NeurIPS

Inductive Bias for Emergent Communication in a Continuous Setting

John Isak Fjellvang Villanger, Troels Arnfred Bojesen

Comments NIPS 2023 Preprint. 12 pages, 5 figures, 3 tables

Journal ref (2024) Proceedings of the 5th Northern Lights Deep Learning Conference (NLDL), in Proceedings of Machine Learning Research 233:235-243

NewTerm: Benchmarking Real-Time New Terms for Large Language Models with Annual Updates

Hexuan Deng, Wenxiang Jiao, Xuebo Liu, Min Zhang, Zhaopeng Tu

Comments Accepted to NeurIPS 2024 Datasets and Benchmarks Track

Graph-based Uncertainty Metrics for Long-form Language Model Outputs

Mingjian Jiang, Yangjun Ruan, Prasanna Sattigeri, Salim Roukos, Tatsunori Hashimoto

Comments Accepted as a Spotlight paper at NeurIPS 2024

KD-LoRA: A Hybrid Approach to Efficient Fine-Tuning with LoRA and Knowledge Distillation

Rambod Azimi, Rishav Rishav, Marek Teichmann, Samira Ebrahimi Kahou

Comments Accepted at 4th NeurIPS Efficient Natural Language and Speech Processing Workshop (ENLSP-IV 2024)

Task Confusion and Catastrophic Forgetting in Class-Incremental Learning: A Mathematical Framework for Discriminative and Generative Modelings

Milad Khademi Nori, Il-Min Kim

Comments 30 pages, 15 figures, Camera-Ready NeurIPS 2024

Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent Coding

Jiewen Yang, Yiqun Lin, Bin Pu, Xiaomeng Li

Comments Paper Accepted by NeurIPS 2024

ODRL: A Benchmark for Off-Dynamics Reinforcement Learning

Jiafei Lyu, Kang Xu, Jiacheng Xu, Mengbei Yan, Jingwen Yang, Zongzhang Zhang, Chenjia Bai, Zongqing Lu, Xiu Li

Comments NeurIPS 2024 D&B Track

Segmenting Watermarked Texts From Language Models

Xingchi Li, Guanxun Li, Xianyang Zhang

Comments 25 pages, 12 figures, 2 tables, NeurIPS 2024

Practical Bayesian Algorithm Execution via Posterior Sampling

Chu Xin Cheng, Raul Astudillo, Thomas Desautels, Yisong Yue

Comments Published as a conference paper at the 38th Conference on Neural Information Processing Systems (NeurIPS 2024)

Normal-GS: 3D Gaussian Splatting with Normal-Involved Rendering

Meng Wei, Qianyi Wu, Jianmin Zheng, Hamid Rezatofighi, Jianfei Cai

Comments 9 pages, 5 figures, accepted at NeurIPS 2024

Neural rendering enables dynamic tomography

Ivan Grega, William F. Whitney, Vikram S. Deshpande

Comments 24 pages, 14 figures. Submitted to NeurIPS 2024 ML4PS. For associated visualizations, see https://neural-xray.github.io/nerfxray

A Cosmic-Scale Benchmark for Symmetry-Preserving Data Processing

Julia Balla, Siddharth Mishra-Sharma, Carolina Cuesta-Lazaro, Tommi Jaakkola, Tess Smidt

