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With the rapid growth in sensor data, effectively interpreting and interfacing with these data in a human-understandable way has become crucial.
JEC-QA: A Legal-Domain Question Answering Dataset
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Know What You Don’t Know: Unanswerable Questions for SQuAD. In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers) , Iryna Gurevych and Yusuke Miyao (Eds.). Association for Computational Linguistics, Melbourne, Australia, 784–789
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Context recognition in-the-wild: Unified model for multi-modal sensors and multi-label classification
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HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering. In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing , Ellen Riloff, David Chiang, Julia Hockenmaier, and Jun’ichi Tsujii (Eds.). Association for Computational Linguistics, Brussels, Belgium, 2369–2380
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A Question-Entailment Approach to Question Answering
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BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions. In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers) , Jill Burstein, Christy Doran, and Thamar Solorio (Eds.). Association for Computational Linguistics, Minneapolis, Minnesota, 2924–2936
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Natural Questions: A Benchmark for Question Answering Research
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PathVQA: 30000+ Questions for Medical Visual Question Answering
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RSVQA: Visual question answering for remote sensing data
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Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer
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FinQA: A Dataset of Numerical Reasoning over Financial Data. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing , Marie-Francine Moens, Xuanjing Huang, Lucia Specia, and Scott Wen-tau Yih (Eds.). Association for Computational Linguistics, Online and Punta Cana, Dominican Republic, 3697–3711
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Lora: Low-rank adaptation of large language models
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Learning transferable visual models from natural language supervision. In International conference on machine learning . PMLR, 8748–8763
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DeepSQA: Understanding Sensor Data via Question Answering. In Proceedings of the International Conference on Internet-of-Things Design and Implementation . 106–118
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Ego4d: Around the world in 3,000 hours of egocentric video. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition . 18995–19012
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Llama-adapter: Efficient fine-tuning of language models with zero-init attention
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TENT: Connect Language Models with IoT Sensors for Zero-Shot Activity Recognition
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Amazon Mechanical Turk
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Jetson TX2 Module
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mmCLIP: Boosting mmWave-based Zero-shot HAR via Signal-Text Alignment. In Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems . 184–197
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Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering. In The 36th Conference on Neural Information Processing Systems (NeurIPS)
Pan Lu, Swaroop Mishra, Tony Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, and Ashwin Kalyan. 2022 · 2022
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Conversational ai therapist for daily function screening in home environments. In Proceedings of the 1st ACM International Workshop on Intelligent Acoustic Systems and Applications . 31–36
Jingping Nie, Hanya Shao, Minghui Zhao, Stephen Xia, Matthias Preindl, and Xiaofan Jiang. 2022 · 2022
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Cosmo: contrastive fusion learning with small data for multimodal human activity recognition. In Proceedings of the 28th Annual International Conference on Mobile Computing And Networking . 324–337
Xiaomin Ouyang, Xian Shuai, Jiayu Zhou, Ivy Wang Shi, Zhiyuan Xie, Guoliang Xing, and Jianwei Huang. 2022 · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al · 2023
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Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90%* ChatGPT Quality
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing. 2023 · 2023
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Onellm: One framework to align all modalities with language
Jiaming Han, Kaixiong Gong, Yiyuan Zhang, Jiaqi Wang, Kaipeng Zhang, Dahua Lin, Yu Qiao, Peng Gao, and Xiangyu Yue. 2023 · 2023
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Anymal: An efficient and scalable any-modality augmented language model
Seungwhan Moon, Andrea Madotto, Zhaojiang Lin, Tushar Nagarajan, Matt Smith, Shashank Jain, Chun-Fu Yeh, Prakash Murugesan, Peyman Heidari, Yue Liu, et al · 2023
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IMU2CLIP: Language-grounded Motion Sensor Translation with Multimodal Contrastive Learning. In Findings of the Association for Computational Linguistics: EMNLP 2023 . 13246–13253
Seungwhan Moon, Andrea Madotto, Zhaojiang Lin, Aparajita Saraf, Amy Bearman, and Babak Damavandi. 2023b · 2023
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From Classification to Clinical Insights: Towards Analyzing and Reasoning About Mobile and Behavioral Health Data With Large Language Models
Zachary Englhardt, Chengqian Ma, Margaret E Morris, Chun-Cheng Chang, Xuhai" Orson" Xu, Lianhui Qin, Daniel McDuff, Xin Liu, Shwetak Patel, and Vikram Iyer. 2024 · 2024
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Onellm: One framework to align all modalities with language. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition
Jiaming Han, Kaixiong Gong, Yiyuan Zhang, Jiaqi Wang, Kaipeng Zhang, Dahua Lin, Yu Qiao, Peng Gao, and Xiangyu Yue. 2024 · 2024
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KET-QA: A Dataset for Knowledge Enhanced Table Question Answering
Mengkang Hu, Haoyu Dong, Ping Luo, Shi Han, and Dongmei Zhang. 2024 · 2024
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Health-llm: Large language models for health prediction via wearable sensor data
Yubin Kim, Xuhai Xu, Daniel McDuff, Cynthia Breazeal, and Hae Won Park. 2024 · 2024
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AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration. In MLSys
Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Wei-Ming Chen, Wei-Chen Wang, Guangxuan Xiao, Xingyu Dang, Chuang Gan, and Song Han. 2024 · 2024
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Benchmarking large language models on cmexam-a comprehensive chinese medical exam dataset
Junling Liu, Peilin Zhou, Yining Hua, Dading Chong, Zhongyu Tian, Andrew Liu, Helin Wang, Chenyu You, Zhenhua Guo, Lei Zhu, et al · 2024
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Nuscenes-qa: A multi-modal visual question answering benchmark for autonomous driving scenario. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 38. 4542–4550
Tianwen Qian, Jingjing Chen, Linhai Zhuo, Yang Jiao, and Yu-Gang Jiang. 2024 · 2024
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State of IoT 2024: Number of connected IoT devices growing 13% to 18.8 billion globally
Satyajit Sinha. 2023 · 2024
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EarthVQA: Towards Queryable Earth via Relational Reasoning-Based Remote Sensing Visual Question Answering. In Proceedings of the AAAI Conference on Artificial Intelligence , Vol. 38. 5481–5489
Junjue Wang, Zhuo Zheng, Zihang Chen, Ailong Ma, and Yanfei Zhong. 2024 · 2024
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Large Model for Small Data: Foundation Model for Cross-Modal RF Human Activity Recognition. In Proceedings of the 22nd ACM Conference on Embedded Networked Sensor Systems . 436–449
Yuxuan Weng, Guoquan Wu, Tianyue Zheng, Yanbing Yang, and Jun Luo. 2024 · 2024
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Bufang Yang, Siyang Jiang, Lilin Xu, Kaiwei Liu, Hai Li, Guoliang Xing, Hongkai Chen, Xiaofan Jiang, and Zhenyu Yan. 2024b · 2024
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Mm-fi: Multi-modal non-intrusive 4d human dataset for versatile wireless sensing
Jianfei Yang, He Huang, Yunjiao Zhou, Xinyan Chen, Yuecong Xu, Shenghai Yuan, Han Zou, Chris Xiaoxuan Lu, and Lihua Xie. 2024a · 2024
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The Opportunity challenge: A benchmark database for on-body sensor-based activity recognition
Ricardo Chavarriaga, Hesam Sagha, Alberto Calatroni, Sundara Tejaswi Digumarti, Gerhard Tröster, José del R Millán, and Daniel Roggen. 2013 · 2042
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