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Found 5 papers, 5 papers with code
Ranked List Truncation for Large Language Model-based Re-Ranking
RLT is crucial for re-ranking as it can improve re-ranking efficiency by sending variable-length candidate lists to a re-ranker on a per-query basis.
Query Performance Prediction using Relevance Judgments Generated by Large Language Models
This allows us to predict any IR evaluation measure using the generated relevance judgments as pseudo-labels; Also, this allows us to interpret predicted IR evaluation measures, and identify, track and rectify errors in generated relevance judgments to improve QPP quality.
Self-seeding and Multi-intent Self-instructing LLMs for Generating Intent-aware Information-Seeking dialogs
Furthermore, we propose SOLID-RL, which is further trained to generate a dialog in one step on the data generated by SOLID.
Query Performance Prediction: From Ad-hoc to Conversational Search
The QPP task is to predict the retrieval quality of a search system for a query without relevance judgments.
RefNet: A Reference-aware Network for Background Based Conversation
In this paper, we propose a Reference-aware Network (RefNet) to address the two issues.
