Paper Citation Record · LEDGER

Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2401.15688.

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

pith.paper-citation-record.v1
2401.15688 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T10:44:14.819612Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation c54384a2-feab-4af6-8fa8-682a9caeae27 · inbound

ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment cites this paper.

ELLA: Equip Diffusion Models with LLM for Enhanced Semantic Alignment Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-11T19:43:03.462129Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation edbb091c-f354-41dc-849a-095fe5d5a7f5 · inbound

SPAgent: Adaptive Task Decomposition and Model Selection for General Video Generation and Editing cites this paper.

SPAgent: Adaptive Task Decomposition and Model Selection for General Video Generation and Editing Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-12T10:44:14.819612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6f86732-2de4-403c-b4d3-cb37a9736e51 · inbound

GenMAC: Compositional Text-to-Video Generation with Multi-Agent Collaboration cites this paper.

GenMAC: Compositional Text-to-Video Generation with Multi-Agent Collaboration Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-11T21:28:21.187840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23e8be3f-bce4-4c19-8a68-135c0d0f84dd · inbound

SILMM: Self-Improving Large Multimodal Models for Compositional Text-to-Image Generation cites this paper.

SILMM: Self-Improving Large Multimodal Models for Compositional Text-to-Image Generation Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-11T20:25:14.995830Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 32184a7e-8a9e-4c6a-9641-b754716e4bb3 · inbound

CC-Diff: Enhancing Contextual Coherence in Remote Sensing Image Synthesis cites this paper.

CC-Diff: Enhancing Contextual Coherence in Remote Sensing Image Synthesis Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-11T17:48:40.800111Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd6e6c3e-8c2f-4df4-bef6-5615c070f2bc · inbound

Divide-and-Conquer Approach to Holistic Cognition in High-Similarity Contexts with Limited Data cites this paper.

Divide-and-Conquer Approach to Holistic Cognition in High-Similarity Contexts with Limited Data Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-10T03:03:36.885686Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 57666f45-4c02-4096-a716-88fb6adf9943 · inbound

GenED-SC: Generative Editing Semantic Communication with Integrated Multi-Modal LLMs cites this paper.

GenED-SC: Generative Editing Semantic Communication with Integrated Multi-Modal LLMs Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

Reference 9

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T21:46:15.005895Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 76bb28bf-5a26-45ce-a27a-de5aadb3aa0e · inbound

MetaPoint: Unlocking Precise Spatial Control in Agentic Visual Generation cites this paper.

MetaPoint: Unlocking Precise Spatial Control in Agentic Visual Generation Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-07-02T08:16:48.445622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b7bc5fc3-5521-46c0-8d92-5336b9c6a151 · inbound

ReGRPO: Reflection-Augmented Policy Optimization for Tool-Using Agents cites this paper.

ReGRPO: Reflection-Augmented Policy Optimization for Tool-Using Agents Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-07-01T10:35:41.892548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 16cddb43-7088-4ddf-b420-4df7f2efdd5b · inbound

Think, Plan, Paint: Layout-Aware Reasoning for Controllable Image Generation in Unified Models cites this paper.

Think, Plan, Paint: Layout-Aware Reasoning for Controllable Image Generation in Unified Models Divide and Conquer: Language Models can Plan and Self-Correct for Compositional Text-to-Image Generation

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-01T21:08:01.263081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.