Jesse Roberts

Jesse Roberts

Native Tennesseean Researching AI, Language, and Robotics

Publications

You can also find my articles on my Google Scholar profile.

Textbook

Jesse Roberts, 2024, Introduction to PLC Automation, PDF Version

Selected Publication

How Powerful are Decoder-Only Transformer Neural Models?

Published in IJCNN '24, 2024

This is the first work to directly address the Turing completeness of the underlying technology employed in GPT-x as past work has focused on the more expressive, full auto-encoder transformer architecture. From this theoretical analysis, we show that the sparsity/compressibility of the word embedding is an important consideration for Turing completeness to hold.

Recommended citation: Roberts, Jesse. "How Powerful are Decoder-Only Transformer Neural Models?" arXiv preprint arXiv:2305.17026 (2023). https://arxiv.org/abs/2305.17026

Using Artificial Populations to Study Psychological Phenomena in Neural Models

Published in AAAI '24, 2024

We leverage work in uncertainty estimation in a novel approach to efficiently construct experimental populations. The resultant tool, PopulationLM, has been made open source. We provide theoretical grounding in the uncertainty estimation literature and motivation from current cognitive work regarding language models.

Recommended citation: Roberts, Jesse, et al. 'Using Artificial Populations to Study Psychological Phenomena in Neural Models.' Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 38. No. 17. 2024. https://arxiv.org/abs/2308.08032

All Publications

  1. Umphrey, R., Roberts, J., & Roberts, L. (2024). Investigating Expert-in-the-Loop LLM Discourse Patterns for Ancient Intertextual Analysis. arXiv preprint arXiv:2409.01882.
  2. Moore, K., Roberts, J., Pham, T., & Fisher, D. (2024). Reasoning Beyond Bias: A Study on Counterfactual Prompting and Chain of Thought Reasoning. arXiv preprint arXiv:2408.08651.
  3. Roberts, J. (2024). A Theoretical & Empirical Analysis of Transformer Language Model Behavior. .
  4. Roberts, J., Roberts, L., & Reed, A. (2024). Supporting the Digital Autonomy of Elders Through LLM Assistance. arXiv preprint arXiv:2407.15695.
  5. Roberts, J., Moore, K., Pham, T., Ewaleifoh, O., & Fisher, D. (2024). Large Language Model Recall Uncertainty is Modulated by the Fan Effect. arXiv preprint arXiv:2407.06349.
  6. Moore, K., Roberts, J., Pham, T., Ewaleifoh, O., & Fisher, D. (2024). The Base-Rate Effect on LLM Benchmark Performance: Disambiguating Test-Taking Strategies from Benchmark Performance. arXiv preprint arXiv:2406.11634.
  7. Roberts, J. (2024). Introduction to PLC Automation. .
  8. Roberts, J., Moore, K., & Fisher, D. (2024). Do Large Language Models Learn Human-Like Strategic Preferences?. arXiv preprint arXiv:2404.08710.
  9. Roberts, J. (2024). Do Large Language Models Learn to Human-Like Learn?. Proceedings of the AAAI 2024 Spring Symposium Series.
  10. Roberts, J., Moore, K., Wilenzick, D., & Fisher, D. (2024). Using Artificial Populations to Study Psychological Phenomena in Neural Models. Proceedings of the AAAI Conference on Artificial Intelligence.
  11. Roberts, J. (2023). Rock Climbing Route Generation and Grading as Computational Creativity. arXiv preprint arXiv:2311.02211.
  12. Roberts, J. (2023). How Powerful are Decoder-Only Transformer Neural Models?. arXiv preprint arXiv:2305.17026.
  13. Roberts, J. (2021). Finding an Equilibrium in the Traveler's Dilemma with Fuzzy Weak Domination. 2021 IEEE Conference on Games (CoG).
  14. Roberts, J. & Fisher, D. (2020). pReview: The artificially intelligent conference reviewer. 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA).
  15. Roberts, J. & Fisher, D. (2020). Extending the Philosophy of Computational Criticism.. ICCC.
  16. Roberts, J. & Talbert, D. (2019). Biologically Extending the Gen 2 ANN Model. The Thirty-Second International Flairs Conference.
  17. Roberts, J. & Bhattacharya, I. (2017). Improving any arbitrary MPPT hill climber with ANN estimations. 2017 IEEE 44th Photovoltaic Specialist Conference (PVSC).
  18. Roberts, J. (2017). MNFIS+; or, a Better Hybrid Heuristic Maximum Power Point Tracker. .
  19. Roberts, J. & Bhattacharya, I. (2016). MNFIS and other soft computing based MPPT techniques: A comparative analysis. 2016 IEEE 43rd Photovoltaic Specialists Conference (PVSC).

Venues

Conferences: AAAI, IAAI, IJCAI, AISTATS, ICML, ICLR, NeurIPS, EMNLP, CoNLL, CogSci, ICCC, AIES, KDD, ICANN, IJCNN, IEEE CoG, FLAIRs, NLLP

Journals: AI Magazine, IEEE Transactions on Neural Networks, Frontiers in Theory of Neural Networks, PLOS Complex Systems