Most cited papers
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Less is More: Recursive Reasoning with Tiny Networks
Jolicoeur-Martineau, A. (2025) · arXiv
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Byte Latent Transformer: Patches Scale Better Than Tokens
Pagnoni, A., Pasunuru, R., Rodriguez, P., Nguyen, J., Muller, B., Li, M., Zhou, C., Yu, L., Weston, J., Zettlemoyer, L., et al. (2024) · arXiv
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Symmetry Classification of Topological Photonic Crystals
De Nittis, G., & Lein, M. (2017) · arXiv
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In-context learning agents are asymmetric belief updaters
Schubert, J. A., Jagadish, A. K., Binz, M., & Schulz, E. (2024) · arXiv
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Baseline Defenses for Adversarial Attacks Against Aligned Language Models
Jain, N., Schwarzschild, A., Wen, Y., Somepalli, G., Kirchenbauer, J., Chiang, P.-Y., Goldblum, M., Saha, A., Geiping, J., & Goldstein, T. (2023) · arXiv
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Systematic human learning and generalization from a brief tutorial with explanatory feedback
Nam, A. J., & McClelland, J. L. (2021) · arXiv
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Glacial features of the Milan, Berlin, and Shelburne map areas of northern New Hampshire
Gerath, R. F. (1978) · McGill University
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Uncertainty-Based Abstention in LLMs Improves Safety and Reduces Hallucinations
Tomani, C., Chaudhuri, K., Evtimov, I., Cremers, D., & Ibrahim, M. (2024) · arXiv
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Language Embedded Radiance Fields for Zero-Shot Task-Oriented Grasping
Rashid, A., Sharma, S., Kim, C. M., Kerr, J., Chen, L., Kanazawa, A., & Goldberg, K. (2023) · arXiv
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Improving robustness against common corruptions by covariate shift adaptation
Schneider, S., Rusak, E., Eck, L., Bringmann, O., Brendel, W., & Bethge, M. (2020) · arXiv
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A Systematic Literature Review on the NIS2 Directive
Ruohonen, J. (2024) · arXiv
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Generative Adversarial User Model for Reinforcement Learning Based Recommendation System
Chen, X., Li, S., Li, H., Jiang, S., Qi, Y., & Song, L. (2018) · arXiv
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Peering into the Mind of Language Models: An Approach for Attribution in Contextual Question Answering
Phukan, A., Somasundaram, S., Saxena, A., Goswami, K., & Srinivasan, B. V. (2024) · arXiv
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AutoPrompt: eliciting knowledge from language models with automatically generated prompts
Shin, T., Razeghi, Y., Logan, R. L., Wallace, E., & Singh, S. (2020) · arXiv
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Sequence Modeling of Temporal Credit Assignment for Episodic Reinforcement Learning
Liu, Y., Luo, Y., Zhong, Y., Chen, X., Liu, Q., & Peng, J. (2019) · arXiv
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What shapes feature representations? Exploring datasets, architectures, and training
Hermann, K. L., & Lampinen, A. K. (2020) · arXiv
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ASReview Dory - New and exciting models for ASReview
van der Kuil, T., Teijema, J. J., de Bruin, J., & van de Schoot, R. (2026) · Zenodo
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Incorporating Spatial Awareness in Data-Driven Gesture Generation for Virtual Agents
Deichler, A., Alexanderson, S., & Beskow, J. (2024) · arXiv
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Investigating Morphosyntactic Variation in African American English on Twitter
Masis, T., Eggleston, C., Green, L. J., Jones, T., Armstrong, M., & O'Connor, B. (2023) · University of Massachusetts Amherst
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CoreKB Trust Network
Menotti, L., MARCHESIN, S., Giachelle, F., & Silvello, G. (2025) · Zenodo
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AQuaMuSe: Automatically Generating Datasets for Query-Based Multi-Document Summarization
Kulkarni, S., Chammas, S., Zhu, W., Sha, F., & Ie, E. (2020) · arXiv
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Train longer, generalize better: closing the generalization gap in large batch training of neural networks
Hoffer, E., Hubara, I., & Soudry, D. (2017) · arXiv
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BLOOM: A 176B-Parameter Open-Access Multilingual Language Model
Workshop, B., :, Scao, T. L., Fan, A., Akiki, C., Pavlick, E., Ilić, S., Hesslow, D., Castagné, R., Luccioni, A. S., et al. (2022) · arXiv
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