Paper Citation Record · LEDGER

STeCa: Step-level Trajectory Calibration for LLM Agent Learning

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2502.14276.

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

pith.paper-citation-record.v1
2502.14276 v2

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 2026-08-05T06:32:48.257954+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T07:48:47.137127Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T13:59:51.910228Z

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 217ee81d-d12e-4098-a68d-a999ea0abec2 · inbound

Proper Scoring Rules for Agentic Uncertainty Quantification cites this paper.

Proper Scoring Rules for Agentic Uncertainty Quantification STeCa: Step-level Trajectory Calibration for LLM Agent Learning

Reference 4

Resolution: metadata mismatch; arxiv_id, observed 2026-06-30T13:04:40.141022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d2a76704-ce1e-4b46-b927-b9d524d0aeaf · inbound

Reinforcement Learning without Ground-Truth Solutions can Improve LLMs cites this paper.

Reinforcement Learning without Ground-Truth Solutions can Improve LLMs STeCa: Step-level Trajectory Calibration for LLM Agent Learning

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-04T13:59:51.911633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a29b5a32-51e3-48ec-9027-580b96d82b32 · inbound

Bridging Inference-Time Scaling and Episodic Memory with Action-Centric Graphs cites this paper.

Bridging Inference-Time Scaling and Episodic Memory with Action-Centric Graphs STeCa: Step-level Trajectory Calibration for LLM Agent Learning

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-01T07:48:47.137127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a924f989-8c55-44ad-9583-168f12eb114c · inbound

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems cites this paper.

Leveraging Trajectory Graphs for Pre-Execution Error Diagnosis in Agentic LLM Systems STeCa: Step-level Trajectory Calibration for LLM Agent Learning

Reference 49

Resolution: unresolved; no resolver link, observed 2026-07-31T00:46:11.569078Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.