NeurIPS

Category-Extensible Out-of-Distribution Detection via Hierarchical Context Descriptions

Kai Liu, Zhihang Fu, Chao Chen, Sheng Jin, Ze Chen, Mingyuan Tao, Rongxin Jiang, Jieping Ye

Comments Accepted by 37th Conference on Neural Information Processing Systems (NeurIPS 2023). Code is available at https://github.com/alibaba/catex

How to Boost Any Loss Function

Richard Nock, Yishay Mansour

Comments NeurIPS'24

IRCAN: Mitigating Knowledge Conflicts in LLM Generation via Identifying and Reweighting Context-Aware Neurons

Dan Shi, Renren Jin, Tianhao Shen, Weilong Dong, Xinwei Wu, Deyi Xiong

Comments NeurIPS 2024

InfiBench: Evaluating the Question-Answering Capabilities of Code Large Language Models

Linyi Li, Shijie Geng, Zhenwen Li, Yibo He, Hao Yu, Ziyue Hua, Guanghan Ning, Siwei Wang, Tao Xie, Hongxia Yang

Comments 31 pages. Appear at NeurIPS 2024 Datasets and Benchmarks track. Project website: https://infi-coder.github.io/infibench

Generative Forests

Richard Nock, Mathieu Guillame-Bert

Comments NeurIPS'24

Transformer-based Time-Series Biomarker Discovery for COPD Diagnosis

Soham Gadgil, Joshua Galanter, Mohammadreza Negahdar

Comments Accepted as a workshop paper to NeurIPS 2024

RNA-GPT: Multimodal Generative System for RNA Sequence Understanding

Yijia Xiao, Edward Sun, Yiqiao Jin, Wei Wang

Comments Machine Learning for Structural Biology Workshop, NeurIPS 2024

4D Gaussian Splatting in the Wild with Uncertainty-Aware Regularization

Mijeong Kim, Jongwoo Lim, Bohyung Han

Comments NeurIPS 2024

Rethinking CyberSecEval: An LLM-Aided Approach to Evaluation Critique

Suhas Hariharan, Zainab Ali Majid, Jaime Raldua Veuthey, Jacob Haimes

Comments NeurIPS 2024, 2 pages

Dynamic Subset Tuning: Expanding the Operational Range of Parameter-Efficient Training for Large Language Models

Felix Stahlberg, Jared Lichtarge, Shankar Kumar

Comments NeurIPS 2024 Workshop on Adaptive Foundation Models

DeepUQ: Assessing the Aleatoric Uncertainties from two Deep Learning Methods

Rebecca Nevin, Aleksandra Ćiprijanović, Brian D. Nord

Comments Accepted to the Machine Learning for Physical Sciences workshop at NeurIPS 2024; 11 pages, 2 figures, 2 tables

Learning Locally Adaptive Metrics that Enhance Structural Representation with $\texttt{LAMINAR}$

Christian Kleiber, William H. Oliver, Tobias Buck

Comments Accepted to the NeurIPS 2024 Machine Learning and the Physical Sciences workshop. 6 pages, 6 figures

LSH-MoE: Communication-efficient MoE Training via Locality-Sensitive Hashing

Xiaonan Nie, Qibin Liu, Fangcheng Fu, Shenhan Zhu, Xupeng Miao, Xiaoyang Li, Yang Zhang, Shouda Liu, Bin Cui

Comments Accepted by NeurIPS 2024

Developing a Foundation Model for Predicting Material Failure

Agnese Marcato, Javier E. Santos, Aleksandra Pachalieva, Kai Gao, Ryley Hill, Esteban Rougier, Qinjun Kang, Jeffrey Hyman, Abigail Hunter, Janel Chua, Earl Lawrence, Hari Viswanathan, Daniel O'Malley

Comments Accepted at NeurIPS 2024 "Foundation Models for Science: Progress, Opportunities, and Challenges" Workshop

Brain Treebank: Large-scale intracranial recordings from naturalistic language stimuli

Christopher Wang, Adam Uri Yaari, Aaditya K Singh, Vighnesh Subramaniam, Dana Rosenfarb, Jan DeWitt, Pranav Misra, Joseph R. Madsen, Scellig Stone, Gabriel Kreiman, Boris Katz, Ignacio Cases, Andrei Barbu

