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Paper Citation Record · LEDGER

GTR: Guided Thought Reinforcement Prevents Thought Collapse in RL-based VLM Agent Training

As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2503.08525.

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

pith.paper-citation-record.v1
2503.08525 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-28T15:45:26.891621Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-01T22:06:16.650922Z

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 6ff8bf06-0f63-4e45-bf90-89a8ffb3a6c4 · inbound

RoboAgent: Chaining Basic Capabilities for Embodied Task Planning cites this paper.

RoboAgent: Chaining Basic Capabilities for Embodied Task Planning GTR: Guided Thought Reinforcement Prevents Thought Collapse in RL-based VLM Agent Training

Reference 114

Resolution
verified exact
arxiv_id, observed 2026-05-11T05:15:57.094252Z

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.

source=pdf_text observed=2026-05-10T18:15:08.727921Z digest=sha256:ea1c9de368ef5f48796bc78c6c4fe1c4d6503d30455ecb6a7cd5e495d3ae52f7

Observation cefe4ba6-a065-4a31-b66b-15a07b9356e0 · inbound

Attention-guided Fine-tuning of Multimodal Large Language Models Improves Chain-of-Thought Reasoning cites this paper.

Attention-guided Fine-tuning of Multimodal Large Language Models Improves Chain-of-Thought Reasoning GTR: Guided Thought Reinforcement Prevents Thought Collapse in RL-based VLM Agent Training

Reference 12

Resolution
metadata mismatch
arxiv_id, observed 2026-07-01T22:06:16.652337Z

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.

source=arxiv_source observed=2026-06-28T15:45:26.891621Z digest=sha256:e1e165584cc950f82300338f5169b89d45b7d1c2531ab3d47fcae0bbeebeba85