Tag: ranking
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Model inference for ranking from pairwise comparisons
Model inference for ranking from pairwise comparisons arXiv:2512.15269v1 Announce Type: cross Abstract: We consider the problem of ranking objects from noisy pairwise comparisons, for example, ranking tennis players from the outcomes of matches. We follow a standard approach to this problem and assume that each object has an unobserved strength and that the outcome of…
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Assumption-free stability for ranking problems
Assumption-free stability for ranking problems arXiv:2506.02257v1 Announce Type: new Abstract: In this work, we consider ranking problems among a finite set of candidates: for instance, selecting the top-$k$ items among a larger list of candidates or obtaining the full ranking of all items in the set. These problems are often unstable, in the sense that…
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StealthRank: LLM Ranking Manipulation via Stealthy Prompt Optimization
StealthRank: LLM Ranking Manipulation via Stealthy Prompt Optimization arXiv:2504.05804v1 Announce Type: cross Abstract: The integration of large language models (LLMs) into information retrieval systems introduces new attack surfaces, particularly for adversarial ranking manipulations. We present StealthRank, a novel adversarial ranking attack that manipulates LLM-driven product recommendation systems while maintaining textual fluency and stealth. Unlike existing…
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Ranking and Selection with Simultaneous Input Data Collection
Ranking and Selection with Simultaneous Input Data Collection arXiv:2503.11773v1 Announce Type: new Abstract: In this paper, we propose a general and novel formulation of ranking and selection with the existence of streaming input data. The collection of multiple streams of such data may consume different types of resources, and hence can be conducted simultaneously. To…
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Ranking Basics: Pointwise, Pairwise, Listwise
Ranking Basics: Pointwise, Pairwise, Listwise Because thy neighbour matters Image taken from unsplash.com First, let’s talk about where ranking comes into play. Ranking is a big deal in e-commerce and search applications — essentially, any scenario where you need to organize documents based on a query. It’s a little different from classic classification or regression problems. For…
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Ranking of Large Language Model with Nonparametric Prompts
Ranking of Large Language Model with Nonparametric Prompts arXiv:2412.05506v1 Announce Type: new Abstract: We consider the inference for the ranking of large language models (LLMs). Alignment arises as a big challenge to mitigate hallucinations in the use of LLMs. Ranking LLMs has been shown as a well-performing tool to improve alignment based on the best-of-$N$…