Research map / Large language models / Alignment and preferences
Learning to summarize with human feedback
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.
Closest papers by meaning
- Learning from Failure: Improving Meeting Summarization without Good Samples (AAAI 2024 · similarity 0.90)
- PersonalSum: A User-Subjective Guided Personalized Summarization Dataset for Large Language Models (NeurIPS 2024 · similarity 0.88)
- Maximizing Signal in Human-Model Preference Alignment (AAAI 2025 · similarity 0.87)
- Learning to Summarize by Learning to Quiz: Adversarial Agentic Collaboration for Long Document Summarization (ICLR 2026 · similarity 0.87)
- Enabling Lanuguage Models to Implicitly Learn Self-Improvement (ICLR 2024 · similarity 0.86)
- BooookScore: A systematic exploration of book-length summarization in the era of LLMs (ICLR 2024 · similarity 0.86)
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.