Making Large Language Models Interactive: A Pioneer Study on Supporting Complex Information-Seeking Tasks with Implicit Constraints

Understand

Current interactive systems with natural language interfaces lack the ability to understand a complex information-seeking request which expresses several implicit constraints at once, and there is no prior information about user preferences e.g.,"find hiking trails around San Francisco which are accessible with toddlers and have beautiful scenery in summer", where output is a list of possible suggestions for users to start their exploration.

• In such scenarios, user requests can be issued in one shot in the form of a complex and long query, unlike conversational and exploratory search models, where require short utterances or queries are often presented to the system step by step.
• We have designed and deployed a platform to collect the data from approaching such complex interactive systems.
• Moreover, despite with the current advancement of generative language models these models suffer from hallucination in providing accurate factual knowledge.