ReSUM - SQuALITY - R2: leaderboard

ReSUM v1 Table5: query-focused long-meeting summarization on QMSum and SQuALITY; source-native zero-shot, CoT, RAG, fine-tuned and multi-agent methods remain separate run identities. Short source model labels (including LLaMA3-3B and GPT-4-mini) are not bound to a guessed checkpoint. R1/R2/RL, BERTScore, Mover and COMET are native 0–1 values; chrF is native percent. No transformation, model alias, cross-method pooling or resource metric.

Metric: Native score (0–1). Source: arxiv.org. Saturation forecast: Rough model projection: around 2026. 16 models tracked.

Top models

#ModelScoreOverall rank
1FT+Res Qwen (ReSUM Run: method=End-to-End Fine-tuned with Reasoning;checkpoint=source-native;effort=unreported)0.14
2Our Method (ReSUM Run: method=ReSUM Multi-Agent;checkpoint=source-native;effort=unreported)0.13
3FT LLaMA (ReSUM Run: method=Fine-tuned (FT);checkpoint=source-native;effort=unreported)0.09
4FT Qwen (ReSUM Run: method=Fine-tuned (FT);checkpoint=source-native;effort=unreported)0.09
5FT+Res LLaMA (ReSUM Run: method=End-to-End Fine-tuned with Reasoning;checkpoint=source-native;effort=unreported)0.09
6GPT-4-mini (ReSUM Run: method=Zero-shot;checkpoint=source-native;effort=unreported)0.08
7Qwen3-4B (ReSUM Run: method=Zero-shot;checkpoint=source-native;effort=unreported)0.07
8COT LLaMA (ReSUM Run: method=Chain-of-Thought (CoT);checkpoint=source-native;effort=unreported)0.07
9COT Qwen (ReSUM Run: method=Chain-of-Thought (CoT);checkpoint=source-native;effort=unreported)0.07
10LLaMA3-3B (ReSUM Run: method=Zero-shot;checkpoint=source-native;effort=unreported)0.06

Interactive version: theaggregate.ai/benchmark?slug=resum-squality-r2 · How It Works · Data refreshed daily, snapshot 2026-11-12.