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Structured Composition of Verifiable Atomic Insights for Table-to-Report Generation

Paper recorded by Signals 4 on 2026-10-02 in cs.CL. Abstract reproduced from arXiv; link to the original below.

Published 2026-10-02 on arXiv · recorded by Signals 4 on 2026-10-05

Category: cs.CL · 自然语言处理 · first seen 2026-10-05

Abstract

Table-to-report generation refers to the task of automatically generating article-level analyt- ical reports from relational tables and is an essential capability for automated data science and decision support. Its central challenge lies in systematically discovering verifiable com- posite insights across tables, attributes, and analytical perspectives, and organizing them into coherent, complete

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#339 most recent of 660 cs.CL papers we have recorded · ↑ newer: Divergence controls entropy in distillation · ↓ older: Learning from Repaired Reasoning: Root-Cause-Guided On-Policy Distilla
Cite this page: Structured Composition of Verifiable Atomic Insights for Table-to-Report Generation: the #339 most recent of 660 cs.CL papers we have recorded (as of 2026-10-02). Source: Signals 4 (Signals API) — https://data.jiangzhang.ca/signals4/t/papers/structured-composition-of-verifiable-atomic-insights-for-table-to-report-generat.html
Free to quote with attribution to “Signals 4 (Signals API)”. Machine-readable: papers.json
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