arXiv (All)
open access
Overview of the NTCIR-19 Automatic Evaluation of LLMs 2 (AEOLLM-2) Task
In this paper, we provide an overview of the NTCIR-19 Automatic Evaluation of LLMs 2 (AEOLLM-2) task. Building on the success of the NTCIR-18 core task AEOLLM, we proposed AEOLLM-2 for NTCIR-19 to further investigate automatic evaluation methods for Large Language Models (LLMs), particularly in long
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
- A Survey on Evaluation of Large Language Models#16569
- Uncheatable Eval: Dynamic Compression-Based Evaluation of Language Models#1064054
- XQDT: eXplainable and Quantitative Data-Text Alignment Metric with Feedback Signals#820683
- Recognition-Refusal Misalignment in LLMs: Why Models Answer Structurally Unanswerable Questions#793331
- Recognition-Refusal Misalignment in LLMs: Why Models Answer Structurally Unanswerable Questions#789327
Record · ID 1248878
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