RankGuard is a decentralized OLTR system that filters model updates using local click data for poisoning resistance and supplies the first formal convergence guarantee for decentralized OLTR.
Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval , pages =
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Combining contrastive loss with KLD distillation and adding sparsity regularization improves effectiveness and reduces FLOPS by 2x in conversational search with minimal recall loss.
A multi-turn RAG system combines learned sparse retrieval with LLM-conditioned rewriting, listwise reranking, and generation to handle conversational QA and unanswerable queries across four domains.
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Efficient and Robust Online Learning to Rank in Decentralized Systems
RankGuard is a decentralized OLTR system that filters model updates using local click data for poisoning resistance and supplies the first formal convergence guarantee for decentralized OLTR.