Paper Citation Record · LEDGER

Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.05603.

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

pith.paper-citation-record.v1
2410.05603 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:49:09.652700Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T08:41:24.346832Z

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 428410d0-761f-4cd5-a3ef-ddb3d9be759d · inbound

Practical Considerations for Agentic LLM Systems cites this paper.

Practical Considerations for Agentic LLM Systems Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition

Reference 103

Resolution: unresolved; no resolver link, observed 2026-08-11T21:49:09.652700Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a7ff9a7-71eb-4f40-9861-cd592d0103da · inbound

Understanding Task Vectors in In-Context Learning: Emergence, Functionality, and Limitations cites this paper.

Understanding Task Vectors in In-Context Learning: Emergence, Functionality, and Limitations Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T05:04:25.346396Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a90ef7c-8523-4fb1-984d-13512b347ec1 · inbound

Exploring Task Performance with Interpretable Models via Sparse Auto-Encoders cites this paper.

Exploring Task Performance with Interpretable Models via Sparse Auto-Encoders Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T19:08:51.648824Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c47e4c13-e86e-426d-8f79-26d92c99453f · inbound

NoisyCoconut: Counterfactual Consensus via Latent Space Reasoning cites this paper.

NoisyCoconut: Counterfactual Consensus via Latent Space Reasoning Everything Everywhere All at Once: LLMs can In-Context Learn Multiple Tasks in Superposition

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:41:24.351717Z

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.