Selecting evidence before summarizing improves long-context reasoning efficiency

A 14-billion-parameter model trained to extract and compress relevant passages outperformed larger open-source models while using shorter outputs.

Chinese Tech
Zhaoyuan Xia (Peking University) · Qinghongbing Xie (Tsinghua University) · Yung Xiang Hue (Tsinghua University) · Jianguang Jiang (Baidu Inc) · Gaofeng Lu (Baidu Inc) · Zhenyu Jiao (Baidu Inc) · +4 more
Research Digest··2 min read
Xia et al.

The authors developed Highlight-Then-Summarize, or H2S, a compress-then-reason procedure for documents, conversations, and code.

Why this paper

From Baidu Inc. and 2 others · Part of Context Engineering for Agents, now 30 papers

In one line

Highlight-Then-Summarize compresses evidence by selecting and summarizing before answering, improving long-context reasoning.

What we could check

  • ·No code link found
  • ·No weights link found
  • ·No dataset link found
  • ·No compute details found
  • ·No stated limitations found
  • ✓Reports numbers on named benchmarks

Observed from the paper text and links we have. Absence here means we did not find it, not that it does not exist.

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