NeurIPS

XLand-MiniGrid: Scalable Meta-Reinforcement Learning Environments in JAX

Alexander Nikulin, Vladislav Kurenkov, Ilya Zisman, Artem Agarkov, Viacheslav Sinii, Sergey Kolesnikov

Comments Neural Information Processing Systems (NeurIPS 2024) Track on Datasets and Benchmarks. Source code at https://github.com/dunnolab/xland-minigrid

TransDreamer: Reinforcement Learning with Transformer World Models

Chang Chen, Yi-Fu Wu, Jaesik Yoon, Sungjin Ahn

Comments Deep RL Workshop NeurIPS 2021

Equivariant spatio-hemispherical networks for diffusion MRI deconvolution

Axel Elaldi, Guido Gerig, Neel Dey

Comments Accepted to NeurIPS 2024. 24 pages with 13 figures. Code available at https://github.com/AxelElaldi/fast-equivariant-deconv

Alien Recombination: Exploring Concept Blends Beyond Human Cognitive Availability in Visual Art

Alejandro Hernandez, Levin Brinkmann, Ignacio Serna, Nasim Rahaman, Hassan Abu Alhaija, Hiromu Yakura, Mar Canet Sola, Bernhard Schölkopf, Iyad Rahwan

Comments NeurIPS 2024 Workshop on Creativity & Generative AI, 13 pages, 11 figures

Generalizable Person Re-identification via Balancing Alignment and Uniformity

Yoonki Cho, Jaeyoon Kim, Woo Jae Kim, Junsik Jung, Sung-eui Yoon

Comments NeurIPS 2024

IKEA Manuals at Work: 4D Grounding of Assembly Instructions on Internet Videos

Yunong Liu, Cristobal Eyzaguirre, Manling Li, Shubh Khanna, Juan Carlos Niebles, Vineeth Ravi, Saumitra Mishra, Weiyu Liu, Jiajun Wu

Comments NeurIPS 2024 Datasets and Benchmarks Track

AMAGO-2: Breaking the Multi-Task Barrier in Meta-Reinforcement Learning with Transformers

Jake Grigsby, Justin Sasek, Samyak Parajuli, Daniel Adebi, Amy Zhang, Yuke Zhu

Comments NeurIPS 2024

Unveiling the Hidden: Online Vectorized HD Map Construction with Clip-Level Token Interaction and Propagation

Nayeon Kim, Hongje Seong, Daehyun Ji, Sujin Jang

Comments 18 pages, 9 figures, NeurIPS 2024

Maximization of Approximately Submodular Functions

Thibaut Horel, Yaron Singer

Comments 12 pages

Journal ref Advances in Neural Information Processing Systems 29, NeurIPS 2016, pp. 3045-3053

Evaluating Generative AI Systems is a Social Science Measurement Challenge

Hanna Wallach, Meera Desai, Nicholas Pangakis, A. Feder Cooper, Angelina Wang, Solon Barocas, Alexandra Chouldechova, Chad Atalla, Su Lin Blodgett, Emily Corvi, P. Alex Dow, Jean Garcia-Gathright, Alexandra Olteanu, Stefanie Reed, Emily Sheng, Dan Vann, Jennifer Wortman Vaughan, Matthew Vogel, Hannah Washington, Abigail Z. Jacobs

Comments NeurIPS 2024 Workshop on Evaluating Evaluations (EvalEval)

Constrained Diffusion with Trust Sampling

William Huang, Yifeng Jiang, Tom Van Wouwe, C. Karen Liu

Comments 18 pages, 6 figures, NeurIPS

Generating Compositional Scenes via Text-to-image RGBA Instance Generation

Alessandro Fontanella, Petru-Daniel Tudosiu, Yongxin Yang, Shifeng Zhang, Sarah Parisot

Comments NeurIPS 2024

MRI Parameter Mapping via Gaussian Mixture VAE: Breaking the Assumption of Independent Pixels

Moucheng Xu, Yukun Zhou, Tobias Goodwin-Allcock, Kimia Firoozabadi, Joseph Jacob, Daniel C. Alexander, Paddy J. Slator

Comments NeurIPS 2024 Workshop in Machine Learning and the Physical Sciences

ML$^2$Tuner: Efficient Code Tuning via Multi-Level Machine Learning Models

JooHyoung Cha, Munyoung Lee, Jinse Kwon, Jubin Lee, Jemin Lee, Yongin Kwon

Comments Accepted in NeurIPS 2024 workshop on Machine Learning for Systems, 12 pages, 5 figures

Can Generic LLMs Help Analyze Child-adult Interactions Involving Children with Autism in Clinical Observation?

