Publications 论文发表
2024
Proceedings of the 2024 Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region · 08 Dec 2024
arXiv preprint arXiv:2412.05579 · 07 Dec 2024
ACM Transactions on Information Systems · 26 Nov 2024
arXiv preprint arXiv:2411.06112 · 09 Nov 2024
Findings of the Association for Computational Linguistics: EMNLP 2024 · 01 Nov 2024
arXiv preprint arXiv:2411.00331 · 01 Nov 2024
Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing · 01 Nov 2024
arXiv preprint arXiv:2410.21801 · 29 Oct 2024
Proceedings of the 32nd ACM International Conference on Multimedia · 28 Oct 2024
Proceedings of the 1st International Workshop on Brain-Computer Interfaces (BCI) for Multimedia Understanding · 28 Oct 2024
Proceedings of the 33rd ACM International Conference on Information and Knowledge Management · 21 Oct 2024
arXiv preprint arXiv:2410.15393 · 20 Oct 2024
IEEE Transactions on Industrial Informatics · 17 Oct 2024
arXiv preprint arXiv:2410.12265 · 16 Oct 2024
arXiv preprint arXiv:2410.07745 · 10 Oct 2024
Proceedings of the 18th ACM Conference on Recommender Systems · 08 Oct 2024
Proceedings of the 18th ACM Conference on Recommender Systems · 08 Oct 2024
arXiv preprint arXiv:2410.03742 · 01 Oct 2024
arXiv preprint arXiv:2409.20288 · 30 Sep 2024
Journal of the Association for Information Science and Technology · 01 Sep 2024
Language reconstruction from non-invasive brain recordings has been a long-standing challenge. Existing research has addressed this challenge with a classification setup, where a set of language candidates are pre-constructed and then matched with the representation decoded from brain recordings. Here, we propose a new method that addresses language reconstruction through auto-regressive generation, which directly uses the representation decoded from functional magnetic resonance imaging (fMRI) as the input for a large language model (LLM), removing the reliance on the accuracy of pre-constructed candidates. While an LLM can already generate high-quality content, our approach produces results more closely aligned with the visual or auditory language stimuli in response to which brain recordings are sampled, especially for content deemed “surprising” for the LLM. Furthermore, we show that the proposed approach can be used in an auto-regressive manner to reconstruct a 10-minute-long stimulus, which outperforms previous methods with a classification setup. Our findings demonstrate the effectiveness of employing brain language interfaces in a generative setup and delineate a promising path to investigating language formation in the human brain. · 14 Aug 2024
Proceedings of the 2024 ACM SIGIR International Conference on Theory of Information Retrieval · 02 Aug 2024
arXiv preprint arXiv:2407.14192 · 19 Jul 2024
arXiv preprint arXiv:2407.09417 · 12 Jul 2024
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval · 10 Jul 2024
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval · 10 Jul 2024
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval · 10 Jul 2024
Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval · 10 Jul 2024
arXiv preprint arXiv:2407.00247 · 28 Jun 2024
arXiv preprint arXiv:2406.15313 · 21 Jun 2024
arXiv preprint arXiv:2406.07151 · 11 Jun 2024
arXiv preprint arXiv:2405.20718 · 31 May 2024
arXiv preprint arXiv:2405.18058 · 28 May 2024
arXiv preprint arXiv:2405.11272 · 18 May 2024
arXiv preprint arXiv:2404.15753 · 24 Apr 2024
arXiv preprint arXiv:2404.13940 · 22 Apr 2024
arXiv preprint arXiv:2404.08301 · 12 Apr 2024
arXiv preprint arXiv:2404.03707 · 04 Apr 2024
arXiv preprint arXiv:2404.00947 · 01 Apr 2024
arXiv preprint arXiv:2404.01008 · 01 Apr 2024
arXiv preprint arXiv:2403.20296 · 29 Mar 2024
arXiv preprint arXiv:2403.18435 · 27 Mar 2024
arXiv preprint arXiv:2403.18365 · 27 Mar 2024
arXiv preprint arXiv:2403.18684 · 27 Mar 2024
arXiv preprint arXiv:2403.18317 · 27 Mar 2024
arXiv preprint arXiv:2403.18325 · 27 Mar 2024
arXiv preprint arXiv:2403.18628 · 27 Mar 2024
arXiv preprint arXiv:2403.18348 · 27 Mar 2024
