NeurIPS

Latent Diffusion Model for DNA Sequence Generation

Zehui Li, Yuhao Ni, Tim August B. Huygelen, Akashaditya Das, Guoxuan Xia, Guy-Bart Stan, Yiren Zhao

Comments 2023 Conference on Neural Information Processing Systems (NeurIPS 2023) AI for Science Workshop

Recurrent Hypernetworks are Surprisingly Strong in Meta-RL

Jacob Beck, Risto Vuorio, Zheng Xiong, Shimon Whiteson

Comments Published at NeurIPS 2023. We provide code at https://github.com/jacooba/hyper

Beta Diffusion

Mingyuan Zhou, Tianqi Chen, Zhendong Wang, Huangjie Zheng

Comments NeurIPS 2023

VisIT-Bench: A Benchmark for Vision-Language Instruction Following Inspired by Real-World Use

Yonatan Bitton, Hritik Bansal, Jack Hessel, Rulin Shao, Wanrong Zhu, Anas Awadalla, Josh Gardner, Rohan Taori, Ludwig Schmidt

Comments Accepted to NeurIPS 2023, Datasets and Benchmarks. Website: https://visit-bench.github.io/

MVDiffusion: Enabling Holistic Multi-view Image Generation with Correspondence-Aware Diffusion

Shitao Tang, Fuyang Zhang, Jiacheng Chen, Peng Wang, Yasutaka Furukawa

Comments Project page, https://mvdiffusion.github.io; NeurIPS 2023 (spotlight); Compressed camera-ready version

WBCAtt: A White Blood Cell Dataset Annotated with Detailed Morphological Attributes

Satoshi Tsutsui, Winnie Pang, Bihan Wen

Comments Neural Information Processing Systems 2023

OpenGSL: A Comprehensive Benchmark for Graph Structure Learning

Zhiyao Zhou, Sheng Zhou, Bochao Mao, Xuanyi Zhou, Jiawei Chen, Qiaoyu Tan, Daochen Zha, Yan Feng, Chun Chen, Can Wang

Comments 25 pages, 21 figures. Camera-ready version for NeurIPS Datasets and Benchmarks Track 2023

Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena

Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, Ion Stoica

Comments NeurIPS 2023 Datasets and Benchmarks Track

PolyDiffuse: Polygonal Shape Reconstruction via Guided Set Diffusion Models

Jiacheng Chen, Ruizhi Deng, Yasutaka Furukawa

Comments Project page: https://poly-diffuse.github.io/; NeurIPS 2023 camera-ready version

Towards Revealing the Mystery behind Chain of Thought: A Theoretical Perspective

Guhao Feng, Bohang Zhang, Yuntian Gu, Haotian Ye, Di He, Liwei Wang

Comments 42 pages; Camera-ready version for NeurIPS 2023 (Oral Presentation)

Learning Rate Free Sampling in Constrained Domains

Louis Sharrock, Lester Mackey, Christopher Nemeth

Comments Accepted at NeurIPS 2023

What You See is What You Read? Improving Text-Image Alignment Evaluation

Michal Yarom, Yonatan Bitton, Soravit Changpinyo, Roee Aharoni, Jonathan Herzig, Oran Lang, Eran Ofek, Idan Szpektor

Comments Accepted to NeurIPS 2023. Website: https://wysiwyr-itm.github.io/

Neural Lyapunov Control for Discrete-Time Systems

Junlin Wu, Andrew Clark, Yiannis Kantaros, Yevgeniy Vorobeychik

Comments NeurIPS 2023

Causal Discovery from Subsampled Time Series with Proxy Variables

Mingzhou Liu, Xinwei Sun, Lingjing Hu, Yizhou Wang

Comments NeurIPS 2023

Lift Yourself Up: Retrieval-augmented Text Generation with Self Memory

Xin Cheng, Di Luo, Xiuying Chen, Lemao Liu, Dongyan Zhao, Rui Yan

Comments Neurips 2023

Learning with Explanation Constraints

Rattana Pukdee, Dylan Sam, J. Zico Kolter, Maria-Florina Balcan, Pradeep Ravikumar

