Topic - Edition
Gaurish Technologies is a technology and digital solutions company helping businesses build a stronger online presence, streamline operations, and achieve sustainable growth. Through it, the company offers services…
arXiv:2508.19449v3 Announce Type: replace-cross Abstract: Automated crash reporting systems generate large volumes of duplicate reports, overwhelming issue-tracking systems and increasing developer workload. Traditional…
arXiv:2610.07760v2 Announce Type: replace Abstract: Retrieval-augmented generation systems can route difficult queries to deeper context, but batch deployments must allocate a shared token budget across calls whose…
arXiv:2610.30128v1 Announce Type: new Abstract: Existing sequential recommenders usually allocate a fixed computational budget to every item in a user's interaction history, regardless of the item's contribution to the…
arXiv:2607.21951v4 Announce Type: replace Abstract: This paper investigates the adversarial manipulation of the ranked recommendations produced by web-augmented large language models (LLMs). When an LLM answers a…
arXiv:2610.29520v1 Announce Type: new Abstract: Retrieval-based in-context learning (ICL) enables large language models (LLMs) to predict tabular labels from similar examples, but it remains unclear whether LLM…
arXiv:2610.28656v1 Announce Type: cross Abstract: Future-work statements offer a record of the questions researchers choose to leave open. Using them to describe a field, however, requires separating thematic change…
arXiv:2610.29812v1 Announce Type: cross Abstract: Literature-searching language agents are becoming a standard component of scientific assistants for the life sciences, yet there is little controlled evidence on which…
arXiv:2610.28642v1 Announce Type: new Abstract: Generative recommendation over discrete Semantic IDs has become a powerful paradigm for item retrieval. Real-world systems, however, frequently require real-time…
arXiv:2511.14130v3 Announce Type: replace-cross Abstract: Deploying LLMs for financial information retrieval demands accuracy, cost efficiency, and reproducibility, yet most approaches require expensive fine-tuning.…
arXiv:2605.18767v2 Announce Type: replace Abstract: Multi-hop question answering requires aggregating information from multiple documents, a critical capability for knowledge-intensive applications. A fundamental…
arXiv:2610.29138v1 Announce Type: new Abstract: Multimodal click-through rate (CTR) prediction is central to search systems, where ranking depends on item content, query relevance, and user preference. Existing…
arXiv:2610.28636v1 Announce Type: new Abstract: We present ResearchHub, an interactive system for personalized literature discovery over biomedical preprints. Given a researcher profile or a free-form query, ResearchHub…
arXiv:2610.28641v1 Announce Type: new Abstract: Domain-specific tabular and transaction foundation models are increasingly proposed as drop-in representation learners for financial applications, but their value relative…
arXiv:2610.29298v1 Announce Type: new Abstract: Generative recommenders replace the retrieve-then-rank cascade with a single model: beam search over semantic item identifiers performs retrieval, and the same likelihood…
arXiv:2610.28929v1 Announce Type: cross Abstract: This technical report documents the design and implementation of Scriptorium, a digital library search interface designed to support multi-human, multi-AI collaboration:…
arXiv:2610.28638v1 Announce Type: new Abstract: As urban residents demand higher-quality instant delivery services, demand forecasting, estimated time of arrival prediction, and next-stop prediction have become critical…
arXiv:2610.28922v1 Announce Type: new Abstract: Generative LLMs can label spans without task-specific training, but their output is not tied to positions in the input: a returned span may be absent from the input or…
arXiv:2610.29464v1 Announce Type: new Abstract: Dense retrieval has become a fundamental paradigm for modern information retrieval, supporting efficient semantic search across a wide range of applications. Its…
arXiv:2610.29556v1 Announce Type: cross Abstract: One of the enduring challenges in online platforms is recommendation. Both communities and advertisers face difficulties in analyzing complex user behavior, identifying…
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