arXiv preprint arXiv:2403.19716 · 27 Mar 2024
arXiv preprint arXiv:2403.13242 · 20 Mar 2024
arXiv preprint arXiv:2403.11152 · 17 Mar 2024
arXiv preprint arXiv:2403.10081 · 15 Mar 2024
Language Generation from Brain Recordings Page 1 1 1 Language Generation from Brain Recordings Ziyi Ye Tsinghua University 2024.3.12 Page 2 2 Introduction • Application of Brain-Computer Interface (BCI) • Instruction decoding [NeuraLink 2021] • Emotion recognition [Edgar 2020] • Sematic decoding • Visual information reconstruction [Takagi 2023] • Language information reconstruction [Makin 2020] Fig: Neuralink's monkey use BCI to play games [Cooney 2021] Fig: Emotion recognition [Edgar 2020] Fig: Speech decoding [Makin 2020] Page 3 3 Background • Existing language BCIs • Pre-defining a series of semantic candidates • Limitations • A limited number of semantic candidates (usually 2-50) • High task dependency Feature extraction Pre-defined semantic candidates Fig:Language BCIs by pre-definition and post-hoc selection/classification sunny rainy apple Page 4 4 Background • Emergence of … · 12 Mar 2024
Unsupervised Real-Time Hallucination Detection based on the Internal States of Large Language Models
arXiv preprint arXiv:2403.06448 · 11 Mar 2024
Proceedings of the 2024 ACM SIGIR Conference on Human Information Interaction and Retrieval · 10 Mar 2024
arXiv preprint arXiv:2403.04184 · 07 Mar 2024
arXiv preprint arXiv:2403.00814 · 25 Feb 2024
arXiv preprint arXiv:2402.15708 · 24 Feb 2024
arXiv preprint arXiv:2402.15235 · 23 Feb 2024
arXiv preprint arXiv:2402.15164 · 23 Feb 2024
arXiv preprint arXiv:2402.14440 · 22 Feb 2024
arXiv preprint arXiv:2402.02816 · 05 Feb 2024
arXiv preprint arXiv:2401.15641 · 28 Jan 2024
Recently, dense retrieval (DR) models, which represent queries and documents with fixed-width vectors and retrieve relevant ones via nearest neighbor search, have drawn increasing attention from the IR community. However, previous studies have shown that the effectiveness of DR critically relies on sufficient training signals, which leads to severe performance degradation when applied in out-of-domain scenarios, where large-scale training data are usually unavailable. To solve this problem, existing studies adopt a data-augmentation-plus-joint-training paradigm to construct weak/pseudo supervisions on the target domain and combine them with the large-scale human annotated data on the source domain to train the DR models. However, they don’t explicitly distinguish the data and the supervision signals in the training process and simply assume that the DR models are mighty enough to capture and memorize different domain knowledge and relevance matching patterns without guidance, which, as shown in this paper, is not true. Based on this observation, we propose a Robust Multi-Supervision Combining strategy (RMSC) that decouples the domain and supervision signals by explicitly telling the DR models how the domain data and supervision signals are combined in the training data with specially designed soft tokens. With the extra soft tokens to store the domain-specific and supervisionspecific knowledge, RMSC allows the DR models to conduct retrieval based on human-like relevance matching patterns and target-specific language distribution on the target domain without human annotations. Extensive experiments on zeroshot … · 01 Jan 2024
Legal question answering based on case documents is a pivotal legal AI application and helps extract key elements from the legal case documents to promote downstream tasks. Intuitively, the form of this task is similar to legal machine reading comprehension. However, in existing legal machine reading comprehension datasets, the background information is much shorter than the legal case documents, and the questions are not designed from the perspective of legal knowledge. In this paper, we present LeDQA 1, the first Chinese legal case document-based question answering dataset to our best knowledge. Specifically, we build a comprehensive question schema (including 