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of 4
pro vyhledávání: '"BehnamGhader, Parishad"'
Autor:
BehnamGhader, Parishad, Adlakha, Vaibhav, Mosbach, Marius, Bahdanau, Dzmitry, Chapados, Nicolas, Reddy, Siva
Large decoder-only language models (LLMs) are the state-of-the-art models on most of today's NLP tasks and benchmarks. Yet, the community is only slowly adopting these models for text embedding tasks, which require rich contextualized representations
Externí odkaz:
http://arxiv.org/abs/2404.05961
Retriever-augmented instruction-following models are attractive alternatives to fine-tuned approaches for information-seeking tasks such as question answering (QA). By simply prepending retrieved documents in its input along with an instruction, thes
Externí odkaz:
http://arxiv.org/abs/2307.16877
Augmenting pretrained language models with retrievers has shown promise in effectively solving common NLP problems, such as language modeling and question answering. In this paper, we evaluate the strengths and weaknesses of popular retriever-augment
Externí odkaz:
http://arxiv.org/abs/2212.09146
Although large pre-trained language models have achieved great success in many NLP tasks, it has been shown that they reflect human biases from their pre-training corpora. This bias may lead to undesirable outcomes when these models are applied in re
Externí odkaz:
http://arxiv.org/abs/2211.14402