arXiv (All)
open access
Overfitting Mitigation via Singular Value Decomposition in Minimum Bayes Risk Decoding
Minimum Bayes Risk (MBR) decoding enables high-quality text generation by selecting the hypothesis that maximizes a utility metric over sampled pseudo-references. However, it is highly susceptible to metric overfitting: it can irregularly inflate the chosen utility metric at the direct expense of ot
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
- Consensus Group Relative Policy Optimization for Text Generation#927222
- Noisy-Channel Minimum Bayes Risk Decoding#343487
- Page-Aware Retrieval-Augmented Generation for EvalLLM 2026: A Five-Variant Study on French PDFs#1129397
- LLMAR: A Tuning-Free Recommendation Framework for Sparse and Text-Rich Industrial Domains#998189
- Position: It's time to act on the risk of efficient personalized text generation#208832
Record · ID 821107
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