NeurIPS

LexEval: A Comprehensive Chinese Legal Benchmark for Evaluating Large Language Models

Haitao Li, You Chen, Qingyao Ai, Yueyue Wu, Ruizhe Zhang, Yiqun Liu

Comments NeurIPs 2024

Learning Spatially-Aware Language and Audio Embeddings

Bhavika Devnani, Skyler Seto, Zakaria Aldeneh, Alessandro Toso, Elena Menyaylenko, Barry-John Theobald, Jonathan Sheaffer, Miguel Sarabia

Comments 26 pages, 7 figures, accepted at NeurIPS 2024

SAM-MPA: Applying SAM to Few-shot Medical Image Segmentation using Mask Propagation and Auto-prompting

Jie Xu, Xiaokang Li, Chengyu Yue, Yuanyuan Wang, Yi Guo

Comments Accepted as an oral presentation at NeurIPS 2024 AIM-FM Workshop

Different Bias Under Different Criteria: Assessing Bias in LLMs with a Fact-Based Approach

Changgeon Ko, Jisu Shin, Hoyun Song, Jeongyeon Seo, Jong C. Park

Comments Accepted in NeurIPS 2024 Workshop on Socially Responsible Language Modelling Research (SoLaR)

An In-depth Investigation of Sparse Rate Reduction in Transformer-like Models

Yunzhe Hu, Difan Zou, Dong Xu

Comments NeurIPS 2024

Conformalised Conditional Normalising Flows for Joint Prediction Regions in time series

Eshant English, Christoph Lippert

Comments Workshop on Bayesian Decision-making and Uncertainty, 38th Conference on Neural Information Processing Systems (NeurIPS 2024)

Reprogramming Pretrained Target-Specific Diffusion Models for Dual-Target Drug Design

Xiangxin Zhou, Jiaqi Guan, Yijia Zhang, Xingang Peng, Liang Wang, Jianzhu Ma

Comments Accepted to NeurIPS 2024

Learning via Surrogate PAC-Bayes

Antoine Picard-Weibel, Roman Moscoviz, Benjamin Guedj

Comments 20 pages

Journal ref Neurips 2024, Dec 2024, Vancouver, Canada

LLM Circuit Analyses Are Consistent Across Training and Scale

Curt Tigges, Michael Hanna, Qinan Yu, Stella Biderman

Comments NeurIPS 2024

Delta-CoMe: Training-Free Delta-Compression with Mixed-Precision for Large Language Models

Bowen Ping, Shuo Wang, Hanqing Wang, Xu Han, Yuzhuang Xu, Yukun Yan, Yun Chen, Baobao Chang, Zhiyuan Liu, Maosong Sun

Comments NeurIPS 2024

Linguistic Collapse: Neural Collapse in (Large) Language Models

Robert Wu, Vardan Papyan

Comments NeurIPS 2024; 35 pages; 30 figures; reverted to log mean norms for NC2

Diffusion-Reward Adversarial Imitation Learning

Chun-Mao Lai, Hsiang-Chun Wang, Ping-Chun Hsieh, Yu-Chiang Frank Wang, Min-Hung Chen, Shao-Hua Sun

Comments NeurIPS 2024. Project page: https://nturobotlearninglab.github.io/DRAIL/

UniTS: A Unified Multi-Task Time Series Model

Shanghua Gao, Teddy Koker, Owen Queen, Thomas Hartvigsen, Theodoros Tsiligkaridis, Marinka Zitnik

Comments NeurIPS 2024

Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration

Wenjie Fu, Huandong Wang, Chen Gao, Guanghua Liu, Yong Li, Tao Jiang

Comments Repo: NeurIPS2024_SPV-MIA" target="_blank" rel="noopener">https://github.com/tsinghua-fib-lab/NeurIPS2024_SPV-MIA

Journal ref The Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS 2024)

Exploring Discrete Flow Matching for 3D De Novo Molecule Generation

Ian Dunn, David R. Koes

Comments Presented at the NeurIPS 2024 Machine Learning for Structural Biology Workshop

Privacy Protection in Personalized Diffusion Models via Targeted Cross-Attention Adversarial Attack

