Justin Lovelace

Ph.D. Candidate in Computer Science at Cornell University.

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Gates Hall

Cornell University

Ithaca, NY

My current research focuses on developing diffusion models for language and speech generation, aiming to advance the capabilities and controllability of generative models in these domains. I am fortunate to be advised by Prof. Kilian Q. Weinberger.

Previously, I earned my M.S. in Language Technologies from Carnegie Mellon University, where I conducted NLP research under the advisement of Dr. Carolyn Rosé. I completed my undergraduate studies at Texas A&M University, where I engaged in Clinical NLP research with Dr. Bobak Mortazavi.

selected publications

  1. COLM
    Stop-Think-AutoRegress: Language Modeling with Latent Diffusion Planning
    Justin Lovelace, Christian Belardi, Sofian Zalouk, and 3 more authors
    Conference on Language Modeling (COLM), 2025
  2. Preprint
    SpeechOp: Inference-Time Task Composition for Generative Speech Processing
    Justin Lovelace, Rithesh Kumar, Jiaqi Su, and 3 more authors
    ArXiv Preprint, 2025
  3. Preprint
    Pre-training Limited Memory Language Models with Internal and External Knowledge
    Linxi Zhao, Sofian Zalouk, Christian Belardi, and 5 more authors
    ArXiv Preprint, 2025
  4. ACL Findings
    Diffusion Guided Language Modeling
    Justin Lovelace, Varsha Kishore, Yiwei Chen, and 1 more author
    Findings of the Annual Meeting of the Association for Computational Linguistics (Findings of ACL), 2024
  5. NeurIPS
    Latent Diffusion for Language Generation
    Justin Lovelace, Varsha Kishore, Chao Wan, and 2 more authors
    Conference on Neural Information Processing Systems (NeurIPS), 2023