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According to the Probability Ranking Principle (PRP), ranking documents in decreasing order of their probability of relevance leads to an optimal document ranking for ad-hoc retrieval.
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Introducing MANtIS: a novel Multi-Domain Information Seeking Dialogues Dataset
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Some simple effective approximations to the 2-poisson model for probabilistic weighted retrieval
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Iart: Intent-aware response ranking with transformers in information-seeking conversation systems
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Speaker-aware bert for multi-turn response selection in retrieval-based chatbots
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Calibrating healthcare ai: Towards reliable and interpretable deep predictive models
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In search of lost domain generalization
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Mean-variance analysis: A new document ranking theory in information retrieval
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Portfolio theory of information retrieval
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Risky business: modeling and exploiting uncertainty in information retrieval
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Back to the roots: mean-variance analysis of relevance estimations
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Calibrating predictive model estimates to support personalized medicine
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Bayesian learning for neural networks , volume 118
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Asking clarifying questions in open-domain information-seeking conversations
Mohammad Aliannejadi, Hamed Zamani, Fabio Crestani, and W Bruce Croft. 2019 · 2019
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BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
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Utterance-to-utterance interactive matching network for multi-turn response selection in retrieval-based chatbots
Jia-Chen Gu, Zhen-Hua Ling, and Quan Liu. 2019 · 2019
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A deep look into neural ranking models for information retrieval
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The eighth dialog system technology challenge
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Diederik P Kingma and Jimmy Ba. 2014 · 2014
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Weight uncertainty in neural networks
Charles Blundell, Julien Cornebise, Koray Kavukcuoglu, and Daan Wierstra. 2015 · 2015
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Obtaining well calibrated probabilities using bayesian binning
Mahdi Pakdaman Naeini, Gregory F Cooper, and Milos Hauskrecht. 2015 · 2015
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Dropout as a bayesian approximation
Y Gal and Z Ghahramani. 2016 · 2016
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Uncertainty in deep learning
Yarin Gal. 2016 · 2016
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On calibration of modern neural networks
Chuan Guo, Geoff Pleiss, Yu Sun, and Kilian Q Weinberger. 2017 · 2017
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Billion-scale similarity search with gpus
Jeff Johnson, Matthijs Douze, and Hervé Jégou. 2017 · 2017
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A large-scale corpus for conversation disentanglement
Jonathan K. Kummerfeld, Sai R. Gouravajhala, Joseph J. Peper, Vignesh Athreya, Chulaka Gunasekara, Jatin Ganhotra, Siva Sankalp Patel, Lazaros C Polymenakos, and Walter Lasecki. 2019 · 2019
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A simple baseline for bayesian uncertainty in deep learning
Wesley J Maddox, Pavel Izmailov, Timur Garipov, Dmitry P Vetrov, and Andrew Gordon Wilson. 2019 · 2019
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Can you trust your model’s uncertainty? evaluating predictive uncertainty under dataset shift
Yaniv Ovadia, Emily Fertig, Jie Ren, Zachary Nado, David Sculley, Sebastian Nowozin, Joshua Dillon, Balaji Lakshminarayanan, and Jasper Snoek. 2019 · 2019
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
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Multi-representation fusion network for multi-turn response selection in retrieval-based chatbots
Chongyang Tao, Wei Wu, Can Xu, Wenpeng Hu, Dongyan Zhao, and Rui Yan. 2019 · 2019
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Comparison of transfer-learning approaches for response selection in multi-turn conversations
Jesse Vig and Kalai Ramea. 2019 · 2019
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Simple applications of bert for ad hoc document retrieval
Wei Yang, Haotian Zhang, and Jimmy Lin. 2019 · 2019
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Multi-hop selector network for multi-turn response selection in retrieval-based chatbots
Chunyuan Yuan, Wei Zhou, Mingming Li, Shangwen Lv, Fuqing Zhu, Jizhong Han, and Songlin Hu. 2019 · 2019
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Evaluating stochastic rankings with expected exposure
Fernando Diaz, Bhaskar Mitra, Michael D. Ekstrand, Asia J. Biega, and Ben Carterette. 2020 · 2020
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“none of the above”: Measure uncertainty in dialog response retrieval
Yulan Feng, Shikib Mehri, Maxine Eskenazi, and Tiancheng Zhao. 2020 · 2020
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Query reformulation using query history for passage retrieval in conversational search
Sheng-Chieh Lin, Jheng-Hong Yang, Rodrigo Nogueira, Ming-Feng Tsai, Chuan-Ju Wang, and Jimmy Lin. 2020 · 2020
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Improving contextual language models for response retrieval in multi-turn conversation
Junyu Lu, Xiancong Ren, Yazhou Ren, Ao Liu, and Zenglin Xu. 2020 · 2020
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Curriculum learning strategies for ir
Gustavo Penha and Claudia Hauff. 2020 · 2020
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