Show HN: Unlearning Comparator, a visual tool to compare machine unlearning
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Show HN: Improving RAG with chess Elo scores
Show HN: Improving RAG with chess Elo scores Hello HN,<p>I'm Ghita, co-founder of ZeroEntropy (YC W25). We build high accuracy search infrastructure for RAG and AI Agents.<p>We just released two new state-of-the-art rerankers zerank-1, and zerank-1-small. One of them is fully open-source under Apache 2.0.<p>We trained those models using a novel Elo score inspired pipeline which we describe in detail in the blog attached. In a nutshell, here is an outline of the training steps: * Collect soft preferences between pairs of documents using an ensemble of LLMs. * Fit an ELO-style rating system (Bradley-Terry) to turn pairwise comparisons into absolute per-document scores. * Normalize relevance scores across queries using a bias correction step, modeled using cross-query comparisons and solved with MLE.<p>You can try the models either through our API (<a href="https://docs.zeroentropy.dev/models">https://docs.zeroentropy.dev/models</a>), or via HuggingFace (<a href="https://huggingface.co/zeroentropy/zerank-1-small" rel="nofollow">https://huggingface.co/zeroentropy/zerank-1-small</a>).<p>We would love this community's feedback on the models, and the training approach. A full technical report is also going to be released soon.<p>Thank you!
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