少量样本提示提升工具调用效率 在大型语言模型(LLM)的应用中,工具的使用至关重要。我们一直在研究如何提升LLM调用工具的性能。一种常见的提升方法是通过少量样本提示,即将一些模型输入的示例和期望的输出结果直接展示给模型。据Language Models are Few-Shot Learners一文,这种方法能够在多种任务中显著提高模型的表现。本...
Power of LLMs for prevalent language-based ML tasks using prompting and analyze the pros and cons of zero-shot and few-shot prompting.
Paper tables with annotated results for SPARSEFIT: Few-shot Prompting with Sparse Fine-tuning for Jointly Generating Predictions and Natural Language Explanations
We used the MedVInT-TD model with PMC-LLaMA and PMC-CLIP backbones. OpenFlamingo Awadalla et al. (2023), a powerful VLM which was trained on generaldomain data, and which served as the base model to train Med-Flamingo. We report both zero-shot and few-shot performance. We expect ...
WikiSP, a few-shot Seq2Seq semantic parserby fine-tuning LLaMA with a few shot training set. We improve the learnability of SPARQL queries by replacing the IDs of properties and domains with their unique names; we tolerate errors in entity linking by accepting mentions in the que...
with RadGraph and Few-Shot Prompting Benjamin Yan1, Ruochen Liu1, David E. Kuo1, Subathra Adithan2, Eduardo Pontes Reis1,3, Stephen Kwak4, Vasantha Kumar Venugopal5, Chloe P. O’Connell6, Agustina Saenz7, Pranav Rajpurkar7,†, Michael Moor1,† ...
We expect that the rise of multimodal medical few-shot learners will lead to exciting opportunities with regard to model explainability (via rationale generation) as well as grounding the model in verified sources (via multimodal retrieval to augment the few-shot prompt). Thereby, our work serv...
For this, we perform data generation leveraging the Prompting framework, suggesting that language models contain valuable task-agnostic knowledge that can be used beyond the common pre-training/fine-tuning scheme. As a result, we consistently outperform previous approaches on few-shot Question Answering...
can someone please advise on how to do few-shot prompting with llama-guard as mentioned in this paper? (at section 3.2) Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations Alternatives No response Additional context I tried custom taxonomy categories and none of them seems ...
KECP: Knowledge Enhanced Contrastive Prompting for Few-shot Extractive Question Answering. In Proceedings of the 2022 Conference on Empirical Methods in Natu-ral Language Processing, Abu Dhabi, United Arab Emirates, 7–11 December 2022. [Google Scholar] Xu, W.-W.; Li, X.; Zhang, W.-X.; ...