2024 Oral Papers
315 papers found • Page 3 of 7
Flow to Better: Offline Preference-based Reinforcement Learning via Preferred Trajectory Generation
Zhilong Zhang, Yihao Sun, Junyin Ye et al.
Foundation Policies with Hilbert Representations
Seohong Park, Tobias Kreiman, Sergey Levine
FreeDyG: Frequency Enhanced Continuous-Time Dynamic Graph Model for Link Prediction
Yuxing Tian, Yiyan Qi, Fan Guo
FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling
Haonan Qiu, Menghan Xia, Yong Zhang et al.
From Fourier to Neural ODEs: Flow Matching for Modeling Complex Systems
Xin Li, Jingdong Zhang, Qunxi Zhu et al.
From Generalization Analysis to Optimization Designs for State Space Models
Fusheng Liu, Qianxiao Li
FROSTER: Frozen CLIP is A Strong Teacher for Open-Vocabulary Action Recognition
Xiaohu Huang, Hao Zhou, Kun Yao et al.
Frozen Transformers in Language Models Are Effective Visual Encoder Layers
Ziqi Pang, Ziyang Xie, Yunze Man et al.
Future Language Modeling from Temporal Document History
Changmao Li, Jeffrey Flanigan
GAFormer: Enhancing Timeseries Transformers Through Group-Aware Embeddings
Jingyun Xiao, Ran Liu, Eva Dyer
Game-Theoretic Robust Reinforcement Learning Handles Temporally-Coupled Perturbations
Yongyuan Liang, Yanchao Sun, Ruijie Zheng et al.
Generative Learning for Financial Time Series with Irregular and Scale-Invariant Patterns
Hongbin Huang, Minghua Chen, Xiao Qiao
Genie: Generative Interactive Environments
Jake Bruce, Michael Dennis, Ashley Edwards et al.
Graph-based Forecasting with Missing Data through Spatiotemporal Downsampling
Ivan Marisca, Cesare Alippi, Filippo Maria Bianchi
Graph-based Virtual Sensing from Sparse and Partial Multivariate Observations
Giovanni De Felice, Andrea Cini, Daniele Zambon et al.
GraphPulse: Topological representations for temporal graph property prediction
Kiarash Shamsi, Farimah Poursafaei, Shenyang(Andy) Huang et al.
Graph Transformers on EHRs: Better Representation Improves Downstream Performance
Raphael Poulain, Rahmatollah Beheshti
Ground-A-Video: Zero-shot Grounded Video Editing using Text-to-image Diffusion Models
Hyeonho Jeong, Jong Chul YE
Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogram
Yeongyeon Na, Minje Park, Yunwon Tae et al.
HelmFluid: Learning Helmholtz Dynamics for Interpretable Fluid Prediction
Lanxiang Xing, Haixu Wu, yuezhou ma et al.
Hierarchical State Space Models for Continuous Sequence-to-Sequence Modeling
Raunaq Bhirangi, Chenyu Wang, Venkatesh Pattabiraman et al.
High-Performance Temporal Reversible Spiking Neural Networks with $\mathcal{O}(L)$ Training Memory and $\mathcal{O}(1)$ Inference Cost
JiaKui Hu, Man Yao, Xuerui Qiu et al.
How Deep Do We Need: Accelerating Training and Inference of Neural ODEs via Control Perspective
Keyan Miao, Konstantinos Gatsis
How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Models
Pascal Chang, Jingwei Tang, Markus Gross et al.
How Well Can LLMs Negotiate? NegotiationArena Platform and Analysis
Federico Bianchi, Patrick John Chia, Mert Yuksekgonul et al.
Hybrid Inverse Reinforcement Learning
Juntao Ren, Gokul Swamy, Steven Wu et al.
Hybrid Neural Representations for Spherical Data
Hyomin Kim, Yunhui Jang, Jaeho Lee et al.
IIANet: An Intra- and Inter-Modality Attention Network for Audio-Visual Speech Separation
Kai Li, Runxuan Yang, Fuchun Sun et al.
Implicit Gaussian process representation of vector fields over arbitrary latent manifolds
Robert Peach, Matteo Vinao-Carl, Nir Grossman et al.
Implicit Representations for Constrained Image Segmentation
Jan Philipp Schneider, Mishal Fatima, Jovita Lukasik et al.
In-Context Learning Dynamics with Random Binary Sequences
Eric Bigelow, Ekdeep Singh Lubana, Robert Dick et al.
Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images
Kuofeng Gao, Yang Bai, Jindong Gu et al.
Inherent Trade-Offs between Diversity and Stability in Multi-Task Benchmarks
Guanhua Zhang, Moritz Hardt
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics
Manuel Brenner, Florian Hess, Georgia Koppe et al.
Interacting Diffusion Processes for Event Sequence Forecasting
Mai Zeng, Florence Regol, Mark Coates
Invariance-based Learning of Latent Dynamics
Kai Lagemann, Christian Lagemann, Sach Mukherjee
Investigating Pre-Training Objectives for Generalization in Vision-Based Reinforcement Learning
Donghu Kim, Hojoon Lee, Kyungmin Lee et al.
IOI: Invisible One-Iteration Adversarial Attack on No-Reference Image- and Video-Quality Metrics
Ekaterina Shumitskaya, Anastasia Antsiferova, Dmitriy Vatolin
Irregular Multivariate Time Series Forecasting: A Transformable Patching Graph Neural Networks Approach
Weijia Zhang, Chenlong Yin, Hao Liu et al.
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting
Yong Liu, Tengge Hu, Haoran Zhang et al.
Keep the Momentum: Conservation Laws beyond Euclidean Gradient Flows
Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré
Kernel Metric Learning for In-Sample Off-Policy Evaluation of Deterministic RL Policies
Haanvid Lee, Tri Wahyu Guntara, Jongmin Lee et al.
KISA: A Unified Keyframe Identifier and Skill Annotator for Long-Horizon Robotics Demonstrations
Longxin Kou, Fei Ni, Yan Zheng et al.
Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks
David Bell, Yujie Lu, Shinda Huang et al.
Language-guided Skill Learning with Temporal Variational Inference
Haotian Fu, Pratyusha Sharma, Elias Stengel-Eskin et al.
Language Models Represent Space and Time
Wes Gurnee, Max Tegmark
Large Language Models are Geographically Biased
Rohin Manvi, Samar Khanna, Marshall Burke et al.
Large Language Models Are Not Robust Multiple Choice Selectors
Chujie Zheng, Hao Zhou, Fandong Meng et al.
Latent Logic Tree Extraction for Event Sequence Explanation from LLMs
Zitao Song, Chao Yang, Chaojie Wang et al.
Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck
Marco Federici, Patrick Forré, Ryota Tomioka et al.