NeurIPS

Identifying and Solving Conditional Image Leakage in Image-to-Video Diffusion Model

Min Zhao, Hongzhou Zhu, Chendong Xiang, Kaiwen Zheng, Chongxuan Li, Jun Zhu

Comments NeurIPS 2024. Project page: https://cond-image-leak.github.io/

BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack

Yuri Kuratov, Aydar Bulatov, Petr Anokhin, Ivan Rodkin, Dmitry Sorokin, Artyom Sorokin, Mikhail Burtsev

Comments NeurIPS 2024 Datasets and Benchmarks Track

Bag of Tricks: Benchmarking of Jailbreak Attacks on LLMs

Zhao Xu, Fan Liu, Hao Liu

Comments Accepted by NeurIPS 2024

Testably Learning Polynomial Threshold Functions

Lucas Slot, Stefan Tiegel, Manuel Wiedmer

Comments Accepted to NeurIPS 2024. v2: Minor updates of exposition. 53 pages

Skill-aware Mutual Information Optimisation for Generalisation in Reinforcement Learning

Xuehui Yu, Mhairi Dunion, Xin Li, Stefano V. Albrecht

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

MMLU-Pro: A More Robust and Challenging Multi-Task Language Understanding Benchmark

Yubo Wang, Xueguang Ma, Ge Zhang, Yuansheng Ni, Abhranil Chandra, Shiguang Guo, Weiming Ren, Aaran Arulraj, Xuan He, Ziyan Jiang, Tianle Li, Max Ku, Kai Wang, Alex Zhuang, Rongqi Fan, Xiang Yue, Wenhu Chen

Comments This version has been accepted and published at NeurIPS 2024 Track Datasets and Benchmarks (Spotlight)

DC-Gaussian: Improving 3D Gaussian Splatting for Reflective Dash Cam Videos

Linhan Wang, Kai Cheng, Shuo Lei, Shengkun Wang, Wei Yin, Chenyang Lei, Xiaoxiao Long, Chang-Tien Lu

Comments 10 pages,7 figures;project page: https://linhanwang.github.io/dcgaussian/; Accepted to NeurIPS 2024

DMPlug: A Plug-in Method for Solving Inverse Problems with Diffusion Models

Hengkang Wang, Xu Zhang, Taihui Li, Yuxiang Wan, Tiancong Chen, Ju Sun

Comments Published in NeurIPS 2024 (https://openreview.net/forum?id=81IFFsfQUj)

DeTikZify: Synthesizing Graphics Programs for Scientific Figures and Sketches with TikZ

Jonas Belouadi, Simone Paolo Ponzetto, Steffen Eger

Comments Accepted at NeurIPS 2024 (spotlight); Project page: https://github.com/potamides/DeTikZify

Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models

Tuomas Kynkäänniemi, Miika Aittala, Tero Karras, Samuli Laine, Timo Aila, Jaakko Lehtinen

Comments NeurIPS 2024

From Similarity to Superiority: Channel Clustering for Time Series Forecasting

Jialin Chen, Jan Eric Lenssen, Aosong Feng, Weihua Hu, Matthias Fey, Leandros Tassiulas, Jure Leskovec, Rex Ying

Comments NeurIPS 2024

DeNetDM: Debiasing by Network Depth Modulation

Silpa Vadakkeeveetil Sreelatha, Adarsh Kappiyath, Abhra Chaudhuri, Anjan Dutta

Comments Camera-ready version : NeurIPS 2024, * indicates these authors contributed equally

Learning to Compute Gröbner Bases

Hiroshi Kera, Yuki Ishihara, Yuta Kambe, Tristan Vaccon, Kazuhiro Yokoyama

Comments NeurIPS 2024

Mind the spikes: Benign overfitting of kernels and neural networks in fixed dimension

Moritz Haas, David Holzmüller, Ulrike von Luxburg, Ingo Steinwart

Comments Compared to the NeurIPS version (v2), this version strengthens Assumption (K) from d/2<s<=3d/4 to d/2<s<3d/4 and corrects Lemma B.2 by posing additional assumptions. This does not affect any other statements. We provide Python code to reproduce all of our experimental results at https://github.com/moritzhaas/mind-the-spikes

