NeurIPS

Adversarial Sample-Based Approach for Tighter Privacy Auditing in Final Model-Only Scenarios

Sangyeon Yoon, Wonje Jeung, Albert No

Comments 10 pages, NeurIPS (SFLLM Workshop)

Span-Based Optimal Sample Complexity for Weakly Communicating and General Average Reward MDPs

Matthew Zurek, Yudong Chen

Comments Revision adds Theorem 3 on the difficulty of estimating the span of the optimal bias. arXiv admin note: text overlap with arXiv:2311.13469

Journal ref Conference on Neural Information Processing Systems (NeurIPS), 2024

Initializing Services in Interactive ML Systems for Diverse Users

Avinandan Bose, Mihaela Curmei, Daniel L. Jiang, Jamie Morgenstern, Sarah Dean, Lillian J. Ratliff, Maryam Fazel

Comments 38th Conference on Neural Information Processing Systems (NeurIPS 2024)

DU-Shapley: A Shapley Value Proxy for Efficient Dataset Valuation

Felipe Garrido-Lucero, Benjamin Heymann, Maxime Vono, Patrick Loiseau, Vianney Perchet

Comments 22 pages

Journal ref https://proceedings.neurips.cc/paper_files/paper/2024/hash/03cd3cf3f74d4f9ce5958de269960884-Abstract-Conference.html

Fast Projection onto the Capped Simplex with Applications to Sparse Regression in Bioinformatics

Andersen Ang, Jianzhu Ma, Nianjun Liu, Kun Huang, Yijie Wang

Comments 12 pages, 5 figures

Journal ref Advances in Neural Information Processing Systems 2021

The Well: a Large-Scale Collection of Diverse Physics Simulations for Machine Learning

Ruben Ohana, Michael McCabe, Lucas Meyer, Rudy Morel, Fruzsina J. Agocs, Miguel Beneitez, Marsha Berger, Blakesley Burkhart, Keaton Burns, Stuart B. Dalziel, Drummond B. Fielding, Daniel Fortunato, Jared A. Goldberg, Keiya Hirashima, Yan-Fei Jiang, Rich R. Kerswell, Suryanarayana Maddu, Jonah Miller, Payel Mukhopadhyay, Stefan S. Nixon, Jeff Shen, Romain Watteaux, Bruno Régaldo-Saint Blancard, François Rozet, Liam H. Parker, Miles Cranmer, Shirley Ho

Comments 38th Conference on Neural Information Processing Systems (NeurIPS 2024) Track on Datasets and Benchmarks

Coevolving with the Other You: Fine-Tuning LLM with Sequential Cooperative Multi-Agent Reinforcement Learning

Hao Ma, Tianyi Hu, Zhiqiang Pu, Boyin Liu, Xiaolin Ai, Yanyan Liang, Min Chen

Comments Accepted by NeurIPS '24

On Convergence of Adam for Stochastic Optimization under Relaxed Assumptions

Yusu Hong, Junhong Lin

Comments NeurIPS 2024

Your Diffusion Model is Secretly a Certifiably Robust Classifier

Huanran Chen, Yinpeng Dong, Shitong Shao, Zhongkai Hao, Xiao Yang, Hang Su, Jun Zhu

Comments Accepted by NeurIPS 2024. Also named as "Diffusion Models are Certifiably Robust Classifiers"

Adversarial Prompt Evaluation: Systematic Benchmarking of Guardrails Against Prompt Input Attacks on LLMs

Giulio Zizzo, Giandomenico Cornacchia, Kieran Fraser, Muhammad Zaid Hameed, Ambrish Rawat, Beat Buesser, Mark Purcell, Pin-Yu Chen, Prasanna Sattigeri, Kush Varshney

Comments NeurIPS 2024, Safe Generative AI Workshop

Measuring AI agent autonomy: Towards a scalable approach with code inspection

Peter Cihon, Merlin Stein, Gagan Bansal, Sam Manning, Kevin Xu

Comments NeurIPS Socially Responsible Language Modelling Research (SoLaR) Workshop 2024

Provable Partially Observable Reinforcement Learning with Privileged Information

Yang Cai, Xiangyu Liu, Argyris Oikonomou, Kaiqing Zhang

Comments This paper has been accepted to 2024 Conference on Neural Information Processing Systems (NeurIPS 2024)

DeepInteraction++: Multi-Modality Interaction for Autonomous Driving

Zeyu Yang, Nan Song, Wei Li, Xiatian Zhu, Li Zhang, Philip H. S. Torr

Comments Journal extension of NeurIPS 2022. arXiv admin note: text overlap with arXiv:2208.11112

