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Paper Citation Record · LEDGER

AgentRefine: Enhancing Agent Generalization through Refinement Tuning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2501.01702.

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

pith.paper-citation-record.v1
2501.01702 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:11:55.463221Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T20:48:56.423902Z

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 6d14c2c3-a659-4623-831a-f5bc105149cd · inbound

Large Language Models for Planning: A Comprehensive and Systematic Survey cites this paper.

Large Language Models for Planning: A Comprehensive and Systematic Survey AgentRefine: Enhancing Agent Generalization through Refinement Tuning

Reference 66

Resolution
unresolved
no resolver link, observed 2026-08-07T14:11:55.463221Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:11:55.463221Z digest=sha256:1b97e1b699828fda928a6f0bd252459b365a15744bb49c44a9f88b9c86c15c82

Observation 644eca4f-dee4-4cdd-a7f4-01188eee14f7 · inbound

Agent-Environment Alignment via Automated Interface Generation cites this paper.

Agent-Environment Alignment via Automated Interface Generation AgentRefine: Enhancing Agent Generalization through Refinement Tuning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-07T13:45:31.292672Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:45:31.292672Z digest=sha256:3a66fbc96363c5c16a578cd05546088a704b7d158f81f1b3845f7452baec2121

Observation c9a98375-1970-4930-a02b-426f3af5ff02 · inbound

PGPO: Enhancing Agent Reasoning via Pseudocode-style Planning Guided Preference Optimization cites this paper.

PGPO: Enhancing Agent Reasoning via Pseudocode-style Planning Guided Preference Optimization AgentRefine: Enhancing Agent Generalization through Refinement Tuning

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-07T11:47:00.667874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T11:47:00.667874Z digest=sha256:9ed57fdc7ac51276cde745c33922fabee9a1a6005d88040a09582a952e950bb0

Observation 6a5dedfc-061a-41d8-b712-4157991f9fe6 · inbound

RLVMR: Reinforcement Learning with Verifiable Meta-Reasoning Rewards for Robust Long-Horizon Agents cites this paper.

RLVMR: Reinforcement Learning with Verifiable Meta-Reasoning Rewards for Robust Long-Horizon Agents AgentRefine: Enhancing Agent Generalization through Refinement Tuning

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T11:21:25.444678Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T11:21:25.444678Z digest=sha256:a9182eda3fee69cf2a58fc6dafe33b3e2b80a1d78cf99a85378f6a836cd2e6c2

Observation 7c2cb04b-f4bc-4af7-95a3-bae0d1e053a4 · inbound

Source Component Shift Adaptation via Offline Decomposition and Online Mixing Approach cites this paper.

Source Component Shift Adaptation via Offline Decomposition and Online Mixing Approach AgentRefine: Enhancing Agent Generalization through Refinement Tuning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-05T20:35:42.954633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:35:42.954633Z digest=sha256:30f8e90b137d65aca90b6537e62e0a61e6a8585c838ed5dda06ade1894b23114

Observation d8d751b2-fc5c-4fbf-8159-3cefec194abb · inbound

Leveraging OS-Level Primitives for Robotic Action Management cites this paper.

Leveraging OS-Level Primitives for Robotic Action Management AgentRefine: Enhancing Agent Generalization through Refinement Tuning

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-05T20:38:39.405045Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T20:38:39.405045Z digest=sha256:8543cbf2d8dbf17093f2d4c709f505639f9079f9a359baf7c37dbfce29074b34

Observation c975513a-09f3-49bd-a2fe-3067633210df · inbound

From History to State: Constant-Context Skill Learning for LLM Agents cites this paper.

From History to State: Constant-Context Skill Learning for LLM Agents AgentRefine: Enhancing Agent Generalization through Refinement Tuning

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-11T18:01:05.502490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-08T16:50:43.547830Z digest=sha256:42e63a2d3ed8c1204195fb2864fe43ea8a28c9e7b93d907f3298d7426911ca7b

Observation 072174d9-9e44-4abc-9638-4ea9a8a01b69 · inbound

Test-Time Deep Thinking to Explore Implicit Rules cites this paper.

Test-Time Deep Thinking to Explore Implicit Rules AgentRefine: Enhancing Agent Generalization through Refinement Tuning

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-06-30T11:54:38.208867Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T11:52:15.163893Z digest=sha256:8ed21943b40efde64c609fe41e2b6fa673a377b6abd68c98931c2e6934f2a243

Observation 376eb1ba-609a-495e-b4b3-86f7a7c16cbe · inbound

OPD-Evolver: Cultivating Holistic Agent Evolver via On-Policy Distillation cites this paper.

OPD-Evolver: Cultivating Holistic Agent Evolver via On-Policy Distillation AgentRefine: Enhancing Agent Generalization through Refinement Tuning

Reference 118

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T20:48:56.425501Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=arxiv_source observed=2026-06-27T01:07:49.603969Z digest=sha256:562fa39745c3a032e8d0a166f81843c793cafdd374d6692ec4763366cea5adea

Observation ddddbc5f-1585-4c36-8a98-841c2807c6af · inbound

Agentic-DPO: From Imitation to Agentic Policy Optimization on Expert Trajectories cites this paper.

Agentic-DPO: From Imitation to Agentic Policy Optimization on Expert Trajectories AgentRefine: Enhancing Agent Generalization through Refinement Tuning

Reference 12

Resolution
unresolved
no resolver link, observed 2026-07-14T10:33:54.851493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T10:33:54.851493Z digest=sha256:1c626a4fd6c7d8b844af5ad79d39b1ab17b10afc1fe9a90e2cf9b038b1c260f2

Observation 6af45b6f-4368-4aab-b860-146e11fd5df8 · inbound

Beyond Action Imitation: Learning a Decision-Aware User Simulator for Online Advertising cites this paper.

Beyond Action Imitation: Learning a Decision-Aware User Simulator for Online Advertising AgentRefine: Enhancing Agent Generalization through Refinement Tuning

Reference 10

Resolution
unresolved
no resolver link, observed 2026-07-30T17:56:01.404123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-30T17:56:01.404123Z digest=sha256:4f3d4dd6f0726519d904a9cd2bedac22a3533e6838c08b1b6f3fe3c90df84602