Schwenk, Dustin

Objaverse: A Universe of Annotated 3D Objects

Deitke, M., Schwenk, D., Salvador, J., Weihs, L., Michel, O., VanderBilt, E., Schmidt, L., Ehsanit, K., Kembhavi, A., & Farhadi, A. (2023) · 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

3D Shape Modeling and AnalysisAdvanced Neural Network Applications

Cited by 725

Are You Smarter Than a Sixth Grader? Textbook Question Answering for Multimodal Machine Comprehension

Kembhavi, A., Seo, M., Schwenk, D., Choi, J., Farhadi, A., & Hajishirzi, H. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Multimodal Machine Learning ApplicationsTopic Modeling

Cited by 244

RoboTHOR: An Open Simulation-to-Real Embodied AI Platform

Deitke, M., Han, W., Herrasti, A., Kembhavi, A., Kolve, E., Mottaghi, R., Salvador, J., Schwenk, D., VanderBilt, E., Wallingford, M., et al. (2020) · 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Reinforcement Learning in RoboticsRobot Manipulation and Learning

Cited by 220

X-LXMERT: Paint, Caption and Answer Questions with Multi-Modal Transformers

Cho, J., Lu, J., Schwenk, D., Hajishirzi, H., & Kembhavi, A. (2020) · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Multimodal Machine Learning ApplicationsGenerative Adversarial Networks and Image Synthesis

Cited by 99

OLMo: Accelerating the Science of Language Models

Groeneveld, D., Beltagy, I., Walsh, E., Bhagia, A., Kinney, R., Tafjord, O., Jha, A., Ivison, H., Magnusson, I., Wang, Y., et al. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 70

Dolma: an open corpus of three trillion tokens for language model pretraining research

Soldaini, L., Kinney, R., Bhagia, A., Schwenk, D., Atkinson, D., Authur, R., Bogin, B., Chandu, K., Dumas, J., Elazar, Y., et al. (2024) · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

Topic ModelingNatural Language Processing Techniques

Cited by 56

Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research

Soldaini, L., Kinney, R., Bhagia, A., Schwenk, D., Atkinson, D., Authur, R., Bogin, B., Chandu, K., Dumas, J., Elazar, Y., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 10

OLMo: Accelerating the Science of Language Models

Groeneveld, D., Beltagy, I., Walsh, P., Bhagia, A., Kinney, R., Tafjord, O., Jha, A. H., Ivison, H., Magnusson, I., Wang, Y., et al. (2024) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 10

What's In My Big Data?

Elazar, Y., Bhagia, A., Magnusson, I., Ravichander, A., Schwenk, D., Suhr, A., Walsh, P., Groeneveld, D., Soldaini, L., Singh, S., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 9

2 OLMo 2 Furious

OLMo, T., Walsh, P., Soldaini, L., Groeneveld, D., Lo, K., Arora, S., Bhagia, A., Gu, Y., Huang, S., Jordan, M., et al. (2025) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 2

Paloma: A Benchmark for Evaluating Language Model Fit

Magnusson, I., Bhagia, A., Hofmann, V., Soldaini, L., Jha, A. H., Tafjord, O., Schwenk, D., Walsh, E. P., Elazar, Y., Lo, K., et al. (2023) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 1