Xide Xu, Muhammad Atif Butt, Sandesh Kamath, Bogdan Raducanu

Comments Accepted at Safe Generative AI Workshop (NeurIPS 2024)

Towards Foundation Models for Critical Care Time Series

Manuel Burger, Fedor Sergeev, Malte Londschien, Daphné Chopard, Hugo Yèche, Eike Gerdes, Polina Leshetkina, Alexander Morgenroth, Zeynep Babür, Jasmina Bogojeska, Martin Faltys, Rita Kuznetsova, Gunnar Rätsch

Comments Accepted for Oral Presentation at AIM-FM Workshop at NeurIPS 2024

Sparse patches adversarial attacks via extrapolating point-wise information

Yaniv Nemcovsky, Avi Mendelson, Chaim Baskin

Comments AdvML-Frontiers 24: The 3nd Workshop on New Frontiers in Adversarial Machine Learning, NeurIPS 24

Learning Optimal Lattice Vector Quantizers for End-to-end Neural Image Compression

Xi Zhang, Xiaolin Wu

Comments Accepted by NeurIPS 2024

PIANIST: Learning Partially Observable World Models with LLMs for Multi-Agent Decision Making

Jonathan Light, Sixue Xing, Yuanzhe Liu, Weiqin Chen, Min Cai, Xiusi Chen, Guanzhi Wang, Wei Cheng, Yisong Yue, Ziniu Hu

Comments Published at Language Gamification Workshop 2024 @ NeurIPS

Navigating the Effect of Parametrization for Dimensionality Reduction

Haiyang Huang, Yingfan Wang, Cynthia Rudin

Comments NeurIPS 2024

Inducing Human-like Biases in Moral Reasoning Language Models

Artem Karpov, Seong Hah Cho, Austin Meek, Raymond Koopmanschap, Lucy Farnik, Bogdan-Ionut Cirstea

Comments Accepted to the 2nd Workshop on Unifying Representations in Neural Models (UniReps) at NeurIPS 2024

Trap-MID: Trapdoor-based Defense against Model Inversion Attacks

Zhen-Ting Liu, Shang-Tse Chen

Comments Accepted by Neural Information Processing Systems (NeurIPS) 2024

Improving Decision Sparsity

Yiyang Sun, Tong Wang, Cynthia Rudin

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

Incorporating Metabolic Information into LLMs for Anomaly Detection in Clinical Time-Series

Maxx Richard Rahman, Ruoxuan Liu, Wolfgang Maass

Journal ref NeurIPS 2024 Workshop on Time Series in the Age of Large Models

Fostering Intrinsic Motivation in Reinforcement Learning with Pretrained Foundation Models

Alain Andres, Javier Del Ser

Comments Accepted at the Intrinsically Motivated Open-ended Learning workshop at NeurIPS 2024

Language Grounded Multi-agent Reinforcement Learning with Human-interpretable Communication

Huao Li, Hossein Nourkhiz Mahjoub, Behdad Chalaki, Vaishnav Tadiparthi, Kwonjoon Lee, Ehsan Moradi-Pari, Charles Michael Lewis, Katia P Sycara

Comments Accepted to Neurips 2024, 19 pages, 10 figures

TEG-DB: A Comprehensive Dataset and Benchmark of Textual-Edge Graphs

Zhuofeng Li, Zixing Gou, Xiangnan Zhang, Zhongyuan Liu, Sirui Li, Yuntong Hu, Chen Ling, Zheng Zhang, Liang Zhao

Comments Accepted by NeurIPS 2024

Optimistic Verifiable Training by Controlling Hardware Nondeterminism

Megha Srivastava, Simran Arora, Dan Boneh

Comments 11 pages, 5 figures, Neural Information Processing Systems (NeurIPS) 2024,

PointMamba: A Simple State Space Model for Point Cloud Analysis

Dingkang Liang, Xin Zhou, Wei Xu, Xingkui Zhu, Zhikang Zou, Xiaoqing Ye, Xiao Tan, Xiang Bai

Comments Accepted at NeurIPS 2024. The code will be made available at https://github.com/LMD0311/PointMamba