Topic - Edition
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:2610.08232v1 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:2610.08200v1 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:2610.07023v1 Announce Type: cross Abstract: Large Language Models (LLMs) have achieved remarkable capabilities but remain vulnerable to jailbreak attacks that elicit harmful or unsafe outputs. Existing safety…
arXiv:2610.07402v1 Announce Type: new Abstract: Semantic ID-based generative recommendation represents each item as a sequence of discrete tokens, enabling structured modeling of item semantics. A critical challenge is…
arXiv:2610.07886v1 Announce Type: cross Abstract: Dietary nutrition planning plays an important role in chronic disease management and maintaining a healthy body. In applications, it must simultaneously satisfy…
arXiv:2609.34951v3 Announce Type: replace-cross Abstract: In 2023, AI models answered from training data and hallucinated when it ran out, and businesses were told to seed that knowledge. Models' training knowledge has…
arXiv:2610.07437v1 Announce Type: new Abstract: For retrieving prior cases in Indian legal judgments, the problem involves distinguishing relevant legal facts from mere lexical similarities because a prior case that…
arXiv:2610.02387v2 Announce Type: replace-cross Abstract: In every fast nearest-neighbor index, recall is measured, never predicted: each operating point is tuned by serving it against ground truth. SOLO is an index…
arXiv:2610.08077v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) turns agent experience into learning signals primarily through scalar outcome rewards after interaction. For…
arXiv:2610.07760v1 Announce Type: new Abstract: Retrieval-augmented generation systems can route difficult queries to deeper context, but batch deployments must allocate a shared token budget across calls whose costs…
arXiv:2610.07384v1 Announce Type: cross Abstract: Individual animal re-identification from camera-trap imagery is an instance retrieval problem central to non-invasive wildlife monitoring: a query image must retrieve…
arXiv:2610.08229v1 Announce Type: cross Abstract: Contextual priors improve neural-to-language decoding by reshaping candidate scores. However, confidence is read from the same reshaped scores, so the errors a prior…
arXiv:2610.07132v1 Announce Type: cross Abstract: Croissant has emerged as a standard for machine-readable dataset metadata, yet populating its fields remains labor-intensive and requires careful reading of accompanying…
arXiv:2610.08452v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) is a widely used approach for grounding large language models (LLMs) in external knowledge. However, configuring a pipeline is an…
arXiv:2610.07105v1 Announce Type: new Abstract: Recommendation recursive self-improvement (Rec-RSI) feeds recommender outputs into subsequent training. Evaluating each round solely through its latest model assumes that…
arXiv:2606.01782v3 Announce Type: replace Abstract: LLM-based re-rankers produce rankings through repeated local comparisons (listwise, pairwise or pointwise), requiring many sequential model calls. We study how…
arXiv:2605.18850v2 Announce Type: replace Abstract: We introduce KadiAssistant, a privacy-by-design AI assistant integrated into the Kadi research data ecosystem, enabling researchers to efficiently access, aggregate,…
arXiv:2610.08136v1 Announce Type: new Abstract: Generative recommenders decode items from a user's interaction history, but offer no way for users to correct a recommendation that misses their current intent. Adding…
arXiv:2610.08245v1 Announce Type: new Abstract: Existing research on user fairness in recommender systems has developed diverse objectives. However, it has paid limited attention to a distinct distributive perspective:…
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