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Paper Citation Record · LEDGER

Can large language models explore in-context?

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2403.15371.

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

pith.paper-citation-record.v1
2403.15371 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:03:26.307343Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T05:57:41.689630Z

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 c14075a3-af6b-4cea-a2df-df48b7991ca5 · inbound

e3: Learning to Explore Enables Extrapolation of Test-Time Compute for LLMs cites this paper.

e3: Learning to Explore Enables Extrapolation of Test-Time Compute for LLMs Can large language models explore in-context?

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T05:03:26.307343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:03:26.307343Z digest=sha256:8b912253694c886e03fbcf0637778cf54d7c0f42fa35d90b57c12e22c5ed7759

Observation 097a55a6-5e4c-4383-bec7-b4b810126b6f · inbound

Behavioral Exploration: Learning to Explore via In-Context Adaptation cites this paper.

Behavioral Exploration: Learning to Explore via In-Context Adaptation Can large language models explore in-context?

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T18:15:44.938881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T18:15:44.938881Z digest=sha256:43c1975d331cec77c8c46d57fd144d88be5bb42a044f55efd779a1631353e1ff

Observation bdc44b5f-a928-407a-80a9-53f371552662 · inbound

ABBEL: Learning Natural-Language Belief States for Memory-Efficient Interaction cites this paper.

ABBEL: Learning Natural-Language Belief States for Memory-Efficient Interaction Can large language models explore in-context?

Reference 6

Resolution
unresolved
no resolver link, observed 2026-08-03T14:34:51.319254Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T14:34:51.319254Z digest=sha256:a449aa00f629b0e1f706bbd043809c929549c78bd14ffc26d8b3040658f829ab

Observation 02ea7086-85eb-4f6d-9a8b-5149daae45cf · inbound

CA-SQL: Complexity-Aware Inference Time Reasoning for Text-to-SQL via Exploration and Compute Budget Allocation cites this paper.

CA-SQL: Complexity-Aware Inference Time Reasoning for Text-to-SQL via Exploration and Compute Budget Allocation Can large language models explore in-context?

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:25:58.203031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-11T02:28:20.366674Z digest=sha256:995cdcaeb8ec42f372b2a8adf31fbab5f9ebdaa4ae50738ad5f6b1566baaefca

Observation 5e3a72b7-e39c-4ba1-a931-6ff7d071f22c · inbound

The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes cites this paper.

The Periodic Table of LLM Reasoning: A Structured Survey of Reasoning Paradigms, Methods, and Failure Modes Can large language models explore in-context?

Reference 121

Resolution
verified exact
arxiv_id, observed 2026-07-03T05:57:41.691457Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-27T12:59:51.091008Z digest=sha256:73001cebf2dea04ca07d523d2911d769b53660f720187e486ef42ac2bee7368c