AgentSelect: Benchmark for Narrative Query-to-Agent Recommendation
arXiv:2603.03761v2 Announce Type: replace-cross Abstract: LLM agents are rapidly becoming the practical interface for task automation, yet the ecosystem lacks a…
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arXiv:2603.03761v2 Announce Type: replace-cross Abstract: LLM agents are rapidly becoming the practical interface for task automation, yet the ecosystem lacks a…
arXiv:2610.37973v2 Announce Type: replace Abstract: LLM-based generative recommendation reads long, text-rich interaction histories but generates only short sem…
arXiv:2606.28780v2 Announce Type: replace Abstract: Multimodal large language models (MLLMs) are widely applied to visual document understanding. However, compr…
arXiv:2606.28351v3 Announce Type: replace Abstract: Recent Hypergraph-based retrieval-augmented generation (HyperRAG) methods use hyper edges to connect multipl…
arXiv:2605.21987v2 Announce Type: replace Abstract: Recent conversational recommender systems have begun to unify recommendation and response generation within …
arXiv:2605.12887v3 Announce Type: replace Abstract: Web-enabled LLM agents are changing how online information influences search outcomes. Existing Generative E…
arXiv:2603.02999v4 Announce Type: replace Abstract: The end-to-end generative paradigm is revolutionizing advertising recommendation systems, driving a shift fr…
arXiv:2512.12084v3 Announce Type: replace Abstract: Existing Text-to-SQL benchmarks primarily focus on single-table queries or limited joins in general-purpose …
arXiv:2611.08325v1 Announce Type: cross Abstract: Retrieved web text can carry instructions aimed at the language model, or synthetic pages written to mislead. …
arXiv:2611.07971v1 Announce Type: cross Abstract: Some Python workflows need transactional reads and writes over documents, traversals over a graph, and similar…
arXiv:2611.07899v1 Announce Type: cross Abstract: Conversational agents can retrieve information directly or delegate retrieval to a subagent. This design choic…
arXiv:2611.07859v1 Announce Type: cross Abstract: Deep research agents answer complex questions through repeated search. They rely on a harness that runs their …
arXiv:2611.07486v1 Announce Type: cross Abstract: Mapping behavioral intelligence in malware analysis reports to ATT&CK techniques supports threat analysis and …
arXiv:2611.07174v1 Announce Type: cross Abstract: MapHub, the MIDAS arXiv Preprint Hub, assesses each day's new arXiv submissions for every participant in a res…
arXiv:2611.08228v1 Announce Type: new Abstract: Information Retrieval (IR) is much more than ad hoc web search: a large portion of the information seeking activ…
arXiv:2611.08014v1 Announce Type: new Abstract: Dense similarity supplies reusable corpus representations, while probabilistic relevance decisions offer query-d…
arXiv:2611.07631v1 Announce Type: new Abstract: Long-horizon LLM agents require memory systems that preserve useful information across sessions and retrieve it …
arXiv:2611.07591v1 Announce Type: new Abstract: Re-ranking aims to present users with an ordered list that maximizes sequence-level utility. Industrial deployme…
arXiv:2611.07588v1 Announce Type: new Abstract: Collaborative-filtering (CF) scores provide graded, personalized rewards for training large language model (LLM)…
arXiv:2611.07523v1 Announce Type: new Abstract: Semantic information can enrich the identifiers and structured fields used by recommender systems. Semantic toke…