Nearly Optimal Approximation of Matrix Functions by the Lanczos Method

Noah Amsel, Tyler Chen, Anne Greenbaum, Cameron Musco, Chris Musco

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

Galaxy Formation and Evolution via Phase-temporal Clustering with FuzzyCat $\circ$ AstroLink

William H. Oliver, Tobias Buck

Comments Accepted to the NeurIPS 2024 Machine Learning and the Physical Sciences workshop. 9 pages, 2 figures

Near-Optimal Dynamic Regret for Adversarial Linear Mixture MDPs

Long-Fei Li, Peng Zhao, Zhi-Hua Zhou

Comments NeurIPS 2024

Predictor-Corrector Enhanced Transformers with Exponential Moving Average Coefficient Learning

Bei Li, Tong Zheng, Rui Wang, Jiahao Liu, Qingyan Guo, Junliang Guo, Xu Tan, Tong Xiao, Jingbo Zhu, Jingang Wang, Xunliang Cai

Comments Accepted by NeurIPS 2024

Can Transformers Smell Like Humans?

Farzaneh Taleb, Miguel Vasco, Antônio H. Ribeiro, Mårten Björkman, Danica Kragic

Comments Spotlight paper at NeurIPS 2024

Hierarchical Orchestra of Policies

Thomas P Cannon, Özgür Simsek

Comments Accepted as a poster. NeurIPS IMOL

Controlling for Unobserved Confounding with Large Language Model Classification of Patient Smoking Status

Samuel Lee, Zach Wood-Doughty

Comments Advancements In Medical Foundation Models: Explainability, Robustness, Security, and Beyond (AIM-FM) at NeurIPS 2024

A scalable generative model for dynamical system reconstruction from neuroimaging data

Eric Volkmann, Alena Brändle, Daniel Durstewitz, Georgia Koppe

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

Membership Inference Attacks against Large Vision-Language Models

Zhan Li, Yongtao Wu, Yihang Chen, Francesco Tonin, Elias Abad Rocamora, Volkan Cevher

Comments NeurIPS 2024

The Unreasonable Effectiveness of LLMs for Query Optimization

Peter Akioyamen, Zixuan Yi, Ryan Marcus

Comments To appear in the Machine Learning for Systems Workshop at NeurIPS 2024

Continual Audio-Visual Sound Separation

Weiguo Pian, Yiyang Nan, Shijian Deng, Shentong Mo, Yunhui Guo, Yapeng Tian

Comments NeurIPS 2024

Test-Time Dynamic Image Fusion

Bing Cao, Yinan Xia, Yi Ding, Changqing Zhang, Qinghua Hu

Comments Accepted by NeurIPS 2024

On the Comparison between Multi-modal and Single-modal Contrastive Learning

Wei Huang, Andi Han, Yongqiang Chen, Yuan Cao, Zhiqiang Xu, Taiji Suzuki

Comments 51pages, 1 figure, 1 table

Journal ref NeurIPS 2024

Toward Robust Incomplete Multimodal Sentiment Analysis via Hierarchical Representation Learning

Mingcheng Li, Dingkang Yang, Yang Liu, Shunli Wang, Jiawei Chen, Shuaibing Wang, Jinjie Wei, Yue Jiang, Qingyao Xu, Xiaolu Hou, Mingyang Sun, Ziyun Qian, Dongliang Kou, Lihua Zhang

Comments Accepted by NeurIPS 2024

BrainBits: How Much of the Brain are Generative Reconstruction Methods Using?

David Mayo, Christopher Wang, Asa Harbin, Abdulrahman Alabdulkareem, Albert Eaton Shaw, Boris Katz, Andrei Barbu

Comments 23 pages, 16 figures, Accepted at NeurIPS 2024

Pricing and Competition for Generative AI

Rafid Mahmood

Comments NeurIPS 2024; 10 pages