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pro vyhledávání: '"Kannappan, Anand"'
Retrieval Augmented Generation (RAG) techniques aim to mitigate hallucinations in Large Language Models (LLMs). However, LLMs can still produce information that is unsupported or contradictory to the retrieved contexts. We introduce LYNX, a SOTA hall
Externí odkaz:
http://arxiv.org/abs/2407.08488
FinanceBench is a first-of-its-kind test suite for evaluating the performance of LLMs on open book financial question answering (QA). It comprises 10,231 questions about publicly traded companies, with corresponding answers and evidence strings. The
Externí odkaz:
http://arxiv.org/abs/2311.11944
Autor:
Vidgen, Bertie, Scherrer, Nino, Kirk, Hannah Rose, Qian, Rebecca, Kannappan, Anand, Hale, Scott A., Röttger, Paul
The past year has seen rapid acceleration in the development of large language models (LLMs). However, without proper steering and safeguards, LLMs will readily follow malicious instructions, provide unsafe advice, and generate toxic content. We intr
Externí odkaz:
http://arxiv.org/abs/2311.08370