Daily edition · Information Retrieval
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37 articles · 3 sources · 36 papers ·
Top topics: Information Retrieval · AI Research · AI
PGX Inc. has released version 1.0 of pgx-bm25, an extension that adds Okapi BM25 ranked full-text search to PostgreSQL as a native index access method. It supports PostgreSQL 17 and 18, and installs as bm25_native.…
arXiv:2610.08200v1 Announce Type: new Abstract: We ask whether specific attention heads, and more finely specific neurons inside those heads, are responsible for recognizing that a language model's context contains…
arXiv:2610.08232v1 Announce Type: new Abstract: Since the early adoption of e-commerce, travel and tourism has been a lab for the design of recommender systems: tools that help travelers choose destinations, flights,…
arXiv:2610.07091v1 Announce Type: cross Abstract: The evolution of machine learning has progressively changed where intelligence resides in an AI system. In conventional machine learning the task, data representation,…
arXiv:2610.08463v1 Announce Type: cross Abstract: Long-context inference and Retrieval-Augmented Generation (RAG) handle evidence selection at vastly different scales, from a single long prompt to an entire corpus. We…
arXiv:2610.07309v1 Announce Type: cross Abstract: Long-term-memory agents can retrieve relevant information that is inadmissible for the current request because it belongs to another principal, violates policy, or…
arXiv:2409.19979v4 Announce Type: replace Abstract: Large language models (LLMs) have demonstrated prominent reasoning capabilities in recommendation tasks by transforming them into text-generation tasks. However,…
arXiv:2610.06902v1 Announce Type: cross Abstract: Retrieval-augmented generation grounds language models in external context, but for long documents flat top-$k$ retrieval can cluster on a single region and miss…
arXiv:2312.11018v3 Announce Type: replace Abstract: Bundle recommendation ranks sets of related items rather than isolated items. Its central challenge is to connect user preferences, item interactions, and bundle…
arXiv:2610.06857v1 Announce Type: cross Abstract: SQL efficiency optimization aims to transform slow queries into semantically equivalent but faster alternatives. However, directly optimizing SQL with large language…
arXiv:2610.05028v2 Announce Type: replace Abstract: Geographic information retrieval (GeoIR) tasks require systems to interpret ambiguous toponyms for downstream applications. Traditionally, toponym resolution relies on…
arXiv:2610.07960v1 Announce Type: new Abstract: Recent advances in agentic search have given large language model (LLM) agents finer control over corpus exploration. However, search interfaces often return matching…
arXiv:2610.08407v1 Announce Type: new Abstract: Contextual information, capturing the circumstances of a user-item interaction, is central to recommender systems. Prior work draws context from location, time, or…
arXiv:2610.08732v1 Announce Type: new Abstract: Generative Information Retrieval (GIR) has emerged as a transformative paradigm, shifting document retrieval from a traditional "retrieve-and-rank" workflow to…
arXiv:2610.07622v1 Announce Type: new Abstract: Recent advancements in large language models have introduced new capabilities for reasoning over structured data, particularly through program-aided tools that can analyze…
arXiv:2609.34577v2 Announce Type: replace-cross Abstract: Informative Path Planning for scalar field reconstruction uses predictive uncertainty to direct sensing vehicles toward maximally informative locations. Gaussian…
arXiv:2610.07731v1 Announce Type: new Abstract: Dense retrieval models are typically trained with contrastive objectives that learn effective representations but do not directly optimize retrieval metrics or downstream…
arXiv:2610.07761v1 Announce Type: new Abstract: In this work, we propose a novel recommendation model, CLARER (Contrastive Learning for Aspect Representation towards Explainable Recommendation) that integrates aspect…
arXiv:2610.07266v1 Announce Type: new Abstract: Retriever upgrades are typically evaluated using aggregate metrics, which can hide regressions on queries the previous retriever already served correctly. We study these…
arXiv:2610.08716v1 Announce Type: new Abstract: Generative retrieval trains a language model to generate the identifier of a relevant document. Recent work replaces the autoregressive decoder with diffusion, but changes…
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