reference 80

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation f08039c4-94ba-41f7-aa50-46e4ceb24d83 · outbound

This paper cites – Amplitude Differences: 1.

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

Reference 81

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 5371e27f-7407-4d9a-9726-4a33d85a8357 · outbound

This paper cites Random fluctuations are minimal and consistent across categories.

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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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 90607232-b1b6-444f-a5db-06ad45ddd8a0 · outbound

This paper cites – Structural Break Differences: 1.

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

Reference 83

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Pith citing papers

Observation 4c4903e9-89bb-42a2-bae2-878519290faa · inbound

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

Reference 150

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation a8b24ed1-8e9a-4076-bcd0-9888ddead4c9 · inbound

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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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

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Observation 589f49de-571a-4790-b84d-b909c25fdf48 · inbound

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

Reference 73

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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