Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2401.15688.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T21:08:01.263081Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
0 of 0 outbound references displayed
External citation measurements
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
No outbound reference observations are available for this paper version.
Observation c54384a2-feab-4af6-8fa8-682a9caeae27 · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation cd6e6c3e-8c2f-4df4-bef6-5615c070f2bc · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 57666f45-4c02-4096-a716-88fb6adf9943 · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 76bb28bf-5a26-45ce-a27a-de5aadb3aa0e · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation b7bc5fc3-5521-46c0-8d92-5336b9c6a151 · inbound
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
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 16cddb43-7088-4ddf-b420-4df7f2efdd5b · inbound
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
Source-reported events for the cited work
Unavailable: canonical work link unavailable.