{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T18:15:25Z","timestamp":1758824125135,"version":"3.41.0"},"publisher-location":"New York, NY, USA","reference-count":59,"publisher":"ACM","license":[{"start":{"date-parts":[[2025,5,6]],"date-time":"2025-05-06T00:00:00Z","timestamp":1746489600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["2003279","1826967","2100237","1911095","2112665","2120019","2211386"],"award-info":[{"award-number":["2003279","1826967","2100237","1911095","2112665","2120019","2211386"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000028","name":"Semiconductor Research Corporation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000028","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,5,6]]},"DOI":"10.1145\/3715014.3722074","type":"proceedings-article","created":{"date-parts":[[2025,5,4]],"date-time":"2025-05-04T23:37:21Z","timestamp":1746401841000},"page":"282-289","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["SensorQA: A Question Answering Benchmark for Daily-Life Monitoring"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-3854-7930","authenticated-orcid":false,"given":"Benjamin","family":"Reichman","sequence":"first","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9638-6184","authenticated-orcid":false,"given":"Xiaofan","family":"Yu","sequence":"additional","affiliation":[{"name":"University of California, San Diego, La Jolla, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0641-3677","authenticated-orcid":false,"given":"Lanxiang","family":"Hu","sequence":"additional","affiliation":[{"name":"University of California, San Diego, La Jolla, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-0561-9471","authenticated-orcid":false,"given":"Jack","family":"Truxal","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-8410-3472","authenticated-orcid":false,"given":"Atishay","family":"Jain","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, USA"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-5447-8693","authenticated-orcid":false,"given":"Rushil","family":"Chandrupatla","sequence":"additional","affiliation":[{"name":"University of California, San Diego, La Jolla, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6954-997X","authenticated-orcid":false,"given":"Tajana S","family":"Rosing","sequence":"additional","affiliation":[{"name":"University of California, San Diego, La Jolla, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3358-6362","authenticated-orcid":false,"given":"Larry","family":"Heck","sequence":"additional","affiliation":[{"name":"Georgia Institute of Technology, Atlanta, USA"}]}],"member":"320","published-online":{"date-parts":[[2025,5,6]]},"reference":[{"key":"e_1_3_2_1_1_1","unstructured":"2024. Amazon Mechanical Turk. https:\/\/www.mturk.com\/. [Online]."},{"key":"e_1_3_2_1_2_1","unstructured":"2024. Jetson TX2 Module. https:\/\/developer.nvidia.com\/embedded\/jetson-tx2. [Online]."},{"key":"e_1_3_2_1_3_1","unstructured":"2024. SensorQA Dataset. https:\/\/anonymous.4open.science\/r\/SensorQA-373E\/. [Online]."},{"key":"e_1_3_2_1_4_1","volume-title":"Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al.","author":"Achiam Josh","year":"2023","unstructured":"Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023. Gpt-4 technical report. arXiv preprint arXiv:2303.08774 (2023)."},{"key":"e_1_3_2_1_5_1","volume-title":"Proceedings of the acl workshop on intrinsic and extrinsic evaluation measures for machine translation and\/or summarization. 65--72","author":"Banerjee Satanjeev","year":"2005","unstructured":"Satanjeev Banerjee and Alon Lavie. 2005. METEOR: An automatic metric for MT evaluation with improved correlation with human judgments. In Proceedings of the acl workshop on intrinsic and extrinsic evaluation measures for machine translation and\/or summarization. 65--72."},{"key":"e_1_3_2_1_6_1","volume-title":"A Question-Entailment Approach to Question Answering. BMC Bioinform. 20, 1","author":"Abacha Asma Ben","year":"2019","unstructured":"Asma Ben Abacha and Dina Demner-Fushman. 2019. A Question-Entailment Approach to Question Answering. BMC Bioinform. 