AI Paper Atlas

Research map / Architectures and efficiency / Attention and transformers

Generating Coherent Narratives by Learning Dynamic and Discrete Entity States with a Contrastive Framework

AAAI 2023 · Architectures and efficiency › Attention and transformers · approach: Language model pretraining and induction · 4 citations (OpenAlex)

Read the paperCheck your idea against 108,967 papers

AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.

Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use dynamic discrete entity states learned with a contrastive objectiveBART-Base narrative generation · Wikiplots testB-1: 29.81 -> 31.81Helped
Use dynamic discrete entity states learned with a contrastive objectiveBART-Base narrative generation · Wikiplots testMAUVE: 80.16 -> 87.88Helped
Use dynamic discrete entity states learned with a contrastive objectiveBART-Base narrative generation · CNN News testB-1: 33.07 -> 33.83Helped
Use dynamic discrete entity states learned with a contrastive objectiveBART-Base narrative generation · CNN News testMAUVE: 87.25 -> 91.02Helped
Use dynamic discrete entity states learned with a contrastive objectiveBART-Base narrative generation · CNN News testRpt-16: 14.37 -> 14.29Helped
Add entity state attention layer (ablation)ERIC · Wikiplots testB-1: 30.12 -> 31.81Helped
Add entity state attention layer (ablation)ERIC · Wikiplots testMAUVE: 83.29 -> 87.88Helped
Add entity state attention layer (ablation)ERIC · Wikiplots testRpt-16: 16.75 -> 16.22Helped
Add entity state representations and contrastive learning (ablation)ERIC · Wikiplots testB-1: 28.84 -> 31.81Helped
Add entity state representations and contrastive learning (ablation)ERIC · Wikiplots testMAUVE: 83.18 -> 87.88Helped
Add entity states, contrastive learning, and next-mentioned-entity prediction (ablation)ERIC · Wikiplots testB-1: 28.63 -> 31.81Helped
Add entity states, contrastive learning, and next-mentioned-entity prediction (ablation)ERIC · Wikiplots testMAUVE: 73.01 -> 87.88Helped

Closest papers by meaning

Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.

Open scime draft

Get the next scime Dispatch and a monthly field update

Free. We send a confirmation link first; every email has a one-click unsubscribe. Privacy