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Paper Citation Record · LEDGER

STeCa: Step-level Trajectory Calibration for LLM Agent Learning

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 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 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:53:40.544944Z

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 52c22c42-2152-43e2-87f6-f02544f078e2 · inbound

LLM-Guided Reinforcement Learning: Addressing Training Bottlenecks through Policy Modulation cites this paper.

LLM-Guided Reinforcement Learning: Addressing Training Bottlenecks through Policy Modulation STeCa: Step-level Trajectory Calibration for LLM Agent Learning

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-07T13:53:40.544944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:53:40.544944Z digest=sha256:905a9c4f87d05439a0954d4c6c26da49aa432a69fe3beadd053b3709611c61f0

Observation 4f8e9611-831e-476c-97d4-ba992b9a6c50 · inbound

SPA-RL: Reinforcing LLM Agents via Stepwise Progress Attribution cites this paper.

SPA-RL: Reinforcing LLM Agents via Stepwise Progress Attribution STeCa: Step-level Trajectory Calibration for LLM Agent Learning

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T13:53:00.472873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:53:00.472873Z digest=sha256:ee3306e7ce37cefe7185744cda68504a2fe69c9f21dd7078ca8e396f8f7a7e89

Observation 5c6d6211-4907-4e1e-afef-1f97b687be2d · inbound

Unleashing Embodied Task Planning Ability in LLMs via Reinforcement Learning cites this paper.

Unleashing Embodied Task Planning Ability in LLMs via Reinforcement Learning STeCa: Step-level Trajectory Calibration for LLM Agent Learning

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T21:55:04.117987Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T21:55:04.117987Z digest=sha256:6ed74c7de0b217a52d3467a2e461c4957f55fb3698247fb36cdf750c817dd7e2

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-06-30T12:59:57.639608Z digest=sha256:a3236b1bc1adc5a3d8a2fadedff909c966e11250937ede6d933dcb326f758081

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-26T04:47:47.691913Z digest=sha256:bbbd880bcc42957711bf1b89ffd667a714759777c3ff3239416fa8a690b57d3e

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.

source=pdf_text observed=2026-08-01T07:48:47.137127Z digest=sha256:95b7e47ce0e05cba4c89756dac299879284a75fd3a2a48f22e2ca090ff173d81

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.

source=pdf_text observed=2026-07-31T00:46:11.569078Z digest=sha256:367be3b6e1254015c23a19a3d45815775887a784101fe213f7a78492af7ee528