20, 1 (2019), 511:1--511:23. https:\/\/bmcbioinformatics.biomedcentral.com\/articles\/10.1186\/s12859-019-3119-4"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3666025.3699331"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patrec.2012.12.014"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.emnlp-main.300"},{"key":"e_1_3_2_1_10_1","volume-title":"Xing","author":"Chiang Wei-Lin","year":"2023","unstructured":"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. Vicuna: An Open-Source Chatbot Impressing GPT-4 with 90%* ChatGPT Quality. https:\/\/lmsys.org\/blog\/2023-03-30-vicuna\/"},{"key":"e_1_3_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N19-1300"},{"key":"e_1_3_2_1_12_1","volume-title":"Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805","author":"Devlin Jacob","year":"2018","unstructured":"Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018. Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805 (2018)."},{"key":"e_1_3_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3659604"},{"key":"e_1_3_2_1_14_1","volume-title":"Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering. In Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Goyal Yash","year":"2017","unstructured":"Yash Goyal, Tejas Khot, Douglas Summers-Stay, Dhruv Batra, and Devi Parikh. 2017. Making the V in VQA Matter: Elevating the Role of Image Understanding in Visual Question Answering. In Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01842"},{"key":"e_1_3_2_1_16_1","volume-title":"Onellm: One framework to align all modalities with language. arXiv preprint arXiv:2312.03700","author":"Han Jiaming","year":"2023","unstructured":"Jiaming Han, Kaixiong Gong, Yiyuan Zhang, Jiaqi Wang, Kaipeng Zhang, Dahua Lin, Yu Qiao, Peng Gao, and Xiangyu Yue. 2023. Onellm: One framework to align all modalities with language. arXiv preprint arXiv:2312.03700 (2023)."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02510"},{"key":"e_1_3_2_1_18_1","volume-title":"30000+ Questions for Medical Visual Question Answering. ArXiv abs\/2003.10286","author":"He Xuehai","year":"2020","unstructured":"Xuehai He, Yichen Zhang, Luntian Mou, Eric P. Xing, and Pengtao Xie. 2020. PathVQA: 30000+ Questions for Medical Visual Question Answering. ArXiv abs\/2003.10286 (2020). https:\/\/api.semanticscholar.org\/CorpusID:214612106"},{"key":"e_1_3_2_1_19_1","volume-title":"Lora: Low-rank adaptation of large language models. arXiv preprint arXiv:2106.09685","author":"Hu Edward J","year":"2021","unstructured":"Edward J Hu, Yelong Shen, Phillip Wallis, Zeyuan Allen-Zhu, Yuanzhi Li, Shean Wang, Lu Wang, and Weizhu Chen. 2021. Lora: Low-rank adaptation of large language models. arXiv preprint arXiv:2106.09685 (2021)."},{"key":"e_1_3_2_1_20_1","volume-title":"KET-QA: A Dataset for Knowledge Enhanced Table Question Answering. arXiv preprint arXiv:2405.08099","author":"Hu Mengkang","year":"2024","unstructured":"Mengkang Hu, Haoyu Dong, Ping Luo, Shi Han, and Dongmei Zhang. 2024. KET-QA: A Dataset for Knowledge Enhanced Table Question Answering. arXiv preprint arXiv:2405.08099 (2024)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P17-1147"},{"key":"e_1_3_2_1_22_1","volume-title":"Health-llm: Large language models for health prediction via wearable sensor data. arXiv preprint arXiv:2401.06866","author":"Kim Yubin","year":"2024","unstructured":"Yubin Kim, Xuhai Xu, Daniel McDuff, Cynthia Breazeal, and Hae Won Park. 2024. Health-llm: Large language models for health prediction via wearable sensor data. arXiv preprint arXiv:2401.06866 (2024)."},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00276"},{"key":"e_1_3_2_1_24_1","volume-title":"Rouge: A package for automatic evaluation of summaries. In Text summarization branches out. 74--81.","author":"Lin Chin-Yew","year":"2004","unstructured":"Chin-Yew Lin. 2004. Rouge: A package for automatic evaluation of summaries. In Text summarization branches out. 74--81."},{"key":"e_1_3_2_1_25_1","volume-title":"AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration. In MLSys.","author":"Lin Ji","year":"2024","unstructured":"Ji Lin, Jiaming Tang, Haotian Tang, Shang Yang, Wei-Ming Chen, Wei-Chen Wang, Guangxuan Xiao, Xingyu Dang, Chuang Gan, and Song Han. 2024. AWQ: Activation-aware Weight Quantization for LLM Compression and Acceleration. In MLSys."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52733.2024.02484"},{"key":"e_1_3_2_1_27_1","unstructured":"Junling Liu Peilin Zhou Yining Hua Dading Chong Zhongyu Tian Andrew Liu Helin Wang Chenyu You Zhenhua Guo Lei Zhu et al. 2024. Benchmarking large language models on cmexam-a comprehensive chinese medical exam dataset. Advances in Neural Information Processing Systems 36 (2024)."