Tiantian Feng, Anfeng Xu, Rimita Lahiri, Helen Tager-Flusberg, So Hyun Kim, Somer Bishop, Catherine Lord, Shrikanth Narayanan

Comments GenAI for Health Workshop, NeurIPS 2024

DEBUG-HD: Debugging TinyML models on-device using Hyper-Dimensional computing

Nikhil P Ghanathe, Steven J E Wilton

Comments Accepted at the Machine Learning for Systems Workshop at NeurIPS 2024

Pluralistic Alignment Over Time

Toryn Q. Klassen, Parand A. Alamdari, Sheila A. McIlraith

Comments Pluralistic Alignment Workshop at NeurIPS 2024

Drift-Resilient TabPFN: In-Context Learning Temporal Distribution Shifts on Tabular Data

Kai Helli, David Schnurr, Noah Hollmann, Samuel Müller, Frank Hutter

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

Being Considerate as a Pathway Towards Pluralistic Alignment for Agentic AI

Parand A. Alamdari, Toryn Q. Klassen, Rodrigo Toro Icarte, Sheila A. McIlraith

Comments Pluralistic Alignment Workshop at NeurIPS 2024

AmoebaLLM: Constructing Any-Shape Large Language Models for Efficient and Instant Deployment

Yonggan Fu, Zhongzhi Yu, Junwei Li, Jiayi Qian, Yongan Zhang, Xiangchi Yuan, Dachuan Shi, Roman Yakunin, Yingyan Celine Lin

Comments Accepted at NeurIPS 2024

Low-Rank Optimal Transport through Factor Relaxation with Latent Coupling

Peter Halmos, Xinhao Liu, Julian Gold, Benjamin J Raphael

Comments 53 pages, 13 figures, NeurIPS 2024. Comments welcome!

Chain of Alignment: Integrating Public Will with Expert Intelligence for Language Model Alignment

Andrew Konya, Aviv Ovadya, Kevin Feng, Quan Ze Chen, Lisa Schirch, Colin Irwin, Amy X. Zhang

Comments Pluralistic Alignment Workshop at NeurIPS 2024

Activating Self-Attention for Multi-Scene Absolute Pose Regression

Miso Lee, Jihwan Kim, Jae-Pil Heo

Comments Accepted to NeurIPS 2024

Visual Fourier Prompt Tuning

Runjia Zeng, Cheng Han, Qifan Wang, Chunshu Wu, Tong Geng, Lifu Huang, Ying Nian Wu, Dongfang Liu

Comments [NeurIPS 2024] Homepage: https://runjia.tech/vfpt_page/

ImOV3D: Learning Open-Vocabulary Point Clouds 3D Object Detection from Only 2D Images

Timing Yang, Yuanliang Ju, Li Yi

Comments Accepted by NeurIPS 2024. Code link https://github.com/yangtiming/ImOV3D

Journal ref NeurIPS 2024

Gaze-Assisted Medical Image Segmentation

Leila Khaertdinova, Ilya Pershin, Tatiana Shmykova, Bulat Ibragimov

Comments 16 pages, 4 figures, Accepted to AIM-FM Workshop @ NeurIPS'24

Deep Multimodal Representation Learning for Stellar Spectra

Tobias Buck, Christian Schwarz

Comments accepted to the Machine Learning and the Physical Sciences Workshop, NeurIPS 2024

Investigating Sensitive Directions in GPT-2: An Improved Baseline and Comparative Analysis of SAEs

Daniel J. Lee, Stefan Heimersheim

Comments Presented at the Attributing Model Behavior at Scale (ATTRIB) and Scientific Methods for Understanding Deep Learning (SciForDL) workshops at NeurIPS 2024

ActNAS : Generating Efficient YOLO Models using Activation NAS

Sudhakar Sah, Ravish Kumar, Darshan C. Ganji, Ehsan Saboori

Comments 7 pages, 4 figures, FITML workshop, NeuRIPS 2024

ReLU's Revival: On the Entropic Overload in Normalization-Free Large Language Models

Nandan Kumar Jha, Brandon Reagen

Comments Accepted to NeurIPS 2024 Workshop on Attributing Model Behavior at Scale (Camera-ready version)