48 element-based questions) for the Chinese civil law by legal professionals. And considering the cost of human annotations are too expensive, we use one of the SOTA LLMs (ie, GPT-4) to annotate the relevant sentences to these questions in each case document. The constructed dataset originates from Chinese civil cases and contains 100 case documents, 4,800 casequestion pairs and 132,048 sentence-level relevance annotations. We implement several text matching algorithms for relevant sentence selection and various Large Language Models (LLMs) for legal question answering on LeDQA. The experimental results indicate that incorporating relevant sentences can benefit the performance of question answering models, but further efforts are still required to address the remaining challenges such as retrieving irrelevant sentences and incorrect reasoning between retrieved sentences. · 01 Jan 2024
2023
arXiv preprint arXiv:2312.10661 · 17 Dec 2023
(No Title) · 12 Dec 2023
Proceedings of NTCIR-17. https://doi. org/10.20736/0002001317 · 12 Dec 2023
(No Title) · 12 Dec 2023
(No Title) · 12 Dec 2023
Proceedings of the NTCIR-17 Conference · 12 Dec 2023
arXiv preprint arXiv:2312.05669 · 09 Dec 2023
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region · 26 Nov 2023
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region · 26 Nov 2023
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region · 26 Nov 2023
arXiv preprint arXiv:2311.10501 · 17 Nov 2023
arXiv preprint arXiv:2311.09889 · 16 Nov 2023
Journal of Tsinghua University (Science and Technology) · 06 Nov 2023
arXiv preprint arXiv:2311.00333 · 01 Nov 2023
arXiv preprint arXiv:2310.17609 · 26 Oct 2023
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management · 21 Oct 2023
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management · 21 Oct 2023
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management · 21 Oct 2023
Proceedings of the 32nd ACM International Conference on Information and Knowledge Management · 21 Oct 2023
arXiv preprint arXiv:2310.04735 · 07 Oct 2023
arXiv preprint arXiv:2309.17078 · 29 Sep 2023
GNN4EEG: A Benchmark and Toolkit for Electroencephalography Classification with Graph Neural Network
arXiv preprint arXiv:2309.15515 · 27 Sep 2023
Proceedings of the 17th ACM Conference on Recommender Systems · 14 Sep 2023
Orphanet Journal of Rare Diseases · 09 Aug 2023
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining · 06 Aug 2023
ACM Transactions on Information Systems · 25 Jul 2023
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval · 19 Jul 2023
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval · 19 Jul 2023
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval · 18 Jul 2023
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval · 18 Jul 2023
Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval · 18 Jul 2023
arXiv preprint arXiv:2307.00250 · 01 Jul 2023
arXiv preprint arXiv:2305.16637 · 26 May 2023
arXiv preprint arXiv:2305.16606 · 26 May 2023
arXiv preprint arXiv:2305.09918 · 17 May 2023
arXiv preprint arXiv:2305.06812 · 11 May 2023
arXiv preprint arXiv:2305.06817 · 11 May 2023
arXiv preprint arXiv:2305.05393 · 09 May 2023
Proceedings of the ACM Web Conference 2023 · 30 Apr 2023
Proceedings of the ACM Web Conference 2023 · 30 Apr 2023
arXiv preprint arXiv:2304.12650 · 25 Apr 2023
arXiv preprint arXiv:2304.07988 · 17 Apr 2023
arXiv preprint arXiv:2304.08062 · 17 Apr 2023
arXiv preprint arXiv:2304.07944 · 17 Apr 2023
arXiv preprint arXiv:2304.07450 · 15 Apr 2023
European Conference on Information Retrieval · 17 Mar 2023
arXiv preprint arXiv:2303.04710 · 28 Feb 2023
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining · 27 Feb 2023
Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining · 27 Feb 2023
ACM Transactions on Information Systems · 25 Feb 2023
ACM Transactions on Information Systems · 07 Feb 2023
《 广西师范大学学报》(自然科学版) · 06 Feb 2023
arXiv preprint arXiv:2301.12504 · 29 Jan 2023
arXiv preprint arXiv:2301.10389 · 25 Jan 2023
