Mark Johnson

About

Mark A. Johnson is a Professor of Biology and Vice Chair of the Department of Molecular Biology, Cell Biology and Biochemistry at Brown University. He received his B.S. in Biology from Wake Forest University in 1993 and completed his Ph.D. in Microbiology/Cell and Molecular Biology at Michigan State University in 2000, where he studied mRNA degradation. His postdoctoral work at The University of Chicago focused on plant reproductive development, supported by an NIH Ruth L. Kirchstein National Research Service Award. Since joining Brown University in September 2004, his laboratory has concentrated on understanding the molecular basis of cellular communication, particularly in flowering plant reproduction. His research uses pollen tube growth and guidance as a model system to explore mechanisms of invasive cell growth, cellular migration guidance, and cellular polarity determination, with a focus on the fertilization process in flowering plants. Johnson's work aims to elucidate the functions of genes involved in pollen tube growth and guidance, which are critical for plant fertilization and reproductive success.

Research topics

• Computer Science
• Artificial Intelligence
• Natural Language Processing
• Cognitive psychology
• Psychology
• Linguistics

Selected publications

• Sources of Hallucination by Large Language Models on Inference Tasks

  arXiv (Cornell University) · 2023-05-23 · 20 citations

  preprintOpen access

  Large Language Models (LLMs) are claimed to be capable of Natural Language Inference (NLI), necessary for applied tasks like question answering and summarization. We present a series of behavioral studies on several LLM families (LLaMA, GPT-3.5, and PaLM) which probe their behavior using controlled experiments. We establish two biases originating from pretraining which predict much of their behavior, and show that these are major sources of hallucination in generative LLMs. First, memorization a…

  PublisherOA PDFDOI

• Neural Rule-Execution Tracking Machine For Transformer-Based Text Generation

  arXiv (Cornell University) · 2021-07-27 · 4 citations

  preprintOpen access

  Sequence-to-Sequence (S2S) neural text generation models, especially the pre-trained ones (e.g., BART and T5), have exhibited compelling performance on various natural language generation tasks. However, the black-box nature of these models limits their application in tasks where specific rules (e.g., controllable constraints, prior knowledge) need to be executed. Previous works either design specific model structure (e.g., Copy Mechanism corresponding to the rule "the generated output should in…

  PublisherOA PDFDOI

• ECOL-R: Encouraging Copying in Novel Object Captioning with Reinforcement Learning

  arXiv (Cornell University) · 2021-01-25 · 3 citations

  preprintOpen accessSenior author

  Novel Object Captioning is a zero-shot Image Captioning task requiring describing objects not seen in the training captions, but for which information is available from external object detectors. The key challenge is to select and describe all salient detected novel objects in the input images. In this paper, we focus on this challenge and propose the ECOL-R model (Encouraging Copying of Object Labels with Reinforced Learning), a copy-augmented transformer model that is encouraged to accurately…

  PublisherOA PDFDOI

• Mastering the Craft of Data Synthesis for CodeLLMs

  2025-01-01 · 1 citations

  articleOpen access

  Meng Chen, Philip Arthur, Qianyu Feng, Cong Duy Vu Hoang, Yu-Heng Hong, Mahdi Kazemi Moghaddam, Omid Nezami, Duc Thien Nguyen, Gioacchino Tangari, Duy Vu, Thanh Vu, Mark Johnson, Krishnaram Kenthapadi, Don Dharmasiri, Long Duong, Yuan-Fang Li. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers). 2025.

  PublisherOA PDFDOI

• Game Streaming: Implications for Streamers and Game Creators

  Oxford Research Encyclopedia of Communication · 2024-11-19 · 1 citations

  reference-entry1st authorCorresponding

  Since the 2010s, the live streaming—live online video broadcast—of digital gaming has emerged as a significant Internet phenomenon. Millions of people stream their digital gaming for leisure, profit, or some combination, in the process often accumulating large communities of fans and followers who enjoy their streamed content, or simply broadcasting to small but often very dedicated handfuls of viewers. Game live streaming is also plagued by harassment and toxicity, but nevertheless continues to…

  PublisherDOI

Recent grants

• Collaborative research: Bayesian methods for learning and analyzing natural languages

  NSF · $160k · 2006–2010

Frequent coauthors

• Eugene Charniak

  52 shared

• Sharon Goldwater

  34 shared

• David McClosky

  Quanta Technology (United States)

  27 shared

• Mark Steedman

  24 shared

• Dat Quoc Nguyen

  19 shared

• Peter Anderson

  18 shared

• Mark Dras

  17 shared

• Omar Bakr

  Keck Hospital of USC

  17 shared

Education

• B.S., Biology

  Wake Forest University

  1993

• Ph.D., Microbiology/Cell and Molecular Biology

  Michigan State University

  2000

Awards & honors

• The Richard B. Salomon Faculty Research Awards, Brown Univer…

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• Weihan Lih-83
• Eric Morrowh-76
• Gary Wesselh-66