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Found 5 papers, 1 papers with code
Generate then Retrieve: Conversational Response Retrieval Using LLMs as Answer and Query Generators
In these methods, we leverage the capabilities of large language models (LLMs) in understanding the user's information need and generating an appropriate response, to generate multiple queries.
TREC iKAT 2023: The Interactive Knowledge Assistance Track Overview
Conversational Information Seeking has evolved rapidly in the last few years with the development of Large Language Models providing the basis for interpreting and responding in a naturalistic manner to user requests.
Let the LLMs Talk: Simulating Human-to-Human Conversational QA via Zero-Shot LLM-to-LLM Interactions
Our framework involves two LLMs interacting on a specific topic, with the first LLM acting as a student, generating questions to explore a given search topic.
PQuAD: A Persian Question Answering Dataset
We present Persian Question Answering Dataset (PQuAD), a crowdsourced reading comprehension dataset on Persian Wikipedia articles.
Text-based Question Answering from Information Retrieval and Deep Neural Network Perspectives: A Survey
Text-based Question Answering (QA) is a challenging task which aims at finding short concrete answers for users' questions.
