arXiv (OAI Expanded)
open access
Unifying Conformal Language Tasks with In-Context Ensembles
Many NLP tasks, such as summarization and extractive question answering, reduce to retrieving relevant content from documents under two constraints: coverage, retaining enough pertinent information to achieve some goal, and conciseness, removing as much irrelevant information as possible. Conformal
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Unifying Conformal Language Tasks with In-Context Ensembles#925378
- Operationalising Representation in Natural Language Processing#705444
- Large Language Models Are Effective Human Annotation Assistants, But Not Good Independent Annotators#177042
- VocabTailor: Dynamic Vocabulary Selection for Downstream Tasks in Small Language Models#153119
- Where to Look and What to Use: Retrieve-Localize-Generate for Long-Term Conversational Memory Question Answering#1109154
Record · ID 921142
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive