Paper Citation Record · LEDGER

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation

As of 15 August 2026, this Paper Citation Record lists 28 of 28 outbound references and 3 inbound Pith citation observations for arXiv:2412.16643.

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

pith.paper-citation-record.v1
2412.16643 v1

Coverage vector

measured 28 of 28 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T10:25:47.680976Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T13:55:05.253473Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T17:40:15.595697Z

Reference resolution

28 of 28 outbound references displayed

verified exact1
verified fuzzy12
unresolved15
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 813f302f-8b11-4652-beac-05880611cda0 · outbound

This paper cites Time series forecasting of petroleum production using deep lstm recurrent networks,.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Time series forecasting of petroleum production using deep lstm recurrent networks,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:25:48.826569Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a6e106b9-8144-4dd4-a0d9-aa56435fee24 · outbound

This paper cites Reformer: The Efficient Transformer.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Reformer: The Efficient Transformer

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T10:25:47.437972Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d55fa07-1c13-4ce1-bb66-5f0024700d3f · outbound

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

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Informer: Beyond efficient transformer for long sequence time-series forecasting,

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T10:25:47.447128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0070e73-0493-440d-a728-d2cd354524ee · outbound

This paper cites Time-series forecasting with deep learning: a survey,.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Time-series forecasting with deep learning: a survey,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T10:25:47.454896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbed4ea5-a227-4f53-9dfc-aff3c4d200c6 · outbound

This paper cites A survey of time series foundation models: Generalizing time series representation with large language mode,.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation A survey of time series foundation models: Generalizing time series representation with large language mode,

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T10:25:47.466039Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1214d6f5-7d16-46ec-a42b-8f29c207b482 · outbound

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

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Promptcast: A new prompt-based learning paradigm for time series forecasting,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:25:48.768279Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation f21dcfea-11c9-4ff0-88b4-4121dcf609ef · outbound

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

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation One fits all: Power general time series analysis by pretrained lm,

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T10:25:47.490553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4dee1d95-ccae-4215-a905-df2e7029b2ca · outbound

This paper cites Empowering Time Series Analysis with Large Language Models: A Survey.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Empowering Time Series Analysis with Large Language Models: A Survey

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T10:25:47.497652Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7548d0a2-2196-4242-ada8-47b047a019b5 · outbound

This paper cites A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T10:25:47.508484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 45e2483d-a40d-471d-919f-3bcd501fbe9b · outbound

This paper cites Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks,.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks,

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:25:48.718903Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 84fd8feb-1a6a-48d5-82e1-33c215a6ebe9 · outbound

This paper cites Dynamic time warping,.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Dynamic time warping,

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T10:25:47.523487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5697a571-cef1-4f64-a335-a8c00ddeb07a · outbound

This paper cites The m4 competition: 100,000 time series and 61 forecasting methods,.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation The m4 competition: 100,000 time series and 61 forecasting methods,

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T10:25:47.534510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3527b177-b2bb-444d-915d-51c05b54b747 · outbound

This paper cites Time-LLM: Time Series Forecasting by Reprogramming Large Language Models.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Time-LLM: Time Series Forecasting by Reprogramming Large Language Models

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T10:25:47.545713Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 982d923e-521b-416d-b0b4-f6abdd9052dd · outbound

This paper cites Chronos: Learning the Language of Time Series.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Chronos: Learning the Language of Time Series

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T10:25:47.555139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3d69f0a1-61a6-4732-92b1-862628f7cafc · outbound

This paper cites Uni-Parser: Unified Semantic Parser for Question Answering on Knowledge Base and Database.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Uni-Parser: Unified Semantic Parser for Question Answering on Knowledge Base and Database

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-08-11T10:25:47.812772Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 751d020b-7ecd-4a57-a289-f0d534ef0193 · outbound

This paper cites Lost in the middle: How language models use long contexts,.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Lost in the middle: How language models use long contexts,

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:25:48.651365Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation cf38dce3-2b1d-4647-9680-364eae481d75 · outbound

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

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation LSTPrompt: Large language models as zero-shot time series forecasters by long-short-term prompting,

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:25:48.616245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3ef6e5bb-516a-476e-abeb-4c61fe5fd817 · outbound

This paper cites Dynamic programming algorithm optimiza- tion for spoken word recognition,.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Dynamic programming algorithm optimiza- tion for spoken word recognition,

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T10:25:47.589360Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4033238-1d11-40c5-962b-16d6bdfac2e0 · outbound

This paper cites N-BEATS: Neural basis expansion analysis for interpretable time series forecasting.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation N-BEATS: Neural basis expansion analysis for interpretable time series forecasting

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T10:25:47.597085Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7ad97caf-7d28-41b7-a0ef-6127ea40d3c6 · outbound

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

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation iTransformer: Inverted Transformers Are Effective for Time Series Forecasting

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T10:25:47.607022Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cec97eb9-56e1-4555-8993-0709f43e0b52 · outbound

This paper cites Fed- former: Frequency enhanced decomposed transformer for long-term series forecasting,.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Fed- former: Frequency enhanced decomposed transformer for long-term series forecasting,

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:25:48.565123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ecb84f0b-4966-4c60-81da-6ce85041ffed · outbound

This paper cites Pyraformer: Low-complexity pyramidal attention for long-range time series modeling and forecasting,.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Pyraformer: Low-complexity pyramidal attention for long-range time series modeling and forecasting,

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:25:48.507703Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 7c466a99-cdfe-4f0a-a087-82113ca83e46 · outbound

This paper cites Autoformer: Searching transformers for visual recognition,.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Autoformer: Searching transformers for visual recognition,

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:25:48.475250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 93c1a692-1c3e-47ae-b62f-1b0ce913ea94 · outbound

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

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Are transformers effective for time series forecasting?

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T10:25:47.639264Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22db6b79-f6b4-4bab-a444-9baf25311ed4 · outbound

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

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Tsmixer: Lightweight mlp-mixer model for multivariate time series forecasting,

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:25:48.411224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation e5574f6e-cd26-43c3-b761-f7c69312f1da · outbound

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

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Micn: Multi-scale local and global context modeling for long-term series forecasting,

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:25:48.385268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 695a0fb2-58ef-490e-974b-617887dce686 · outbound

This paper cites Film: Frequency improved legendre memory model for long-term time series forecasting,.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Film: Frequency improved legendre memory model for long-term time series forecasting,

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:25:48.361656Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4e241ee0-f8f4-4c62-9091-5a1361b26a9a · outbound

This paper cites Lightts: Lightweight time series classification with adaptive ensemble distillation,.

TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation Lightts: Lightweight time series classification with adaptive ensemble distillation,

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T10:25:48.332663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Pith citing papers

Observation fd5a2e0a-3af3-460a-8550-a7efd414d322 · inbound

TimeHF: Billion-Scale Time Series Models Guided by Human Feedback cites this paper.

TimeHF: Billion-Scale Time Series Models Guided by Human Feedback TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-10T13:55:05.253473Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a74514c4-2072-423e-ab84-b443473b6aaa · inbound

Retrieval-augmented Large Language Models for Financial Time Series Forecasting cites this paper.

Retrieval-augmented Large Language Models for Financial Time Series Forecasting TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-08-08T17:40:15.600811Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 4d4e9ff3-b635-4c91-988b-7d2cb68d6460 · 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 TimeRAG: BOOSTING LLM Time Series Forecasting via Retrieval-Augmented Generation

Reference 128

Resolution: unresolved; no resolver link, observed 2026-08-04T16:49:34.913898Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.