},{"key":"e_1_3_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2020.2988782"},{"key":"e_1_3_2_1_29_1","volume-title":"The 36th Conference on Neural Information Processing Systems (NeurIPS).","author":"Lu Pan","year":"2022","unstructured":"Pan Lu, Swaroop Mishra, Tony Xia, Liang Qiu, Kai-Wei Chang, Song-Chun Zhu, Oyvind Tafjord, Peter Clark, and Ashwin Kalyan. 2022. Learn to Explain: Multimodal Reasoning via Thought Chains for Science Question Answering. In The 36th Conference on Neural Information Processing Systems (NeurIPS)."},{"key":"e_1_3_2_1_30_1","volume-title":"Anymal: An efficient and scalable any-modality augmented language model. arXiv preprint arXiv:2309.16058","author":"Moon Seungwhan","year":"2023","unstructured":"Seungwhan Moon, Andrea Madotto, Zhaojiang Lin, Tushar Nagarajan, Matt Smith, Shashank Jain, Chun-Fu Yeh, Prakash Murugesan, Peyman Heidari, Yue Liu, et al. 2023. Anymal: An efficient and scalable any-modality augmented language model. arXiv preprint arXiv:2309.16058 (2023)."},{"key":"e_1_3_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2023.findings-emnlp.883"},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3539490.3539603"},{"key":"e_1_3_2_1_33_1","unstructured":"US Department of Health Human Services et al. 2021. Increase the proportion of adults who do enough aerobic physical activity for substantial health benefits---PA-02."},{"key":"e_1_3_2_1_34_1","doi-asserted-by":"publisher","DOI":"10.1145\/3495243.3560519"},{"key":"e_1_3_2_1_35_1","doi-asserted-by":"publisher","DOI":"10.1145\/3581791.3596844"},{"key":"e_1_3_2_1_36_1","volume-title":"Proceedings of the 40th annual meeting of the Association for Computational Linguistics. 311--318","author":"Papineni Kishore","year":"2002","unstructured":"Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40th annual meeting of the Association for Computational Linguistics. 311--318."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i5.28253"},{"key":"e_1_3_2_1_38_1","volume-title":"International conference on machine learning. PMLR, 8748--8763","author":"Radford Alec","year":"2021","unstructured":"Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al. 2021. Learning transferable visual models from natural language supervision. In International conference on machine learning. PMLR, 8748--8763."},{"key":"e_1_3_2_1_39_1","first-page":"1","article-title":"Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer","volume":"21","author":"Raffel Colin","year":"2020","unstructured":"Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer. Journal of Machine Learning Research 21, 140 (2020), 1--67. http:\/\/jmlr.org\/papers\/v21\/20-074.html","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-2124"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP49357.2023.10096074"},{"key":"e_1_3_2_1_42_1","volume-title":"Sam-vqa: Supervised attention-based visual question answering model for post-disaster damage assessment on remote sensing imagery","author":"Sarkar Argho","year":"2023","unstructured":"Argho Sarkar, Tashnim Chowdhury, Robin Murphy, Aryya Gangopadhyay, and Maryam Rahnemoonfar. 2023. Sam-vqa: Supervised attention-based visual question answering model for post-disaster damage assessment on remote sensing imagery. IEEE Transactions on Geoscience and Remote Sensing (2023)."},{"key":"e_1_3_2_1_43_1","unstructured":"Satyajit Sinha. 2023. State of IoT 2024: Number of connected IoT devices growing 13% to 18.8 billion globally. https:\/\/iot-analytics.com\/number-connected-iot-devices\/. [Online]."},{"key":"e_1_3_2_1_44_1","volume-title":"Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track. https:\/\/openreview.net\/forum?id=Vn5qZGxGj3","author":"Teng M\u00e9lisande","year":"2023","unstructured":"M\u00e9lisande Teng, Amna Elmustafa, Benjamin Akera, Yoshua Bengio, Hager Radi, Hugo Larochelle, and David Rolnick. 2023. SatBird: a Dataset for Bird Species Distribution Modeling using Remote Sensing and Citizen Science Data. In Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track. https:\/\/openreview.net\/forum?id=Vn5qZGxGj3"},{"key":"e_1_3_2_1_45_1","volume-title":"Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971","author":"Touvron Hugo","year":"2023","unstructured":"Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timoth\u00e9e Lacroix, Baptiste Rozi\u00e8re, Naman Goyal, Eric Hambro, Faisal Azhar, et al. 2023. Llama: Open and efficient foundation language models. arXiv preprint arXiv:2302.13971 (2023)."