cs.IR · 2026-06-17 · No. 26

Information Retrieval, 2026-06-17.

3 new papers in cs.IR. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

3 entries
  1. 01

    IUU+DB: Tracking Illegal, Unreported, and Unregulated Fishing, Seafood Fraud, and Labor Abuse through LLM-driven Information Extraction

    Henry Bodwell, Hong Yang, John C. Simeone, Kelvin Gorospe, Bella Sullivan, Lana Huang, Jessica Gephart, Sandy...

    cs.IR · cs.AI · cs.CY

    Illegal, unreported, and unregulated fishing (IUU) traditionally refers to fishing activities that violate applicable laws or occur in areas that lack applicable laws. We propose the term IUU+ to capture a broader suite of fisheries sector environmental and associated supply chain trade-related crimes and behaviors. Although IUU+ activity is widely recognized as a serious threat to marine ecosystems, markets, and livelihoods, a quantitative...

    arxiv.org/abs/2606.18181 · PDF

  2. 02

    Non-negative Elastic Net Decoding for Information Retrieval

    Koki Okajima, Yasutoshi Ida, Tsukasa Yoshida, Yasuaki Nakamura

    cs.IR · cs.AI · cs.CL

    Dense retrieval has become the dominant paradigm in information retrieval, in which each document is scored against a query by the inner product of their vector embeddings, and the top-$k$ documents by score are retrieved for this query. However, since each document's score depends solely on the embedding of the query and itself, the retrieval process is oblivious to the content of the entire corpus. Therefore, dense retrieval cannot avoid...

    arxiv.org/abs/2606.17910 · PDF

  3. 03

    Temporal Preference Optimization for Unsupervised Retrieval

    HyunJin Kim, Jaejun Shim, Young Jin Kim, JinYeong Bak

    cs.IR · cs.AI

    Unsupervised dense retrievers offer scalability by learning semantic similarity from unlabeled documents via contrastive learning, but they struggle to capture the temporal relevance, retrieving semantically related but temporally misaligned documents-an important aspect when a document collection spans multiple time periods (e.g., retrieving documents from 2018-2025 for "Who is the president in 2019?" introduces temporal ambiguity). Existing...

    arxiv.org/abs/2606.17664 · PDF

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