publications

publications by categories in reversed chronological order. generated by jekyll-scholar.

  1. Language Models Don’t Know What You Want: Evaluating Personalization in Deep Research Needs Real Users
    Nishant Balepur, Malachi Hamada, Varsha Kishore, Sergey Feldman, Amanpreet Singh, and 5 more authors
    In Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) (ACL), 2026.
  2. Improving attributed long-form question answering with intent awareness
    Xinran Zhao, Aakanksha Naik, Jay DeYoung, Joseph Chee Chang, Jena Hwang, and 2 more authors
    In International Conference on Learning Representations (ICLR), 2026.
  3. Astabench: Rigorous benchmarking of ai agents with a scientific research suite
    Jonathan Bragg, Mike D’Arcy, Nishant Balepur, Dan Bareket, Bhavana Dalvi Mishra, and 6 more authors
    In International Conference on Learning Representations (ICLR), 2026.
  4. Dr tulu: Reinforcement learning with evolving rubrics for deep research
    Rulin Shao, Akari Asai, Shannon Zejiang Shen, Hamish Ivison, Varsha Kishore, and 6 more authors
    In International Conference on Machine Learning (ICML), 2026.
  5. Synthesizing scientific literature with retrieval-augmented language models
    Akari Asai, Jacqueline He, Rulin Shao, Weijia Shi, Amanpreet Singh, and 6 more authors
    In Nature , 2026.
  1. Reasonir: Training retrievers for reasoning tasks
    Rulin Shao, Rui Qiao, Varsha Kishore, Niklas Muennighoff, Xi Victoria Lin, and 6 more authors
    In Conference on Language Modelling , 2025.
  1. Diffusion Guided Language Modeling
    Justin Lovelace, Varsha Kishore, Yiwei Chen, and Kilian Weinberger
    In Findings of the Association for Computational Linguistics ACL 2024 Aug , 2024.
  1. Latent Diffusion for Language Generation
    Justin Lovelace, Varsha Kishore, Chao Wan, Eliot Shaktman, and Kilian Q Weinberger
    In Advances in Neural Information Processing Systems Aug (NeurIPS), 2023.
  2. IncDSI: Incrementally Updatable Document Retrieval
    Varsha Kishore, Chao Wan, Justin Lovelace, Yoav Artzi, and Kilian Q Weinberger
    In International Conference on Machine Learning Aug (ICML), 2023.
  3. Correction with Backtracking Reduces Hallucination in Summarization
    Zhenzhen Liu, Chao Wan, Varsha Kishore, Jin Zhou, Minmin Chen, and 1 more author
    In arXiv preprint arXiv:2310.16176 Aug , 2023.
  1. Learning Iterative Neural Optimizers for Image Steganography
    Varsha Kishore, Xiangyu Chen, and Kilian Q Weinberger
    In International Conference on Learning Representations Aug (ICLR), 2022.
  2. Harnessing interpretable and unsupervised machine learning to address big data from modern X-ray diffraction
    Jordan Venderley, Krishnanand Mallayya, Michael Matty, Matthew Krogstad, Jacob Ruff, and 6 more authors
    Proceedings of the National Academy of Sciences Aug , 2022.
  1. Fixed Neural Network Steganography: Train the images, not the network
    Varsha Kishore, Xiangyu Chen, Yan Wang, Boyi Li, and Kilian Q Weinberger
    In International Conference on Learning Representations Aug (ICLR), 2021.
  1. Bertscore: Evaluating text generation with bert
    Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi
    In International Conference on Learning Representations Aug (ICLR), 2019.