Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections
As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2104.04670.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-05-24T12:33:37.701655Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-24T12:34:28.249658Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation f207e3be-5991-4ba3-af77-6efa58737713 · inbound
Multitask Prompted Training Enables Zero-Shot Task Generalization cites this paper.
Multitask Prompted Training Enables Zero-Shot Task Generalization Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections
Reference 76
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T17:59:43.265643Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation a9a2317f-33df-4d2e-b01d-d0a98e525702 · inbound
GPT-NeoX-20B: An Open-Source Autoregressive Language Model cites this paper.
GPT-NeoX-20B: An Open-Source Autoregressive Language Model Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections
Reference 109
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T12:34:28.253416Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 4acd431b-1d90-43cb-83bc-4298157f8150 · inbound
Instruction Tuning with GPT-4 cites this paper.
Instruction Tuning with GPT-4 Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections
Reference 17
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T17:04:18.169337Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b7911ba0-d675-4108-ba92-b5250b98d354 · inbound
QLoRA: Efficient Finetuning of Quantized LLMs cites this paper.
QLoRA: Efficient Finetuning of Quantized LLMs Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections
Reference 73
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:29:53.821221Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation c3bbbca9-6689-419b-9da0-3da4e52e6258 · inbound
A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks cites this paper.
A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T00:13:21.681220Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9f27225d-17b2-4448-a3c5-4a526bb0d8be · inbound
A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks cites this paper.
A Foundation Model for Instruction-Conditioned In-Context Time Series Tasks Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T06:25:07.715191Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 10e296df-e527-4074-ac2a-966145daa61f · inbound
TabEmb: Joint Semantic-Structure Embedding for Table Annotation cites this paper.
TabEmb: Joint Semantic-Structure Embedding for Table Annotation Adapting Language Models for Zero-shot Learning by Meta-tuning on Dataset and Prompt Collections
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T12:41:02.377448Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.