Data Attribution for Text-to-Image Models by Unlearning Synthesized Images

Sheng-Yu Wang, Aaron Hertzmann, Alexei A. Efros, Jun-Yan Zhu, Richard Zhang

Comments NeurIPS 2024 camera ready version. Project page: https://peterwang512.github.io/AttributeByUnlearning Code: https://github.com/PeterWang512/AttributeByUnlearning

LOVA3: Learning to Visual Question Answering, Asking and Assessment

Henry Hengyuan Zhao, Pan Zhou, Difei Gao, Zechen Bai, Mike Zheng Shou

Comments NeurIPS 2024. The code is available at https://github.com/showlab/LOVA3

Personalized Instance-based Navigation Toward User-Specific Objects in Realistic Environments

Luca Barsellotti, Roberto Bigazzi, Marcella Cornia, Lorenzo Baraldi, Rita Cucchiara

Comments NeurIPS 2024 Datasets and Benchmarks Track. Project page: https://aimagelab.github.io/pin/

UNION: Unsupervised 3D Object Detection using Object Appearance-based Pseudo-Classes

Ted Lentsch, Holger Caesar, Dariu M. Gavrila

Comments NeurIPS 2024

E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation

Boqian Wu, Qiao Xiao, Shiwei Liu, Lu Yin, Mykola Pechenizkiy, Decebal Constantin Mocanu, Maurice Van Keulen, Elena Mocanu

Comments Accepted at NeurIPS 2024

Combining Statistical Depth and Fermat Distance for Uncertainty Quantification

Hai-Vy Nguyen, Fabrice Gamboa, Reda Chhaibi, Sixin Zhang, Serge Gratton, Thierry Giaccone

Comments 12 pages

Journal ref Advances in Neural Information Processing Systems (NeurIPS), Vol 37, 30207--30229, 2024

Escaping from the Barren Plateau via Gaussian Initializations in Deep Variational Quantum Circuits

Kaining Zhang, Liu Liu, Min-Hsiu Hsieh, Dacheng Tao

Comments Accepted by the Thirty-Sixth Conference on Neural Information Processing Systems (NeurIPS 2022)

Journal ref Advances in Neural Information Processing Systems, 2022, 35: 18612-18627

Efficient Alignment of Large Language Models via Data Sampling

Amrit Khera, Rajat Ghosh, Debojyoti Dutta

Comments Original work accepted at NeurIPS Efficient Natural Language and Speech Processing Workshop. PMLR, 2024. Experiments with a larger model from a different family, Llama-30B have been added to the appendix for generalizability

From Instance Training to Instruction Learning: Task Adapters Generation from Instructions

Huanxuan Liao, Shizhu He, Yao Xu, Yuanzhe Zhang, Yanchao Hao, Shengping Liu, Kang Liu, Jun Zhao

Comments accepted to NeurIPS 2024

GraphMorph: Tubular Structure Extraction by Morphing Predicted Graphs

Zhao Zhang, Ziwei Zhao, Dong Wang, Liwei Wang

Comments NeurIPS 2024

Leveraging Contrastive Learning for Enhanced Node Representations in Tokenized Graph Transformers

Jinsong Chen, Hanpeng Liu, John E. Hopcroft, Kun He

Comments Accepted by NeurIPS 2024

A Simple and Adaptive Learning Rate for FTRL in Online Learning with Minimax Regret of $Θ(T^{2/3})$ and its Application to Best-of-Both-Worlds

Taira Tsuchiya, Shinji Ito

Comments Published version in Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 38 pages

Fast Rates in Stochastic Online Convex Optimization by Exploiting the Curvature of Feasible Sets

Taira Tsuchiya, Shinji Ito

Comments Published version in Advances in Neural Information Processing Systems 37 (NeurIPS 2024), 25 pages

Learning to be Smooth: An End-to-End Differentiable Particle Smoother

Ali Younis, Erik B. Sudderth

Comments The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)

Evaluating the Prompt Steerability of Large Language Models

Erik Miehling, Michael Desmond, Karthikeyan Natesan Ramamurthy, Elizabeth M. Daly, Pierre Dognin, Jesus Rios, Djallel Bouneffouf, Miao Liu

Comments Short version appeared at the Pluralistic Alignment workshop at NeurIPS 2024; extended version appeared at NAACL 2025

An Information Theoretic Perspective on Conformal Prediction

Alvaro H. C. Correia, Fabio Valerio Massoli, Christos Louizos, Arash Behboodi

Comments Please refer to https://papers.nips.cc/paper_files/paper/2024/hash/b6fa3ed9624c184bd73e435123bd576a-Abstract-Conference.html for the version published in the NeurIPS 2024 proceedings

Journal ref Advances in Neural Information Processing Systems 37 (NeurIPS 2024)

Segment Any Change

Zhuo Zheng, Yanfei Zhong, Liangpei Zhang, Stefano Ermon

Comments NeurIPS 2024