},{"key":"e_1_3_2_1_46_1","doi-asserted-by":"publisher","DOI":"10.1109\/MPRV.2017.3971131"},{"key":"e_1_3_2_1_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/3161192"},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i6.28357"},{"key":"e_1_3_2_1_49_1","doi-asserted-by":"publisher","DOI":"10.1145\/3666025.3699349"},{"key":"e_1_3_2_1_50_1","doi-asserted-by":"publisher","DOI":"10.1145\/3450268.3453529"},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1145\/3570361.3613299"},{"key":"e_1_3_2_1_52_1","doi-asserted-by":"publisher","DOI":"10.1145\/3625687.3625782"},{"key":"e_1_3_2_1_53_1","volume-title":"DrHouse: An LLM-empowered Diagnostic Reasoning System through Harnessing Outcomes from Sensor Data and Expert Knowledge. arXiv preprint arXiv:2405.12541","author":"Yang Bufang","year":"2024","unstructured":"Bufang Yang, Siyang Jiang, Lilin Xu, Kaiwei Liu, Hai Li, Guoliang Xing, Hongkai Chen, Xiaofan Jiang, and Zhenyu Yan. 2024. DrHouse: An LLM-empowered Diagnostic Reasoning System through Harnessing Outcomes from Sensor Data and Expert Knowledge. arXiv preprint arXiv:2405.12541 (2024)."},{"key":"e_1_3_2_1_54_1","volume-title":"Chris Xiaoxuan Lu, and Lihua Xie","author":"Yang Jianfei","year":"2024","unstructured":"Jianfei Yang, He Huang, Yunjiao Zhou, Xinyan Chen, Yuecong Xu, Shenghai Yuan, Han Zou, Chris Xiaoxuan Lu, and Lihua Xie. 2024. Mm-fi: Multi-modal non-intrusive 4d human dataset for versatile wireless sensing. Advances in Neural Information Processing Systems 36 (2024)."},{"key":"e_1_3_2_1_55_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1259"},{"key":"e_1_3_2_1_56_1","unstructured":"Junjie Ye Xuanting Chen Nuo Xu Can Zu Zekai Shao Shichun Liu Yuhan Cui Zeyang Zhou Chao Gong Yang Shen et al. 2023. A comprehensive capability analysis of gpt-3 and gpt-3.5 series models. arXiv preprint arXiv:2303.10420 (2023)."},{"key":"e_1_3_2_1_57_1","volume-title":"Llama-adapter: Efficient fine-tuning of language models with zero-init attention. arXiv preprint arXiv:2303.16199","author":"Zhang Renrui","year":"2023","unstructured":"Renrui Zhang, Jiaming Han, Chris Liu, Peng Gao, Aojun Zhou, Xiangfei Hu, Shilin Yan, Pan Lu, Hongsheng Li, and Yu Qiao. 2023. Llama-adapter: Efficient fine-tuning of language models with zero-init attention. arXiv preprint arXiv:2303.16199 (2023)."},{"key":"e_1_3_2_1_58_1","doi-asserted-by":"crossref","unstructured":"Haoxi Zhong Chaojun Xiao Cunchao Tu Tianyang Zhang Zhiyuan Liu and Maosong Sun. 2019. JEC-QA: A Legal-Domain Question Answering Dataset. arXiv:1911.12011 [cs.CL]","DOI":"10.1609\/aaai.v34i05.6519"},{"key":"e_1_3_2_1_59_1","volume-title":"TENT: Connect Language Models with IoT Sensors for Zero-Shot Activity Recognition. arXiv preprint arXiv:2311.08245","author":"Zhou Yunjiao","year":"2023","unstructured":"Yunjiao Zhou, Jianfei Yang, Han Zou, and Lihua Xie. 2023. TENT: Connect Language Models with IoT Sensors for Zero-Shot Activity Recognition. arXiv preprint arXiv:2311.08245 (2023)."}],"event":{"name":"SenSys '25: 23rd ACM Conference on Embedded Networked Sensor Systems","sponsor":["SIGARCH ACM Special Interest Group on Computer Architecture","SIGMETRICS ACM Special Interest Group on Measurement and Evaluation","SIGOPS ACM Special Interest Group on Operating Systems","SIGMOBILE ACM Special Interest Group on Mobility of Systems, Users, Data and Computing","SIGBED ACM Special Interest Group on Embedded Systems"],"location":"UC Irvine Student Center. Irvine CA USA","acronym":"SenSys '25"},"container-title":["Proceedings of the 23rd ACM Conference on Embedded Networked Sensor Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3715014.3722074","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/abs\/10.1145\/3715014.3722074","content-type":"text\/html","content-version":"vor","intended-application":"syndication"}],"deposited":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T01:56:52Z","timestamp":1750298212000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3715014.3722074"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,6]]},"references-count":59,"alternative-id":["10.1145\/3715014.3722074","10.1145\/3715014"],"URL":"https:\/\/doi.org\/10.1145\/3715014.3722074","relation":{},"subject":[],"published":{"date-parts":[[2025,5,6]]},"assertion":[{"value":"2025-05-06","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}