Comments NeurIPS 2023

Trust Region-Based Safe Distributional Reinforcement Learning for Multiple Constraints

Dohyeong Kim, Kyungjae Lee, Songhwai Oh

Comments 32 pages, Accepted at NeurIPS 2023

Memory Efficient Meta-Learning with Large Images

John Bronskill, Daniela Massiceti, Massimiliano Patacchiola, Katja Hofmann, Sebastian Nowozin, Richard E. Turner

Journal ref 35th Conference on Neural Information Processing Systems (NeurIPS 2021)

SutraNets: Sub-series Autoregressive Networks for Long-Sequence, Probabilistic Forecasting

Shane Bergsma, Timothy Zeyl, Lei Guo

Journal ref Proceedings of 37th Conference on Neural Information Processing Systems (NeurIPS 2023)

Hazards from Increasingly Accessible Fine-Tuning of Downloadable Foundation Models

Alan Chan, Ben Bucknall, Herbie Bradley, David Krueger

Comments Accepted as a spotlight workshop paper at the Socially Responsible Language Modelling Research (SoLaR) workshop, held at NeurIPS 2023

nbi: the Astronomer's Package for Neural Posterior Estimation

Keming Zhang, Joshua S. Bloom, Stéfan van der Walt, Nina Hernitschek

Comments Update references. Accepted to NeurIPS 2023 Workshop on Deep Learning and Inverse Problems. Initially appeared at ICML 2023 Workshop on Machine Learning for Astrophysics. Code at https://github.com/kmzzhang/nbi

Enhancing Sharpness-Aware Optimization Through Variance Suppression

Bingcong Li, Georgios B. Giannakis

Comments Accepted to NeurIPS 2023

Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning

Zachary Charles, Nicole Mitchell, Krishna Pillutla, Michael Reneer, Zachary Garrett

Comments Dataset Grouper is available at https://github.com/google-research/dataset_grouper

Journal ref NeurIPS 2023 (Datasets & Benchmarks)

Provable convergence guarantees for black-box variational inference

Justin Domke, Guillaume Garrigos, Robert Gower

Comments Accepted at NeurIPS 2023

Coordinating Distributed Example Orders for Provably Accelerated Training

A. Feder Cooper, Wentao Guo, Khiem Pham, Tiancheng Yuan, Charlie F. Ruan, Yucheng Lu, Christopher De Sa

Comments NeurIPS 2023

Capture the Flag: Uncovering Data Insights with Large Language Models

Issam Laradji, Perouz Taslakian, Sai Rajeswar, Valentina Zantedeschi, Alexandre Lacoste, Nicolas Chapados, David Vazquez, Christopher Pal, Alexandre Drouin

Comments 14 pages, 1 figure, Foundation Models for Decision Making Workshop at NeurIPS 2023

Structure-Aware Path Inference for Neural Finite State Transducers

Weiting Tan, Chu-cheng Lin, Jason Eisner

Comments In Proceedings of ICBINB Workshop at NeurIPS 2023

Independent Mechanism Analysis and the Manifold Hypothesis

Shubhangi Ghosh, Luigi Gresele, Julius von Kügelgen, Michel Besserve, Bernhard Schölkopf

Comments 6 pages, Accepted at Neurips Causal Representation Learning 2023

Unsupervised Estimation of Ensemble Accuracy

Simi Haber, Yonatan Wexler

Comments 4 pages, 2 figures. Accepted to InfoCOG@NeurIPS 2023

Cross-modal Prompts: Adapting Large Pre-trained Models for Audio-Visual Downstream Tasks

Haoyi Duan, Yan Xia, Mingze Zhou, Li Tang, Jieming Zhu, Zhou Zhao

Comments Accepted to NeurIPS 2023