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News/STELLAR-E: a Synthetic, Tailored, End-to-end LLM Application Rigorous Evaluator
arxiv
PublishedApril 29, 2026 at 4:00 AM
▲bullish

STELLAR-E: a Synthetic, Tailored, End-to-end LLM Application Rigorous Evaluator

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2604.24544v1 Announce Type: new Abstract: The increasing reliance on Large Language Models (LLMs) across diverse sectors highlights the need for robust domain-specific and language-specific evaluation datasets; however, the collection of such datasets is challenging due to privacy concerns, re

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Discussion
Mentioned models
02
  • 01
    Large Language Models (LLMs)
  • 02
    TGRT Self-Instruct
Source
↗
arxiv
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Tags
04
#benchmark#evaluation#language-models#synthetic-data

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Mentioned models
02
  • 01
    Large Language Models (LLMs)
  • 02
    TGRT Self-Instruct
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#benchmark#evaluation#language-models#synthetic-data
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