Topic - Edition
Client-Side Rendering ships a minimal HTML shell to the browser, relying on the user device to download, parse, and execute JavaScript bundles to render UI and fetch data. Server-Side Rendering executes application…
arXiv:2605.14786v2 Announce Type: replace-cross Abstract: As LLM-based agents increasingly browse the web on users' behalf, a natural question arises: can websites passively identify which underlying model powers an…
arXiv:2611.14037v1 Announce Type: new Abstract: Many heritage institutions hold extensive collections of show programs. Too numerous to be cataloged individually, they remain difficult to access and are still largely…
arXiv:2611.14149v1 Announce Type: new Abstract: Information seeking in large language model (LLM) systems increasingly involves decisions about when to acquire information, where to search, and how to evaluate and use…
arXiv:2611.14477v1 Announce Type: new Abstract: Text-to-SQL systems over large pooled catalogs must first retrieve the tables a question needs. We compare against the published table recall of RASL, which uses Claude…
arXiv:2605.15790v2 Announce Type: replace-cross Abstract: Retrieval-Augmented Generation (RAG) grounds large language models (LLMs) in external knowledge, but the retrieved documents can systematically skew generated…
arXiv:2611.13127v1 Announce Type: cross Abstract: Retrieval-augmented language model systems generally select context by query-conditioned relevance. We argue that long-lived AI systems require a second operator:…
arXiv:2611.13797v1 Announce Type: new Abstract: We study hard-label distillation from Gemini 3.1 Flash-Lite to compact encoders on 5.34 million Turkish marketplace reviews. A strict new-SKU temporal test measures…
arXiv:2611.13055v1 Announce Type: cross Abstract: A document preserves the visible result of professional work but often discards the research, calculations, assumptions, evidence, and authorization boundaries behind…
arXiv:2609.04961v2 Announce Type: replace Abstract: E-commerce search often suffers from vocabulary mismatch between user queries and merchant-authored product titles, since short titles cannot fully cover diverse user…
arXiv:2611.13361v1 Announce Type: cross Abstract: Modern e-commerce platforms naturally provide three complementary modalities: textual item descriptions, item images, and user reviews. However, existing multimodal…
arXiv:2611.13595v1 Announce Type: cross Abstract: Verifying corporate financial disclosures against the International Financial Reporting Standards (IFRS) is a core auditing task in which experts cross-reference…
arXiv:2611.13966v1 Announce Type: new Abstract: Taxonomies are structured knowledge representations that support semantic search, recommendation, product catalog organization, and retrieval-augmented generation. Their…
arXiv:2611.13539v1 Announce Type: new Abstract: Researchers and engineers improve recommendation systems by performing A/B experiments with new model architectures, optimization methods, and data features. However,…
arXiv:2607.20938v2 Announce Type: replace Abstract: Traditional recommendation systems rely on latent (dense) representations, making them difficult to interpret and control. We propose the Controllable and…
arXiv:2611.14220v1 Announce Type: new Abstract: Next point-of-interest (POI) prediction supports personalized location services by anticipating users' next destinations. Recent methods leverage large language models…
arXiv:2611.14004v1 Announce Type: new Abstract: As multimodal tourism-related information collected from heterogeneous data sources has become increasingly available, learning effective representations has attracted…
arXiv:2611.14236v1 Announce Type: cross Abstract: Transformer sentence encoders provide strong retrieval quality, but their inference cost becomes a bottleneck when embeddings must be produced on CPUs or refreshed…
arXiv:2610.36991v4 Announce Type: replace-cross Abstract: Retrieval-augmented generation (RAG) systems ground large language models (LLMs) by retrieving external evidence and conditioning generation on the retrieved…
arXiv:2611.12957v1 Announce Type: new Abstract: VLM-based agents solve complex tasks by iteratively interacting with environments, and their effectiveness depends heavily on how the environment exposes information and…
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