dingxingdi Skill: long-form coherent summarization
1. Capability Definition & Real Case
- Professional Definition: The ability to summarize very long documents while preserving global coherence across chunk boundaries, maintaining a readable narrative structure rather than a bag of disconnected local summaries. The capability is primarily about long-range continuity: who is being discussed, what happened, why it matters, and how later parts relate to earlier ones after chunk-and-compress processing.
- Dimension Hierarchy: Document Transformation & Synthesis->Summarization->long-form coherent summarization
Real Case
[Case 1]
- Initial Environment: A recently published book far longer than the model context window is split into chunked inputs, and the system must produce one global summary from the entire book.
- Real Question: "Summarize the following book-length document."
- Real Trajectory: The system first generates chunk-level summaries and then either hierarchically merges them or incrementally updates a running summary while compressing when necessary.
- Why this demonstrates the capability: The benchmark explicitly studies what happens when long summarization requires chunking, merging, updating, and compression. The central quality target is coherence, not just lexical overlap with a reference. This makes it the right case for testing long-range continuity under context pressure.
[Case 2]
- Initial Environment: A long government report, patent, or transcript is supplied as a single-document summarization task in a long-context evaluation suite.
- Real Question: "Write a summary of the document that preserves the important information across the whole context."
- Why this demonstrates the capability: These tasks test whether a model can aggregate information spread across many pages without collapsing into omissions, contradictions, or duplicated points. Unlike short-article summarization, the model must keep section-to-section continuity and relative salience under long input lengths. This demonstrates practical long-document summarization beyond book fiction.
Pipeline Execution Instructions
To synthesize data for this capability, you must strictly follow a 3-phase pipeline. Do not hallucinate steps. Read the corresponding reference file for each phase sequentially:
Phase 1: Environment Exploration Read the exploration guidelines to discover raw knowledge seeds:
references/EXPLORATION.mdPhase 2: Trajectory Selection Once Phase 1 is complete, read the selection criteria to evaluate the trajectory:
references/SELECTION.mdPhase 3: Data Synthesis Once a trajectory passes Phase 2, read the synthesis instructions to generate the final data:
references/SYNTHESIS.md