ACM Transactions on Information Systems · 09 Jan 2023
Lecture Notes in Computer Science · 01 Jan 2023
ACM Transactions on Information Systems · 01 Jan 2023
ACM Transactions on Information Systems · 01 Jan 2023
2022
ACM Transactions on Information Systems · 17 Nov 2022
ACM Transactions on Information Systems · 28 Oct 2022
Proceedings of the 31st ACM International Conference on Information & Knowledge Management · 17 Oct 2022
Proceedings of the 31st ACM International Conference on Information & Knowledge Management · 17 Oct 2022
Proceedings of the 31st ACM International Conference on Information & Knowledge Management · 17 Oct 2022
Brain Topography Adaptive Network for Satisfaction Modeling in Interactive Information Access System
Proceedings of the 30th ACM International Conference on Multimedia · 10 Oct 2022
CCF International Conference on Natural Language Processing and Chinese Computing · 24 Sep 2022
China Conference on Information Retrieval · 16 Sep 2022
Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies · 07 Sep 2022
Information Processing & Management · 01 Sep 2022
arXiv preprint arXiv:2208.07563 · 16 Aug 2022
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining · 14 Aug 2022
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining · 14 Aug 2022
Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining · 14 Aug 2022
arXiv preprint arXiv:2208.05753 · 11 Aug 2022
计算机科学技术学报 · 25 Jul 2022
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval · 06 Jul 2022
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval · 06 Jul 2022
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval · 06 Jul 2022
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval · 06 Jul 2022
Journal of Computer Science and Technology · 01 Jul 2022
arXiv preprint arXiv:2206.05368 · 10 Jun 2022
arXiv preprint arXiv:2204.11447 · 25 Apr 2022
Proceedings of the ACM Web Conference 2022 · 25 Apr 2022
Proceedings of the ACM Web Conference 2022 · 25 Apr 2022
Proceedings of the ACM Web Conference 2022 · 25 Apr 2022
Proceedings of the ACM Web Conference 2022 · 25 Apr 2022
arXiv preprint arXiv:2204.03046 · 06 Apr 2022
arXiv preprint arXiv:2204.02659 · 06 Apr 2022
ACM Transactions on Information Systems (TOIS) · 24 Mar 2022
Proceedings of the 2022 Conference on Human Information Interaction and Retrieval · 14 Mar 2022
International Journal of Machine Learning and Cybernetics · 06 Mar 2022
Big Data Research · 28 Feb 2022
ACM Transactions on Information Systems · 14 Feb 2022
Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining · 11 Feb 2022
Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining · 11 Feb 2022
Proceedings of the Fifteenth ACM International Conference on Web Search and Data Mining · 11 Feb 2022
Advances in Computational Intelligence · 10 Jan 2022
Proceedings of the 16th NTCIR Conference on Evaluation of Information Access Technologies · 01 Jan 2022
With the development of digital information storage technology and portable sensing devices, users are gradually accustomed to recording their personal life (ie, lifelog) in various digital ways. Therefore, the retrieval of lifelogging has become a new and essential research topic in related fields. Unlike traditional search engines, in lifelog, text and other data automatically recorded in real-time by sensors bring challenges to data arrangement and search. As the dataset is highly personalized, interactions and feedback from users should also be considered in the search engine. This paper describes our interactive approach for the NTCIR-16 Lifelog-4 Task. The task is to search relevant lifelog images from the users’ daily lifelog given an event topic. A significant challenge is how to bridge the semantic gap between lifelog images and event-level topics. We propose a framework to address this problem with a multi-functional and flexible feedback mechanism and result presentation for interaction in a search engine. Besides, we propose a query text parsing procedure that parses the long query text into keywords and fills the fields automatically. We analyzed the interactive lifelog search engine with 12 topics constructed by ourselves according to LSC’18 development topics. Finally, we achieved an official result of 741 at the NTCIR-16 Lifelog-4 task in terms of RelRet score over 48 topics. · 01 Jan 2022