Comments 19 pages, 3 figures; To appear at the NeurReps Workshop @ NeurIPS 2024

Referring Human Pose and Mask Estimation in the Wild

Bo Miao, Mingtao Feng, Zijie Wu, Mohammed Bennamoun, Yongsheng Gao, Ajmal Mian

Comments Accepted by NeurIPS 2024. https://github.com/bo-miao/RefHuman

What Factors Affect Multi-Modal In-Context Learning? An In-Depth Exploration

Libo Qin, Qiguang Chen, Hao Fei, Zhi Chen, Min Li, Wanxiang Che

Comments Accepted at NeurIPS 2024

Open-Vocabulary Object Detection via Language Hierarchy

Jiaxing Huang, Jingyi Zhang, Kai Jiang, Shijian Lu

Comments NeurIPS 2024 Camera Ready

Historical Test-time Prompt Tuning for Vision Foundation Models

Jingyi Zhang, Jiaxing Huang, Xiaoqin Zhang, Ling Shao, Shijian Lu

Comments NeurIPS 2024 Camera Ready

Harmony4D: A Video Dataset for In-The-Wild Close Human Interactions

Rawal Khirodkar, Jyun-Ting Song, Jinkun Cao, Zhengyi Luo, Kris Kitani

Comments NeurIPS 2024

Library Learning Doesn't: The Curious Case of the Single-Use "Library"

Ian Berlot-Attwell, Frank Rudzicz, Xujie Si

Comments 24 pages, 7 figures. Accepted to the 4th MATH-AI Workshop at NeurIPS'24

Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL

Andrew Wagenmaker, Kevin Huang, Liyiming Ke, Byron Boots, Kevin Jamieson, Abhishek Gupta

Comments NeurIPS 2024

Uncertainty-Penalized Direct Preference Optimization

Sam Houliston, Alizée Pace, Alexander Immer, Gunnar Rätsch

Comments Accepted at the NeurIPS 2024 FITML Workshop

Human-Object Interaction Detection Collaborated with Large Relation-driven Diffusion Models

Liulei Li, Wenguan Wang, Yi Yang

Comments NeurIPS 2024

AdaNeg: Adaptive Negative Proxy Guided OOD Detection with Vision-Language Models

Yabin Zhang, Lei Zhang

Comments NIPS 2024 Camera Ready, Codes are available at \url{https://github.com/YBZh/OpenOOD-VLM}

Near-Optimal Streaming Heavy-Tailed Statistical Estimation with Clipped SGD

Aniket Das, Dheeraj Nagaraj, Soumyabrata Pal, Arun Suggala, Prateek Varshney

Comments Accepted at NeurIPS 2024

Anatomical 3D Style Transfer Enabling Efficient Federated Learning with Extremely Low Communication Costs

Yuto Shibata, Yasunori Kudo, Yohei Sugawara

Comments Accepted by AIM-FM Workshop at NeurIPS 2024

Sample Efficient Bayesian Learning of Causal Graphs from Interventions

Zihan Zhou, Muhammad Qasim Elahi, Murat Kocaoglu

Comments To appear in Proceedings of NeurIPS 24

ResAD: A Simple Framework for Class Generalizable Anomaly Detection

Xincheng Yao, Zixin Chen, Chao Gao, Guangtao Zhai, Chongyang Zhang

Comments This paper was accepted as a spotlight papaer by NeurIPS 2024

SCube: Instant Large-Scale Scene Reconstruction using VoxSplats

Xuanchi Ren, Yifan Lu, Hanxue Liang, Zhangjie Wu, Huan Ling, Mike Chen, Sanja Fidler, Francis Williams, Jiahui Huang

Comments NeurIPS 2024. Project page: https://research.nvidia.com/labs/toronto-ai/scube/

Privacy without Noisy Gradients: Slicing Mechanism for Generative Model Training

Kristjan Greenewald, Yuancheng Yu, Hao Wang, Kai Xu

Comments accepted to Neurips 2024

Ensembling Finetuned Language Models for Text Classification

Sebastian Pineda Arango, Maciej Janowski, Lennart Purucker, Arber Zela, Frank Hutter, Josif Grabocka

Comments Workshop on Fine-Tuning in Modern Machine Learning @ NeurIPS 2024. arXiv admin note: text overlap with arXiv:2410.04520

Causal Order Discovery based on Monotonic SCMs

Ali Izadi, Martin Ester

Comments Accepted to the NeurIPS 2024 Workshop on Causal Representation Learning