Fetching the paper…
Reading the bibliography…
Large language models (LLMs) can capture rich representations of concepts that are useful for real-world tasks.
Physiobank, physiotoolkit, and physionet: components of a new research resource for complex physiologic signals
A. L. Goldberger, L. A. Amaral, L. Glass, J. M. Hausdorff, P. C. Ivanov, R. G. Mark, J. E. Mietus, G. B. Moody, C.-K. Peng, and H. E. Stanley · 2000
Earlier work this paper cites.
Grounding language in bodily states
A. M. Glenberg, D. Havas, R. Becker, and M. Rinck · 2005
Earlier work this paper cites.
The phq-8 as a measure of current depression in the general population
K. Kroenke, T. W. Strine, R. L. Spitzer, J. B. Williams, J. T. Berry, and A. H. Mokdad · 2009
Earlier work this paper cites.
Introducing a new benchmarked dataset for activity monitoring
A. Reiss and D. Stricker · 2012
Earlier work this paper cites.
Mimic-iii, a freely accessible critical care database
A. E. Johnson, T. J. Pollard, L. Shen, L.-w. H. Lehman, M. Feng, M. Ghassemi, B. Moody, P. Szolovits, L. Anthony Celi, and R. G. Mark · 2016
Earlier work this paper cites.
Image-grounded conversations: Multimodal context for natural question and response generation
N. Mostafazadeh, C. Brockett, W. B. Dolan, M. Galley, J. Gao, G. Spithourakis, and L. Vanderwende · 2017
Earlier work this paper cites.
Emotional dialogue generation using image-grounded language models
B. Huber, D. McDuff, C. Brockett, M. Galley, and B. Dolan · 2018
Earlier work this paper cites.
Superglue: A stickier benchmark for general-purpose language understanding systems
A. Wang, Y. Pruksachatkun, N. Nangia, A. Singh, J. Michael, F. Hill, O. Levy, and S. Bowman · 2019
Earlier work this paper cites.
L. Zhou, Y. Kalantidis, X. Chen, J. J. Corso, and M. Rohrbach · 2019
Earlier work this paper cites.
Language models are few-shot learners
T. Brown, B. Mann, N. Ryder, M. Subbiah, J. D. Kaplan, P. Dhariwal, A. Neelakantan, P. Shyam, G. Sastry, A. Askell, et al · 2020
Earlier work this paper cites.
Scaling laws for neural language models
J. Kaplan, S. McCandlish, T. Henighan, T. B. Brown, B. Chess, R. Child, S. Gray, A. Radford, J. Wu, and D. Amodei · 2020
Cited alongside, same era.
Using natural language processing to understand people and culture
J. Berger and G. Packard · 2021
Cited alongside, same era.
Evaluating large language models trained on code
M. Chen, J. Tworek, H. Jun, Q. Yuan, H. P. d. O. Pinto, J. Kaplan, H. Edwards, Y. Burda, N. Joseph, G. Brockman, et al · 2021
Cited alongside, same era.
Domain-specific language model pretraining for biomedical natural language processing
Y. Gu, R. Tinn, H. Cheng, M. Lucas, N. Usuyama, X. Liu, T. Naumann, J. Gao, and H. Poon · 2021
Cited alongside, same era.
The power of scale for parameter-efficient prompt tuning
B. Lester, R. Al-Rfou, and N. Constant · 2021
Grounded language-image pre-training
L. H. Li, P. Zhang, H. Zhang, J. Yang, C. Li, Y. Zhong, L. Wang, L. Yuan, L. Zhang, J.-N. Hwang, et al · 2022
Later among the works it cites.
Detection of atrial fibrillation in a large population using wearable devices: the fitbit heart study
S. A. Lubitz, A. Z. Faranesh, C. Selvaggi, S. J. Atlas, D. D. McManus, D. E. Singer, S. Pagoto, M. V. McConnell, A. Pantelopoulos, and A. S. Foulkes · 2022
Later among the works it cites.
Limitations of language models in arithmetic and symbolic induction
J. Qian, H. Wang, Z. Li, S. Li, and X. Yan · 2022
Later among the works it cites.
Large language models encode clinical knowledge
K. Singhal, S. Azizi, T. Tu, S. S. Mahdavi, J. Wei, H. W. Chung, N. Scales, A. Tanwani, H. Cole-Lewis, S. Pfohl, et al · 2022
Later among the works it cites.
Mad: A scalable dataset for language grounding in videos from movie audio descriptions
M. Soldan, A. Pardo, J. L. Alcázar, F. Caba, C. Zhao, S. Giancola, and B. Ghanem · 2022
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Text-to-audio grounding: Building correspondence between captions and sound events
X. Xu, H. Dinkel, M. Wu, and K. Yu · 2021
Cited alongside, same era.
Do as i can, not as i say: Grounding language in robotic affordances
M. Ahn, A. Brohan, N. Brown, Y. Chebotar, O. Cortes, B. David, C. Finn, K. Gopalakrishnan, K. Hausman, A. Herzog, et al · 2022
Cited alongside, same era.
Palm: Scaling language modeling with pathways
A. Chowdhery, S. Narang, J. Devlin, M. Bosma, G. Mishra, A. Roberts, P. Barham, H. W. Chung, C. Sutton, S. Gehrmann, et al · 2022
Cited alongside, same era.
Talebrush: sketching stories with generative pretrained language models
J. J. Y. Chung, W. Kim, K. M. Yoo, H. Lee, E. Adar, and M. Chang · 2022
Cited alongside, same era.
Effectiveness of wearable activity trackers to increase physical activity and improve health: a systematic review of systematic reviews and meta-analyses
T. Ferguson, T. Olds, R. Curtis, H. Blake, A. J. Crozier, K. Dankiw, D. Dumuid, D. Kasai, E. O’Connor, R. Virgara, et al · 2022
Cited alongside, same era.
Later among the works it cites.
Lamda: Language models for dialog applications
R. Thoppilan, D. De Freitas, J. Hall, N. Shazeer, A. Kulshreshtha, H.-T. Cheng, A. Jin, T. Bos, L. Baker, Y. Du, et al · 2022
Later among the works it cites.
Natural language processing applied to mental illness detection: a narrative review
T. Zhang, A. M. Schoene, S. Ji, and S. Ananiadou · 2022
Later among the works it cites.
Gpt-4 technical report, 2023
OpenAI · 2023
Closest in time.
Llama: Open and efficient foundation language models
H. Touvron, T. Lavril, G. Izacard, X. Martinet, M.-A. Lachaux, T. Lacroix, B. Rozière, N. Goyal, E. Hambro, F. Azhar, et al · 2023
Closest in time.
How well do large language models perform in arithmetic tasks?
Z. Yuan, H. Yuan, C. Tan, W. Wang, and S. Huang · 2023
Closest in time.