SpeechLLMs for Large-scale Contextualized Zero-shot Slot Filling
机构 * Uniphore
Comments 13 pages, EMNLP 2025
期刊&会议
Conference on Empirical Methods in Natural Language Processing · 会议 · Natural Language Processing
机构 * Uniphore
Comments 13 pages, EMNLP 2025
机构 * Department of Informatics(信息学系)
Comments 9 pages, 6 figures, 3 tables, EMNLP 2025 Demo paper
机构 * Indian Institute of Technology Delhi(印度理工学院德里分校) ; MongoDB, Inc.(MongoDB公司)
Comments EMNLP Main Long Paper 2025
机构 * University of California Irvine(加州大学尔湾分校) ; Capital One
Comments Accepted at the TSAR Workshop @ EMNLP 2025
机构 * Shanghai Jiao Tong University(上海交通大学) ; Fudan University(复旦大学)
Comments Accepted to EMNLP 2025 (Main Conference)
机构 * NYU Shanghai(纽约大学上海校区) ; National University of Singapore(新加坡国立大学) ; Yale University(耶鲁大学) ; Center for Data Science, New York University(纽约大学数据科学中心)
Comments EMNLP 2025 Main
机构 * UC Santa Barbara(加州大学圣芭芭拉分校) ; Amazon Stores Foundational AI(亚马逊商店基础人工智能) ; UC San Diego(加州大学圣地亚哥分校)
Comments EMNLP 2025 Findings
Comments Accepted for publication at EMNLP 2025 Findings. Code and data publicly available at https://github.com/J1mL1/DocMMIR
Comments Appeared in EMNLP 2025 main conference. To better understand prompt injection attacks, see https://people.duke.edu/~zg70/code/PromptInjection.pdf
Journal ref The 2025 Conference on Empirical Methods in Natural Language Processing (EMNLP 2025)
Comments Accepted to EMNLP 2025