Proceedings of NTCIR-16. to appear · 01 Jan 2022
arXiv · 01 Jan 2022
2021
ACM SIGIR Forum · 01 Dec 2021
arXiv preprint arXiv:2111.13957 · 27 Nov 2021
信息安全学报 · 29 Oct 2021
Proceedings of the 30th ACM International Conference on Information & Knowledge Management · 26 Oct 2021
Proceedings of the 30th ACM International Conference on Information & Knowledge Management · 26 Oct 2021
Proceedings of the 30th ACM International Conference on Information & Knowledge Management · 26 Oct 2021
Proceedings of the 30th ACM International Conference on Information & Knowledge Management · 26 Oct 2021
Proceedings of the 30th ACM International Conference on Information & Knowledge Management · 26 Oct 2021
Proceedings of the 30th ACM International Conference on Information & Knowledge Management · 26 Oct 2021
Journal of Software · 26 Oct 2021
Proceedings of the 30th ACM International Conference on Information & Knowledge Management · 26 Oct 2021
ACM Transactions on Information Systems (TOIS) · 27 Sep 2021
arXiv preprint arXiv:2109.10560 · 22 Sep 2021
Frontiers of Computer Science · 11 Sep 2021
中文信息学报 · 31 Aug 2021
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining · 14 Aug 2021
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining · 14 Aug 2021
Frontiers in Digital Health · 11 Aug 2021
arXiv e-prints · 01 Aug 2021
ACM Transactions on Information Systems · 26 Jul 2021
Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval · 11 Jul 2021
Proceedings of the 44th international ACM SIGIR conference on research and development in information retrieval · 11 Jul 2021
Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval · 11 Jul 2021
Proceedings of the 44th international ACM SIGIR conference on research and development in information retrieval · 11 Jul 2021
Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval · 11 Jul 2021
Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval · 11 Jul 2021
Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval · 11 Jul 2021
arXiv preprint arXiv:2106.06467 · 11 Jun 2021
Proceedings of the AAAI Conference on Artificial Intelligence · 18 May 2021
Pacific-Asia Conference on Knowledge Discovery and Data Mining · 08 May 2021
ACM Transactions on Information Systems · 30 Apr 2021
Proceedings of the web conference 2021 · 19 Apr 2021
Proceedings of the Web Conference 2021 · 19 Apr 2021
Proceedings of the Web Conference 2021 · 19 Apr 2021
Proceedings of the 14th ACM International Conference on Web Search and Data Mining · 08 Mar 2021
Proceedings of the 14th ACM International Conference on Web Search and Data Mining · 08 Mar 2021
Journal of South China University of Technology (Natural Science Edition) · 01 Jan 2021
中文信息学报 · 01 Jan 2021
Evaluating Information Retrieval and Access Tasks: NTCIR's Legacy of Research Impact · 01 Jan 2021
As queries submitted by users directly a ect search experiences, how to organize queries has always been a research focus in Web search studies. While search request becomes complex and exploratory, many search sessions contain more than a single query thus reformulation becomes a necessity. To help users better formulate their queries in these complex search tasks, modern search engines usually provide a series of reformulation entries on search engine result pages (SERPs), ie, query suggestions and related entities. However, few existing work have thoroughly studied why and how users perform query reformulations in these heterogeneous interfaces. Therefore, whether search engines provide sucient assistance for users in reformulating queries remains underinvestigated. To shed light on this research question, we conducted a eld study to analyze ne-grained user reformulation behaviors including reformulation type, entry, reason, and