NeurIPS 2024
2024 Accepted Papers:
- 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
- AR-Pro: Anomaly Explanation and Repair with Formal Properties
- Xiayan Ji, Anton Xue, Eric Wong, Oleg Sokolsky, Insup Lee
- Data-Efficient Learning with Neural Programs
- Alaia Solko-Breslin, Seewon Choi, Ziyang Li, Neelay Velingker, Rajeev Alur, Mayur Naik, Eric Wong
- Deep Learning in Medical Image Registration: Magic or Mirage?
- Rohit Jena, Deeksha Sethi, Pratik Chaudhari, James C Gee
- Evolution of Statistical Induction Heads: In-Context Learning Markov Chains
- Benjamin L. Edelman, Ezra Edelman, Surbhi Goel, Eran Malach, Nikolaos Tsilivis
- Fairness-Aware Estimation of Graphical Models
- Zhouping Zhou, Davoud Ataee Tarzanagh , Bojian Hou, Qi Long, Li Shen
- 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
- Generative Adversarial Model-Based Optimization via Source Critic Regularization
- Michael S. Yao, Yimeng Zeng, Hamsa Bastani, Jacob Gardner, James C. Gee, Osbert Bastani
- Geometric Analysis of Nonlinear Manifold Clustering
- Nimita Shinde, Tianjiao Ding, Daniel Robinson, Rene Vidal
- Improving Equivariant Model Training via Constraint Relaxation
- Stefanos Pertigkiozoglou, Evangelos Chatzipantazis, Shubhendu Trivedi, Kostas Daniilidis
- 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
- Length Optimization in conformal Prediction
- Shayan Kiyani, George Pappas, Hamed Hassani
- 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
- One-Shot Safety Alignment for Large Language Models via Optimal Dualization (Spotlight)
- Huang Xinmeng, Shuo Li, Edgar Dobriban, Osbert Bastani, Hamed Hassani, Dongsheng Ding
- Oracle-Efficient Reinforcement Learning for Max Value Ensembles
- Marcel Hussing, Michael Kearns, Aaron Roth, Sikata Bela Sengupta, Jessica Sorrell
- 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
- Prospective Learning: Principled Extrapolation to the Future
- Ashwin De Silva, Rahul Ramesh, Rubing Yang, Joshua T. Vogelstein, Pratik Chaudhari
- Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable
- Martin Bertran, Shuai Tang, Michael Kearns, Jamie Morgenstern, Aaron Roth, Zhiwei Steven Wu
- 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
- Tolerant Algorithms for Learning with Arbitrary Covariate Shift (Spotlight)
- Surbhi Goel, Abhishek Shetty, Konstantinos Stavropoulos, Arsen Vasilyan
- 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
- 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
- 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