Daily edition · Information Retrieval
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25 articles · 2 sources · 25 papers ·
Top topics: AI Research · AI · Information Retrieval
arXiv:2504.06188v3 Announce Type: replace-cross Abstract: AI agents can extend their capabilities at inference time by loading reusable skills into context, yet equipping an agent with too many skills, particularly…
arXiv:2607.02387v2 Announce Type: replace Abstract: NASA and its data centers hold thousands of geoscience datasets and tools like Worldview, Giovanni, the Science Discovery Engine, and Harmony. Finding the right one is…
arXiv:2609.31062v1 Announce Type: cross Abstract: Patient-facing AI assistants promise valuable support to patients, but incoming queries can pose medical risks. To create guardrails, we work with oncologists to define…
arXiv:2609.30547v1 Announce Type: cross Abstract: Audience sizing is a critical component of digital marketing. It enables precise resource allocation, campaign planning, and performance optimization. Traditional…
arXiv:2609.30711v1 Announce Type: new Abstract: Sequential recommendation optimizes which items to rank, while each displayed slate also shapes subsequent feedback and user state. We study how a trained ranker can…
arXiv:2609.30611v1 Announce Type: cross Abstract: On Jan. 30, 2026, the U.S. Department of Justice released a mixed-media collection concerning Jeffrey Epstein, including about three million pages of PDFs. We describe…
arXiv:2609.30576v1 Announce Type: cross Abstract: Large-scale recommenders increasingly adopt the sequential generative recipe behind large language models, bringing the Transformer into recommendation along with design…
arXiv:2609.30601v1 Announce Type: new Abstract: Modern industrial recommender systems must optimize across competing objectives, balancing semantic relevance with business metrics such as engagement and revenue. While…
arXiv:2609.31253v1 Announce Type: new Abstract: Sequential recommenders typically rely on learnable positional embeddings to encode the order of user interactions. In this work, we ask whether this ordinal signal can be…
arXiv:2507.17654v4 Announce Type: replace-cross Abstract: Function-correcting codes are a coding framework designed to minimize redundancy while ensuring that specific functions or computations of encoded data can be…
arXiv:2609.30656v1 Announce Type: new Abstract: Large-scale recommendation models pose distinct, under-explored profiling challenges. Most recommendation model architectures are structurally heterogeneous, intermixing…
arXiv:2609.30717v1 Announce Type: new Abstract: Recent advances in agentic recommender systems are shifting recommender systems from passive filtering engines to instruction-following agents that use external tools to…
arXiv:2609.31164v1 Announce Type: new Abstract: Recommender systems engineer serendipity to foster active exploration and break predictable consumption cycles. The problem with existing offline beyond-accuracy metrics…
arXiv:2609.30297v1 Announce Type: cross Abstract: Conversational recommendation agents are a new paradigm for content discovery, enabling users to express complex intents through natural language (e.g., "recommend…
arXiv:2609.30467v1 Announce Type: cross Abstract: Retrieval-based factuality evaluation, where LLM-generated claims are verified against evidence from authoritative medical corpora, has become the dominant paradigm for…
arXiv:2609.30904v1 Announce Type: new Abstract: Passage reranking plays a crucial role in information retrieval by refining the ordering of candidate passages to better reflect relevance. Existing listwise LLM rerankers…
arXiv:2609.09556v3 Announce Type: replace-cross Abstract: Neural networks can leverage feature superposition to encode more concepts than dimensions, but cross-feature interference constrains the linear accessibility of…
arXiv:2609.30295v1 Announce Type: cross Abstract: Identifying an unfamiliar sign is difficult when a learner remembers its movement but does not know its meaning or formal feature codes. SignTrace addresses this…
arXiv:2609.31498v1 Announce Type: new Abstract: Search is one of the most important features in e-commerce, directly driving customer engagement and business growth. A good product search system must show both relevant…
arXiv:2609.31045v1 Announce Type: new Abstract: Conversational agents, generative recommenders, and personalized advertising all rest on one capability: understanding each user from raw behavior. Prevailing industrial…
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