Topic - Edition
arXiv:2609.28048v1 Announce Type: new Abstract: Modern information retrieval (IR) systems rarely represent time, yet many information needs depend on it: in clinical, journalistic, and legal search, when an event…
arXiv:2609.28349v1 Announce Type: cross Abstract: Quantum computing is moving from research laboratories towards early commercialization and broader socio-technical adoption, supported by sustained hardware progress and…
arXiv:2609.26856v1 Announce Type: new Abstract: Neural information retrieval for Italian is served almost entirely by multilingual models. Several multi-vector (late-interaction) retrievers include Italian among dozens…
arXiv:2609.27953v1 Announce Type: new Abstract: Some LLM-based recommendation rerankers are evaluated under an oracle protocol that guarantees the ground-truth item is present in the scored set, either by injecting it…
arXiv:2609.26780v2 Announce Type: replace-cross Abstract: Long-term conversational memory in multi-party settings requires more than retrieving relevant content from long-term conversations: it must distinguish who said…
arXiv:2609.27225v1 Announce Type: cross Abstract: Probabilistic question-answering systems -- whether large language models (LLMs) themselves, retrieval-augmented generation (RAG), or trained multi-hop retrievers --…
arXiv:2609.27784v1 Announce Type: new Abstract: Semi-structured documents are ubiquitous in scientific reports, financial statements, and technical manuals. Question answering over such documents requires simultaneous…
arXiv:2609.27998v1 Announce Type: new Abstract: Group recommender systems typically rely on either aggregating individual preferences or treating groups as distinct meta-users. However, these methods often suffer from…
arXiv:2609.27183v1 Announce Type: new Abstract: Personalized recommendation depends critically on how user representations are constructed from historical behavior. Two paradigms have emerged for constructing semantic…
arXiv:2609.28007v1 Announce Type: cross Abstract: Most Turkish-capable large language models (LLMs) are evaluated using general-purpose benchmarks rather than long, structurally complex domain documents. This paper…
arXiv:2608.22859v2 Announce Type: replace Abstract: RAG systems are increasingly used to summarize what large collections of documents say. A user asks "What do people think about X?" and receives an answer that reads…
arXiv:2609.27297v1 Announce Type: cross Abstract: Accumulated scientific knowledge advances inquiry when prior findings help researchers choose new questions, design investigations, and interpret results. Realizing this…
arXiv:2609.26975v1 Announce Type: new Abstract: Reproduction studies can produce mixed outcomes. Reported values may differ while the ordering of the compared methods remains the same, a result may hold only under some…
arXiv:2609.27845v1 Announce Type: new Abstract: The landscape of search has changed drastically with how people look for information online. Traditional search engines are being replaced by Generative Search Engines…
arXiv:2609.23354v3 Announce Type: replace Abstract: Traditional Web search follows a human-facing paradigm in which users inspect ranked documents and synthesize information themselves. In AI Search, retrieved documents…
arXiv:2609.28383v1 Announce Type: new Abstract: Watch time is the primary engagement signal in short video feeds, and its prediction directly affects ranking and exposure. Existing methods improve watch time prediction…
arXiv:2609.26977v1 Announce Type: new Abstract: Offline top-k evaluation often ranks one held-out relevant item together with sampled negatives. When several candidates receive exactly the same score, the tie-breaking…
arXiv:2609.27844v1 Announce Type: cross Abstract: Claim denial management costs U.S. healthcare approximately $260 billion annually in administrative overhead. Large Language Models (LLMs) and Retrieval-Augmented…
arXiv:2511.04541v2 Announce Type: replace Abstract: Slate recommender systems (RecSys) present users with ordered sets of interacting items (e.g., playlists). We investigate whether large language models (LLMs) can…
arXiv:2609.28108v1 Announce Type: new Abstract: While hypergraph-based Retrieval-Augmented Generation (RAG) effectively captures higher-order multi-entity correlations, existing paradigms treat extracted hyperedges as…
34 items available
