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NeurIPS 2024

2024 Accepted Papers:

  1. A Textbook Remedy for Domain Shifts: Knowledge Priors for Medical Image Analysis (Spotlight)
    • Yue Yang, Mona Gandhi, Yufei Wang, Yifan Wu, Michael S Yao, Chris Callison-Burch, James Gee, Mark Yatskar
  2. AR-Pro: Anomaly Explanation and Repair with Formal Properties
    • Xiayan Ji, Anton Xue, Eric Wong, Oleg Sokolsky, Insup Lee
  3. Data-Efficient Learning with Neural Programs
    • Alaia Solko-Breslin, Seewon Choi, Ziyang Li, Neelay Velingker, Rajeev Alur, Mayur Naik, Eric Wong
  4. Deep Learning in Medical Image Registration: Magic or Mirage?
    • Rohit Jena, Deeksha Sethi, Pratik Chaudhari, James C Gee
  5. Evolution of Statistical Induction Heads: In-Context Learning Markov Chains
    • Benjamin L. Edelman, Ezra Edelman, Surbhi Goel, Eran Malach, Nikolaos Tsilivis
  6. Fairness-Aware Estimation of Graphical Models
    • Zhouping Zhou, Davoud Ataee Tarzanagh , Bojian Hou, Qi Long, Li Shen
  7. Flex-MoE: Addressing Missing Modalities in Alzheimer’s Disease with Flexible Mixture-of-Experts (Spotlight)
    • Sukwon Yun, Inyoung Choi, Jie Peng, Yangfan Wu, Jingxuan Bao, Qiyiwen Zhang, Jiayi Xin, Qi Long, Tianlong Chen
  8. Generative Adversarial Model-Based Optimization via Source Critic Regularization
    • Michael S. Yao, Yimeng Zeng, Hamsa Bastani, Jacob Gardner, James C. Gee, Osbert Bastani
  9. Improving Equivariant Model Training via Constraint Relaxation
    • Stefanos Pertigkiozoglou, Evangelos Chatzipantazis, Shubhendu Trivedi, Kostas Daniilidis
  10. JailbreakBench: An Open Robustness Benchmark for Jailbreaking Large Language Models
    • Patrick Chao, Edoardo Debenedetti, Alexander Robey, Maksym Andriushchenko, Francesco Croce, Vikash Sehwag, Edgar Dobriban, Nicolas Flammarion, George J. Pappas, Florian Tramèr, Hamed Hassani, Eric Wong
  11. Length Optimization in conformal Prediction
    • Shayan Kiyani, George Pappas, Hamed Hassani
  12. Neural Decoding from Stereotactic EEG: Accounting for Electrode Variability across Subjects
    • Georgios Mentzelopoulos, Evangelos Chatzipantazis, Ashwin G Ramayya, Michelle Hedlund, Vivek Buch, Kostas Daniilidis, Konrad Kording, Flavia Vitale
  13. One-Shot Safety Alignment for Large Language Models via Optimal Dualization (Spotlight)
    • Huang Xinmeng, Shuo Li, Edgar Dobriban, Osbert Bastani, Hamed Hassani, Dongsheng Ding
  14. Oracle-Efficient Reinforcement Learning for Max Value Ensembles
    • Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell
  15. PaCE: Parsimonious Concept Engineering for Large Language Models
    • Jinqi Luo, Tianjiao Ding, Kwan Ho Ryan Chan, Darshan Thaker, Aditya Chattopadhyay, Chris Callison-Burch, René Vidal
  16. Prospective Learning: Principled Extrapolation to the Future
    • Ashwin De Silva, Rahul Ramesh, Rubing Yang, Joshua T. Vogelstein, Pratik Chaudhari
  17. Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable
    • Martin Bertran, Shuai Tang, Michael Kearns, Jamie Morgenstern, Aaron Roth, Zhiwei Steven Wu
  18. SE(3) Equivariant Ray Embeddings for Implicit Multi-View Depth Estimation
    • Yinshuang Xu, Dian Chen, Katherine Liu, Sergey Zakharov, Rares Andrei Ambrus, Kostas Daniilidis, Vitor Campagnolo Guizilini
  19. Tolerant Algorithms for Learning with Arbitrary Covariate Shift (Spotlight)
    • Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan
  20. Toward Efficient Inference for Mixtures of Experts
    • Haiyang Huang, Newsha Ardalani, Anna Sun, Liu Ke, Shruti Bhosale, Hsien-Hsin S. Lee, Carole-Jean Wu, Benjamin Lee
  21. Turning Indirect Knowledge into Direct Demonstrations for Computer Agents at Scale
    • Tianyue Ou, Frank F. Xu, Aman Madaan, Jiarui Liu, Robert Lo, Abishek Sridhar, Sudipta Sengupta, Dan Roth, Graham Neubig, Shuyan Zhou
  22. Visual Sketchpad: Sketching as a Visual Chain of Thought for Multimodal Language Models
    • Yushi Hu, Weijia Shi, Xingyu Fu, Dan Roth, Mari Ostendorf, Luke Zettlemoyer, Noah Smith, Ranjay Krishna