the inspiration source with various search intents. Di erent from existing e orts that rely on external assessors to make judgments, in the eld study we collect both implicit behavior signals and explicit user feedback information. Analysis results demonstrate that query reformulation behavior in Web search varies with the type of search tasks. We also found that the current query suggestion/related query recommendations provided by search engines do not o er enough help for users in complex search tasks. Based on the ndings in our eld study, we design a supervised learning framework to predict: 1) the reason behind each query reformulation, and 2) how users organize the reformulated query … · 01 Jan 2021
Proceedings of the Eighth International Competition on Legal Information Extraction/Entailment, COLIEE2021 · 01 Jan 2021
Information Retrieval: 27th China Conference, CCIR 2021, Dalian, China, October 29–31, 2021, Proceedings 27 · 01 Jan 2021
中文信息学报 · 01 Jan 2021
中国应用法学 · 01 Jan 2021
中国科学基金 · 01 Jan 2021
2020
ACM Transactions on Information Systems (TOIS) · 31 Dec 2020
arXiv preprint arXiv:2012.13102 · 24 Dec 2020
2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) · 14 Dec 2020
ACM SIGIR Forum · 01 Dec 2020
arXiv preprint arXiv:2010.10469 · 20 Oct 2020
Proceedings of the 29th ACM International Conference on Information & Knowledge Management · 19 Oct 2020
Proceedings of the 29th ACM International Conference on Information & Knowledge Management · 19 Oct 2020
Proceedings of the 29th ACM International Conference on Information & Knowledge Management · 19 Oct 2020
CCF International Conference on Natural Language Processing and Chinese Computing · 02 Oct 2020
CCF International Conference on Natural Language Processing and Chinese Computing · 02 Oct 2020
Proceedings of the Association for Information Science and Technology · 01 Oct 2020
Proceedings of the Association for Information Science and Technology · 01 Oct 2020
Frontiers of Computer Science · 29 Sep 2020
China Conference on Information Retrieval · 10 Aug 2020
Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval · 25 Jul 2020
Proceedings of the 43rd international acm sigir conference on research and development in information retrieval · 25 Jul 2020
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval · 25 Jul 2020
Proceedings of the 43rd international ACM SIGIR conference on research and development in information retrieval · 25 Jul 2020
Proceedings of the 43rd international acm sigir conference on research and development in information retrieval · 25 Jul 2020
Proceedings of the 43rd International ACM SIGIR conference on research and development in Information Retrieval · 25 Jul 2020
Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval · 25 Jul 2020
Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval · 25 Jul 2020
Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval · 25 Jul 2020
Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval · 25 Jul 2020
Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval · 25 Jul 2020
Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval · 25 Jul 2020
Proceedings of the 43rd International ACM SIGIR Conference on Research and Development in Information Retrieval · 25 Jul 2020
IJCAI · 01 Jul 2020
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence · 01 Jul 2020
arXiv preprint arXiv:2006.15498 · 28 Jun 2020
Proceedings of The Web Conference 2020 · 19 Apr 2020
Proceedings of The Web Conference 2020 · 19 Apr 2020
Proceedings of the AAAI Conference on Artificial Intelligence · 03 Apr 2020
ACM Transactions on Information Systems · 18 Mar 2020
ACM SIGWEB Newsletter · 13 Feb 2020
Proceedings of the 13th International Conference on Web Search and Data Mining · 20 Jan 2020
Proceedings of the 13th International Conference on Web Search and Data Mining · 20 Jan 2020
AI Open · 01 Jan 2020
2019
Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval · 18 Jul 2019
Special thanks to Yi Ren and Zhefan Wang for the initial construction of this page.