arXiv (All)
open access
AskQE: Question Answering as Automatic Evaluation for Machine Translation
How can a monolingual English speaker determine whether an automatic translation in French is good enough to be shared? Existing MT error detection and quality estimation (QE) techniques do not address this practical scenario. We introduce AskQE, a question generation and answering framework designe
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
- Leveraging Language Models for Log Statement Generation in Multilingual Scenarios: How Far Are We?#229584
- IGT @ FinMMEval 2026 Task 2: Question-Type Prompting with Targeted Extraction for Multilingual Financial QA#985524
- The Blindness of Document-Level Translation Evaluation#973564
- Bactrainus: Optimizing Large Language Models for Multi-hop Complex Question Answering Tasks#629756
- Bactrainus: Optimizing Large Language Models for Multi-hop Complex Question Answering Tasks#627894
Record · ID 1049630
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