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Paper Citation Record · LEDGER

MetaICL: Learning to Learn In Context

As of 14 July 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2110.15943.

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

pith.paper-citation-record.v1
2110.15943 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-07-14T06:31:01.685423+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T07:14:26.441339Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T07:06:43.714296Z

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 4d14c871-3170-4cc5-8960-3d53fd2b96e3 · inbound

MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning cites this paper.

MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning MetaICL: Learning to Learn In Context

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-15T07:31:08.328755Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.

source=pdf_text observed=2026-05-15T07:31:08.266737Z digest=sha256:cad92cdfa4a8372d57f1d35db8a56a1c9fc8766ca02703de812b1ecf98cde294

Observation 2b18b2f4-47b0-4b94-b739-f752e4157c55 · inbound

Discovering Latent Knowledge in Language Models Without Supervision cites this paper.

Discovering Latent Knowledge in Language Models Without Supervision MetaICL: Learning to Learn In Context

Reference 22

Resolution
metadata mismatch
arxiv_id, observed 2026-05-15T20:34:08.341197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.

source=pdf_text observed=2026-05-15T20:34:08.207848Z digest=sha256:916a6add646449dd792bc87399fc99f5733650bfcae0b3ded8d36a00e487e658

Observation baf576d6-4323-43f0-ba5b-ccfd400c0783 · inbound

REPLUG: Retrieval-Augmented Black-Box Language Models cites this paper.

REPLUG: Retrieval-Augmented Black-Box Language Models MetaICL: Learning to Learn In Context

Reference 29

Resolution
verified exact
arxiv_id, observed 2026-05-17T12:41:54.079829Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.

source=arxiv_source observed=2026-05-17T12:41:53.833754Z digest=sha256:d9c18d91d9c2f600fe8effc98533cb7d4f129c830e6dd8ba9a9e97708b4da149

Observation 5174c63a-b55f-43e2-9d66-b8b9feada891 · inbound

ART: Automatic multi-step reasoning and tool-use for large language models cites this paper.

ART: Automatic multi-step reasoning and tool-use for large language models MetaICL: Learning to Learn In Context

Reference 128

Resolution
verified exact
arxiv_id, observed 2026-05-16T19:03:06.171842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.

source=arxiv_source observed=2026-05-16T19:03:05.597295Z digest=sha256:2060109e5d975be64eb1019afe5d425a9bba203d9b31d6f77c2f0c7a6de10e7e

Observation 1fbcf82c-3cd0-4783-912a-ed6316d9bf0e · inbound

QLoRA: Efficient Finetuning of Quantized LLMs cites this paper.

QLoRA: Efficient Finetuning of Quantized LLMs MetaICL: Learning to Learn In Context

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-11T13:29:53.569128Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.

source=pdf_text observed=2026-05-11T13:29:53.345251Z digest=sha256:d107f375cbdea1f2118dcf07bb866d6f95ef62474043c00a46bcde6c0dff216c

Observation 067f1dd5-8579-442f-af1d-6e8864e0f53f · inbound

Scaling Data-Constrained Language Models cites this paper.

Scaling Data-Constrained Language Models MetaICL: Learning to Learn In Context

Reference 73

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:35:21.280121Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.

source=pdf_text observed=2026-05-18T01:35:21.150772Z digest=sha256:2433228ac2e3ecc6c31c4843652772e672f35008842782cbca91ebfdf126ceaa

Observation b4204ce4-f8c1-4b0c-b9b1-a93e253a8f40 · inbound

A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence cites this paper.

A Survey of Self-Evolving Agents: What, When, How, and Where to Evolve on the Path to Artificial Super Intelligence MetaICL: Learning to Learn In Context

Reference 137

Resolution
verified exact
arxiv_id, observed 2026-05-14T22:23:14.791572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.

source=arxiv_source observed=2026-05-14T22:23:14.621091Z digest=sha256:d54033d60e8de1e141a4d357786dbd8beaea13a6fcf0ae7e6ab8df8669478957

Observation 32d94495-30bd-4f88-8bc2-6e7bf3ffb47b · inbound

Meta-learning In-Context Enables Training-Free Cross Subject Brain Decoding cites this paper.

Meta-learning In-Context Enables Training-Free Cross Subject Brain Decoding MetaICL: Learning to Learn In Context

Reference 71

Resolution
verified exact
arxiv_id, observed 2026-05-11T06:15:58.874494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.

source=pdf_text observed=2026-05-10T17:42:33.975433Z digest=sha256:c320d12ec1483e05ec2e93e9731a19e848171f656db3eac261e053d3ea2eec2a

Observation 42e0a5f7-03f9-4598-8f66-9a5539d13e87 · inbound

Learning to Adapt: In-Context Learning Beyond Stationarity cites this paper.

Learning to Adapt: In-Context Learning Beyond Stationarity MetaICL: Learning to Learn In Context

Reference 33

Resolution
metadata mismatch
arxiv_id, observed 2026-05-11T08:45:59.355223Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.

source=arxiv_source observed=2026-05-10T16:30:36.771589Z digest=sha256:54e037decf7d3052781f9f7061b66ec007b51e0237cde88e21951dc843f4b854

Observation 1bd083a9-4840-4017-ba38-65d4960086bb · inbound

STaR-Quant: State-Time Consistent Post-Training Quantization for Diffusion Large Language Models cites this paper.

STaR-Quant: State-Time Consistent Post-Training Quantization for Diffusion Large Language Models MetaICL: Learning to Learn In Context

Reference 122

Resolution
verified exact
arxiv_id, observed 2026-07-02T07:06:43.716299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-07-14T06:31:01.685423+00:00.

source=arxiv_source observed=2026-06-28T07:14:26.441339Z digest=sha256:a81be3353a78a085fe2ad400597c6a0c97bfaacf10acdd36bf851a9077cc21ae