• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 123 matches

• 2024
• 
  Zhiyu Chen, Jason Ingyu Choi, Besnik Fetahu, Shervin Malmasi:
  Identifying High Consideration E-Commerce Search Queries. EMNLP (Industry Track) 2024: 563-572
• 
  Somnath Banerjee, Amruit Sahoo, Sayan Layek, Avik Dutta, Rima Hazra, Animesh Mukherjee:
  Context Matters: Pushing the Boundaries of Open-Ended Answer Generation with Graph-Structured Knowledge Context. EMNLP (Industry Track) 2024: 290-302
• 
  Lei Shu, Nevan Wichers, Liangchen Luo, Yun Zhu, Yinxiao Liu, Jindong Chen, Lei Meng:
  Fusion-Eval: Integrating Assistant Evaluators with LLMs. EMNLP (Industry Track) 2024: 225-238
• 
  Ibrahim Abdelaziz, Kinjal Basu, Mayank Agarwal, Sadhana Kumaravel, Matthew Stallone, Rameswar Panda, Yara Rizk, G. P. Shrivatsa Bhargav, Maxwell Crouse, Chulaka Gunasekara, Shajith Ikbal, Sachindra Joshi, Hima Karanam, Vineet Kumar, Asim Munawar, Sumit Neelam, Dinesh Raghu, Udit Sharma, Adriana Meza Soria, Dheeraj Sreedhar, Praveen Venkateswaran, Merve Unuvar, David Cox, Salim Roukos, Luis A. Lastras, Pavan Kapanipathi:
  Granite-Function Calling Model: Introducing Function Calling Abilities via Multi-task Learning of Granular Tasks. EMNLP (Industry Track) 2024: 1131-1139
• 
  Divyansh Agarwal, Alexander R. Fabbri, Ben Risher, Philippe Laban, Shafiq Joty, Chien-Sheng Wu:
  Prompt Leakage effect and mitigation strategies for multi-turn LLM Applications. EMNLP (Industry Track) 2024: 1255-1275
• 
  Satoshi Akasaki, Manabu Sassano:
  Detecting Ambiguous Utterances in an Intelligent Assistant. EMNLP (Industry Track) 2024: 386-394
• 
  Arjun R. Akula, Garima Pruthi, Inderjit S. Dhillon, Pradyumna Narayana, Sugato Basu, Varun Jampani:
  PRISM: A New Lens for Improved Color Understanding. EMNLP (Industry Track) 2024: 1659-1670
• 
  Peter Anderson, Mano Vikash Janardhanan, Jason He, Wei Cheng, Charlie Flanagan:
  Greenback Bears and Fiscal Hawks: Finance is a Jungle and Text Embeddings Must Adapt. EMNLP (Industry Track) 2024: 362-370
• 
  Gaurav Arora, Shreya Jain, Srujana Merugu:
  Intent Detection in the Age of LLMs. EMNLP (Industry Track) 2024: 1559-1570
• 
  Anab Maulana Barik, Wynne Hsu, Mong-Li Lee:
  Time Matters: An End-to-End Solution for Temporal Claim Verification. EMNLP (Industry Track) 2024: 657-664
• 
  Bishwaranjan Bhattacharjee, Aashka Trivedi, Masayasu Muraoka, Muthukumaran Ramasubramanian, Takuma Udagawa, Iksha Gurung, Nishan Pantha, Rong Zhang, Bharath Dandala, Rahul Ramachandran, Manil Maskey, Kaylin M. Bugbee, Michael Little, Elizabeth Fancher, Irina Gerasimov, Armin Mehrabian, Lauren M. Sanders, Sylvain Costes, Sergi Blanco-Cuaresma, Kelly E. Lockhart, Thomas Allen, Félix Grèzes, Megan Ansdell, Alberto Accomazzi, Yousef El-Kurdi, Davis Wertheimer, Birgit Pfitzmann, Cesar Berrospi Ramis, Michele Dolfi, Rafael Teixeira de Lima, Panagiotis Vagenas, S. Karthik Mukkavilli, Peter W. J. Staar, Sanaz Vahidinia, Ryan McGranaghan, Tsengdar J. Lee:
  INDUS: Effective and Efficient Language Models for Scientific Applications. EMNLP (Industry Track) 2024: 98-112
• 
  Nadjet Bouayad-Agha, Ignasi Gómez-Sebastià, Alba Padró-Arocas, Enric Roura, David Castelló, Rocío Tovar:
  Assisting Breastfeeding and Maternity Experts in Responding to User Queries with an AI-in-the-loop Approach. EMNLP (Industry Track) 2024: 829-841
• 
  Benjamin L. Bullough, Harrison Lundberg, Chen Hu, Weihang Xiao:
  Predicting Entity Salience in Extremely Short Documents. EMNLP (Industry Track) 2024: 50-64
• 
  Lucas Cecchi, Petr Babkin:
  ReportGPT: Human-in-the-loop Verifiable Table-to-Text Generation. EMNLP (Industry Track) 2024: 529-537
