Intent: affirm Security Considerations# The intent classifier uses the OpenAI API to classify intents. This means that your users conversations are sent to OpenAI's servers for classification. The response generated by OpenAI is not send back to the bot's user. However, the user can craft mess...
intent_classification = """[Text]: I really need to get a gym membership, I'm exhausted. [Intent]: get gym membership [Text]: What do I need to make a carbonara? [Intent]: cook carbonara [Text]: I need all these documents sorted and filed by Monday. [Intent]:""" flan_...
4.Harnessing the power of LLMs for normative reasoning in MASs 5.LLMs Are Few-Shot In-Context Low-Resource Language Learners 6.LARA: Linguistic-Adaptive Retrieval-Augmented LLMs for Multi-Turn Intent Classification 7.InstUPR : Instruction-based Unsupervised Passage Reranking with Large Language Mod...
Chen Q, Zhuo Z, Wang W. Bert for joint intent classification and slot filling[J]. arXiv preprint arXiv:1902.10909, 2019. Siro C, Aliannejadi M, de Rijke M. Understanding user satisfaction with task-oriented dialogue systems[C]//Proceedings of the 45th International ACM SIGIR Confe...
Chen Q, Zhuo Z, Wang W. Bert for joint intent classification and slot filling[J]. arXiv preprint arXiv:1902.10909, 2019. Siro C, Aliannejadi M, de Rijke M. Understanding user satisfaction with task-oriented dialogue systems[C]//Proceedings of the 45th International ACM SIGIR Conference on...
For example, Voiceflow’s eval harness for intent classification helped them catch a 10% performance drop when upgrading from the deprecating gpt-3.5-turbo-0301 to the more recent gpt-3.5-turbo-1106. We can apply LLMs for classification by providing a document and prompting the LLM to predict...
Related, Chiang and Lee (2023) investigated whether LLMs can serve as a viable replacement for human evaluators in downstream tasks. Some examples of downstream tasks are text classification (Li et al. 2023b), intent classification (Sahu et al. 2022), toxic language detection (Hartvigsen...
2.1 Few-shots for Intent Classification Prompts For effective intent classification, few-shot examples must be provided for each intent. This should be done in the form of CSV files with two columns:User InputandResponse.User Inputshould contain examples of user utterances, whileResponseindicates whe...
'One size doesn't fit all': Learning how many Examples to use for In-Context Learning for Improved Text Classification, by Manish Chandra, Debasis Ganguly, Yiwen Li and Iadh Ounis "In-Context Learning" or: How I learned to stop worrying and love "Applied Information Retrieval", by Andrew...
Text Classification:This involves labeling entire pieces of text with specific categories. For example, annotators might label a tweet as “toxic” or “non-toxic” or classify a paragraph as “biased” or “neutral.” These labels teach LLMs to detect and avoid generating harmful or biased co...