Daily edition · Information Retrieval
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49 articles · 2 sources · 49 papers ·
Top topics: Information Retrieval · AI · AI Research
arXiv:2609.00618v2 Announce Type: replace Abstract: We investigate the role of conversational context modeling in user preference tracking for Conversational Recommendation Systems (CRSs). In this regard, we propose…
arXiv:2609.02486v1 Announce Type: new Abstract: Document Visual Question Answering (DocVQA) often leverages Retrieval-Augmented Generation (RAG), where late-interaction encoders are commonly used to identify document…
arXiv:2609.01655v1 Announce Type: new Abstract: Unified recommendation models aim to jointly model non-sequential multi-field features and sequential user behaviors, but existing interaction-centric designs mainly focus…
arXiv:2609.01621v1 Announce Type: new Abstract: Artificial intelligence (AI) increasingly treats scientific literature as a data source for building databases, training predictive models, and guiding discovery. Yet…
arXiv:2609.02188v1 Announce Type: new Abstract: Reasoning-intensive retrieval addresses queries whose relevance cannot be identified by surface-level matching, thereby requiring multi-step reasoning. Because relevant…
arXiv:2609.01652v1 Announce Type: new Abstract: Recommender systems in two-sided matching platforms are commonly optimized for immediate engagement signals such as click-through rate, reply rate, or the total number of…
arXiv:2609.02143v1 Announce Type: cross Abstract: Most vector databases rely on graph-based indexes, notably HNSW and Vamana, for approximate nearest neighbor search. With embedding models widely adopted, the datasets…
arXiv:2609.01613v1 Announce Type: new Abstract: Universal multimodal retrieval (UMR) increasingly adopts multimodal large language models (MLLMs) as unified embedding backbones, but their strong retrieval performance…
arXiv:2606.04547v3 Announce Type: replace Abstract: Personalizing large language models requires adapting model behavior to individual users while preserving robustness and deployment-scale efficiency. Existing…
arXiv:2609.01631v1 Announce Type: cross Abstract: Team recommendation aims to select an optimal subset of experts who can form an almost surely successful collaborative team for a given set of required skills.…
arXiv:2609.02379v1 Announce Type: cross Abstract: While existing work on LLM authorship attribution (AA) has made progress, available benchmarks remain limited, often focusing on English, controlled settings, or…
arXiv:2609.01627v1 Announce Type: new Abstract: Explanations play a crucial role in creating trustworthy recommender systems (RS), yet choosing a good explanation method presents challenges. Many explanation methods…
arXiv:2608.29652v2 Announce Type: replace Abstract: Generative Retrieval (GR) is promising for e-commerce search, yet existing methods struggle to maintain query-intent consistency throughout the training pipeline.…
arXiv:2609.01657v1 Announce Type: new Abstract: Multimodal models often build on architectures designed for generative vision-language modeling, typically combining separately pretrained vision encoders with causal…
arXiv:2609.02152v1 Announce Type: new Abstract: Multimodal Recommender Systems (MRSs) typically rely on a flawed "modality harmony" assumption, presuming that multimodal features are inherently beneficial and strictly…
arXiv:2609.02324v1 Announce Type: new Abstract: Large language models have enabled natural language interfaces for structured databases, but generated queries may still contain syntactic errors, violate database…
arXiv:2609.01645v1 Announce Type: new Abstract: Retrieval-augmented question answering is increasingly used to help people navigate public-benefits eligibility, yet the documents these systems retrieve from are written…
arXiv:2608.25489v2 Announce Type: replace-cross Abstract: Graph retrieval-augmented generation places retrieved subgraphs into the model's context window at query time, paying a recurring token cost and exposing source…
arXiv:2609.02129v1 Announce Type: cross Abstract: Data-centric agents repeatedly perform a discovery step before planning or execution: identifying the data objects relevant to a task. Yet successful discovery outcomes…
arXiv:2609.01820v1 Announce Type: new Abstract: Dynamic maximum inner-product search (MIPS) returns the $K$ stored vectors with the largest dot products with a query while allowing the dataset to change through…
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