Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:16:22.385727Z
Paper Citation Record · LEDGER
As of 8 August 2026, this Paper Citation Record lists 19 of 19 outbound references and 0 inbound Pith citation observations for arXiv:2506.21570.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-07T04:16:22.385727Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
19 of 19 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 06598154-b1a0-4f5f-bc14-977e4c35f3fe · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Chronos: Learning the Language of Time Series
Reference 1
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ab2a4ad7-06e5-4814-b20d-cbcdb60f91bb · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Unresolved cited work
Reference 2
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 28eea64a-ad28-4eed-b4cf-58543c2f0543 · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting On the Opportunities and Risks of Foundation Models
Reference 3
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation cc812f25-e325-457b-a8db-bbfe74b790e0 · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Scaling Instruction-Finetuned Language Models
Reference 4
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 49559f20-620e-4951-ab56-3f4fedd22644 · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Large Language Models Are Zero-Shot Time Series Forecasters
Reference 5
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 11fcacc2-1117-4cfe-815b-da7c50f91cd5 · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Scaling laws for transfer, 2021
Reference 6
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 205753f0-3259-47ba-a391-437f34578e81 · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Y., Shi, X., Chen, P.-Y., Liang, Y., Li, Y.-F., Pan, S., and Wen, Q
Reference 7
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation daa43046-084e-4e25-993b-abeea03f6ee8 · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Scaling Laws for Neural Language Models
Reference 8
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 38287725-ba8e-4cd7-8c31-d82deb66ca6b · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation
Reference 9
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1d57a6a4-cc7d-4532-9c06-d8c3d9dfcc5d · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Pretrained Transformers as Universal Computation Engines
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 33762d6f-5081-40f4-9daa-680859041d19 · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting On the Stability of Fine-tuning BERT: Misconceptions, Explanations, and Strong Baselines
Reference 11
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6c98152a-aeac-4fda-9790-76263581624c · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
Reference 12
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 758ed7b2-724a-4f94-bba0-bb97d7f5df63 · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Lag-Llama: Towards Foundation Models for Probabilistic Time Series Forecasting
Reference 13
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fb853581-8106-46f5-9a92-9a8679e85f04 · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Unresolved cited work
Reference 14
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
Observation 7f3d18c2-6685-4b5f-a35a-2ac7f7ab6ca8 · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Scale Efficiently: Insights from Pre-training and Fine-tuning Transformers
Reference 15
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a695f355-aef3-49e9-8426-859e58cd1c5a · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Finetuned Language Models Are Zero-Shot Learners
Reference 16
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eacd3d10-922f-4e55-9c8f-205ebed68ed0 · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Context is Key: A Benchmark for Forecasting with Essential Textual Information
Reference 17
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ee91e22-2d09-4819-a54d-1c35bd1af9d7 · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting Unified Training of Universal Time Series Forecasting Transformers
Reference 18
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fed88b2e-631f-4349-b2b0-5d41dda4b59c · outbound
Random Initialization Can't Catch Up: The Advantage of Language Model Transfer for Time Series Forecasting One fits all:power general time series analysis by pretrained lm, 2023
Reference 19
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.
No inbound Pith citation observations are available.