Most cited papers
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Mitigating Bus Bunching with Reinforcement Learning Enhanced by Semantic Stop Embedding
Dong, X., & Gayah, V. V. (2026) · arXiv
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SwarmHawk: Self-Sustaining Multi-Agent System for Landing on a Moving Platform through an Agent Supervision
Gupta, A., Dorzhieva, E., Baza, A., Alper, M., Fedoseev, A., & Tsetserukou, D. (2022) · arXiv
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Dense Associative Memory for Pattern Recognition
Krotov, D., & Hopfield, J. J. (2016) · arXiv
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Auditing Black-box Models for Indirect Influence
Adler, P., Falk, C., Friedler, S. A., Rybeck, G., Scheidegger, C., Smith, B., & Venkatasubramanian, S. (2016) · arXiv
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MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
Fu, C., Chen, P., Shen, Y., Qin, Y., Zhang, M., Lin, X., Yang, J., Zheng, X., Li, K., Sun, X., et al. (2023) · arXiv
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EvoTrustRAG: Evolution-Aware Conflict Attribution and Evidence Handling for Reliable Retrieval-Augmented Generation
Nie, X., Li, H., Wu, S., Fan, W., Song, Q., & Jiang, W. (2026) · arXiv
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Learning Agile Quadrotor Flight in the Real World
Ren, Y., Zhu, Z., Xing, J., & Scaramuzza, D. (2026) · arXiv
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Impact of COVID 19 on Doctoral and Early Career Researchers
Byrom, N., & Metcalfe, J. (2021) · figshare
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Is Stack Overflow Obsolete? An Empirical Study of the Characteristics of ChatGPT Answers to Stack Overflow Questions
Kabir, S., Udo-Imeh, D. N., Kou, B., & Zhang, T. (2023) · arXiv
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The Surveillance AI Pipeline
Kalluri, P. R., Agnew, W., Cheng, M., Owens, K., Soldaini, L., & Birhane, A. (2023) · arXiv
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EcologicalNetworks.jl - analysing ecological networks of species interactions
Poisot, T., Bélisle, Z., Hoebeke, L., Stock, M., & Szefer, P. (2019) · Zenodo
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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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Glacial features of the Milan, Berlin, and Shelburne map areas of northern New Hampshire
Gerath, R. F. (1978) · McGill University
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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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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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What shapes feature representations? Exploring datasets, architectures, and training
Hermann, K. L., & Lampinen, A. K. (2020) · arXiv
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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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