arXiv (OAI)
open access
SSR-Zero: Simple Self-Rewarding Reinforcement Learning for Machine Translation
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
- CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing#16621
- Compact Visuotactile World Models for Lifting: Prediction, Reward Alignment, and Force Constraints#998437
- Rewarding Reasoning, Not Answers: Fixing and Bounding Test-Time Reinforcement Learning on Medical QA#1122674
- Generative Artificial Intelligence to Transform Inpatient Discharge Summaries to Patient-Friendly Language and Format#686423
- Generative AI-Driven Automated Financial Advisory Systems: Integrating NLP and Reinforcement Learning for Personalized Investment Strategies in FinTech Applications#708992
Record · ID 173298
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