Comments 36 pages, 17 figures; Accepted at NeurIPS Dataset and Benchmarks 2024

Modeling variable guide efficiency in pooled CRISPR screens with ContrastiveVI+

Ethan Weinberger, Ryan Conrad, Tal Ashuach

Comments 15 pages, 4 figures, will be included in the AIDrugX workshop in Neurips 2024

Exact, Tractable Gauss-Newton Optimization in Deep Reversible Architectures Reveal Poor Generalization

Davide Buffelli, Jamie McGowan, Wangkun Xu, Alexandru Cioba, Da-shan Shiu, Guillaume Hennequin, Alberto Bernacchia

Comments Accepted at NeurIPS 2024

Doubly Mild Generalization for Offline Reinforcement Learning

Yixiu Mao, Qi Wang, Yun Qu, Yuhang Jiang, Xiangyang Ji

Comments Accepted to NeurIPS 2024

HairDiffusion: Vivid Multi-Colored Hair Editing via Latent Diffusion

Yu Zeng, Yang Zhang, Jiachen Liu, Linlin Shen, Kaijun Deng, Weizhao He, Jinbao Wang

Journal ref NeurIPS 2024, 38th Annual Conference on Neural Information Processing Systems

Continual Learning in the Frequency Domain

Ruiqi Liu, Boyu Diao, Libo Huang, Zijia An, Zhulin An, Yongjun Xu

Comments Accepted by NeurIPS 2024

Log-concave Sampling from a Convex Body with a Barrier: a Robust and Unified Dikin Walk

Yuzhou Gu, Nikki Lijing Kuang, Yi-An Ma, Zhao Song, Lichen Zhang

Comments NeurIPS 2024

From Text to Treatment Effects: A Meta-Learning Approach to Handling Text-Based Confounding

Henri Arno, Paloma Rabaey, Thomas Demeester

Comments Presented at the NeurIPS 2024 Workshop on Causal Representation Learning

HumanVLA: Towards Vision-Language Directed Object Rearrangement by Physical Humanoid

Xinyu Xu, Yizheng Zhang, Yong-Lu Li, Lei Han, Cewu Lu

Comments NeurIPS 2024

Probabilistic Emulation of a Global Climate Model with Spherical DYffusion

Salva Rühling Cachay, Brian Henn, Oliver Watt-Meyer, Christopher S. Bretherton, Rose Yu

Comments NeurIPS 2024; Code is available at https://github.com/Rose-STL-Lab/spherical-dyffusion

Implicit Bias of Mirror Flow on Separable Data

Scott Pesme, Radu-Alexandru Dragomir, Nicolas Flammarion

Comments Neurips camera ready. Minor changes from the previous versions. Mainly added full iterate trajectories (Figure 4)

ConMe: Rethinking Evaluation of Compositional Reasoning for Modern VLMs

Irene Huang, Wei Lin, M. Jehanzeb Mirza, Jacob A. Hansen, Sivan Doveh, Victor Ion Butoi, Roei Herzig, Assaf Arbelle, Hilde Kuehne, Trevor Darrell, Chuang Gan, Aude Oliva, Rogerio Feris, Leonid Karlinsky

Comments NeurIPS 2024 Camera Ready

AudioMarkBench: Benchmarking Robustness of Audio Watermarking

Hongbin Liu, Moyang Guo, Zhengyuan Jiang, Lun Wang, Neil Zhenqiang Gong

Comments To appear in NeurIPS Datasets and Benchmarks, 2024

On the Effects of Data Scale on UI Control Agents

Wei Li, William Bishop, Alice Li, Chris Rawles, Folawiyo Campbell-Ajala, Divya Tyamagundlu, Oriana Riva

Comments NeurIPS 2024 (Datasets and Benchmarks)

Divide-and-Conquer Posterior Sampling for Denoising Diffusion Priors

Yazid Janati, Badr Moufad, Alain Durmus, Eric Moulines, Jimmy Olsson

Comments Updated version with significant updates

Journal ref NeurIPS 2024

Super Consistency of Neural Network Landscapes and Learning Rate Transfer

Lorenzo Noci, Alexandru Meterez, Thomas Hofmann, Antonio Orvieto

Comments The paper has been accepted at Neurips 2024. This is a revised version of the paper previously titled "Why do Learning Rates Transfer? Reconciling Optimization and Scaling Limits for Deep Learning"