• 
  Robin Chan, Katsiaryna Mirylenka, Thomas Gschwind, Christoph Miksovic, Paolo Scotton, Enrico Toniato, Abdel Labbi:
  Adapting LLMs for Structured Natural Language API Integration. EMNLP (Industry Track) 2024: 991-1000
• 
  Ernie Chang, Matteo Paltenghi, Yang Li, Pin-Jie Lin, Changsheng Zhao, Patrick Huber, Zechun Liu, Rastislav Rabatin, Yangyang Shi, Vikas Chandra:
  Scaling Parameter-Constrained Language Models with Quality Data. EMNLP (Industry Track) 2024: 80-97
• 
  Yuemin Chen, Feifan Wu, Jingwei Wang, Hao Qian, Ziqi Liu, Zhiqiang Zhang, Jun Zhou, Meng Wang:
  Knowledge-augmented Financial Market Analysis and Report Generation. EMNLP (Industry Track) 2024: 1207-1217
• 
  Jiangning Chen, Ziyun Zhang, Qianli Hu:
  Optimizing Entity Resolution in Voice Interfaces: An ASR-Aware Entity Reference Expansion Approach. EMNLP (Industry Track) 2024: 1-7
• 
  Kang Chen, Qing Zhang, Chengbao Lian, Yixin Ji, Xuwei Liu, Shuguang Han, Guoqiang Wu, Fei Huang, Jufeng Chen:
  IPL: Leveraging Multimodal Large Language Models for Intelligent Product Listing. EMNLP (Industry Track) 2024: 697-711
• 
  Zhi-Qi Cheng, Yifei Dong, Aike Shi, Wei Liu, Yuzhi Hu, Jason O'Connor, Alexander G. Hauptmann, Kate Whitefoot:
  SHIELD: LLM-Driven Schema Induction for Predictive Analytics in EV Battery Supply Chain Disruptions. EMNLP (Industry Track) 2024: 303-333
• 
  Kellen Cheng, Anna Lisa Gentile, Pengyuan Li, Chad DeLuca, Guang-Jie Ren:
  Don't be my Doctor! Recognizing Healthcare Advice in Large Language Models. EMNLP (Industry Track) 2024: 970-980
• 
  Nayoung Choi, Youngjune Lee, Gyu-Hwung Cho, Haeyu Jeong, Jungmin Kong, Saehun Kim, Keunchan Park, Sarah Cho, Inchang Jeong, Gyohee Nam, Sunghoon Han, Wonil Yang, Jaeho Choi:
  RRADistill: Distilling LLMs' Passage Ranking Ability for Long-Tail Queries Document Re-Ranking on a Search Engine. EMNLP (Industry Track) 2024: 627-641
• 
  Bonggeun Choi, JeongJae Park, Yoonsung Kim, Jaehyun Park, Youngjoong Ko:
  RAC: Retrieval-augmented Conversation Dataset for Open-domain Question Answering in Conversational Settings. EMNLP (Industry Track) 2024: 1477-1488
• 
  Tarang Chugh, Deepak Zambre:
  ASTRA: Automatic Schema Matching using Machine Translation. EMNLP (Industry Track) 2024: 1237-1244
• 
  Wendi Cui, Zhuohang Li, Damien Lopez, Kamalika Das, Bradley A. Malin, Kumar Sricharan, Jiaxin Zhang:
  Divide-Conquer-Reasoning for Consistency Evaluation and Automatic Improvement of Large Language Models. EMNLP (Industry Track) 2024: 334-361
• 
  Omkar Dige, Diljot Arneja, Tsz Fung Yau, Qixuan Zhang, Mohammad Bolandraftar, Xiaodan Zhu, Faiza Khan Khattak:
  Can Machine Unlearning Reduce Social Bias in Language Models? EMNLP (Industry Track) 2024: 954-969
• 
  Dante Everaert, Rohit Patki, Tianqi Zheng, Christopher Potts:
  AmazonQAC: A Large-Scale, Naturalistic Query Autocomplete Dataset. EMNLP (Industry Track) 2024: 1046-1055
• 
  James Fletcher, Nicholas Dehnen, Seyed Nima Tayarani Bathaie, Aijun An, Heidar Davoudi, Ron DiCarlantonio, Gary Farmaner:
  Generating Vehicular Icon Descriptions and Indications Using Large Vision-Language Models. EMNLP (Industry Track) 2024: 1107-1120
• 
  Charles Goddard, Shamane Siriwardhana, Malikeh Ehghaghi, Luke Meyers, Vladimir Karpukhin, Brian Benedict, Mark McQuade, Jacob Solawetz:
  Arcee's MergeKit: A Toolkit for Merging Large Language Models. EMNLP (Industry Track) 2024: 477-485
• 
  Ruihao Gong, Yang Yong, Shiqiao Gu, Yushi Huang, Chengtao Lv, Yunchen Zhang, Dacheng Tao, Xianglong Liu:
  LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit. EMNLP (Industry Track) 2024: 132-152

skipping 93 more matches