Oral Papers
1,594 papers found • Page 29 of 32
Conference
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.
Latent Trajectory Learning for Limited Timestamps under Distribution Shift over Time
Qiuhao Zeng, Changjian Shui, Long-Kai Huang et al.
Learning and Forgetting Unsafe Examples in Large Language Models
Jiachen Zhao, Zhun Deng, David Madras et al.
Learning Causal Domain-Invariant Temporal Dynamics for Few-Shot Action Recognition
Yuke Li, Guangyi Chen, Ben Abramowitz et al.
Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings
Ilyass Hammouamri, Ismail Khalfaoui Hassani, Timothée Masquelier
Learning Grounded Action Abstractions from Language
Lio Wong, Jiayuan Mao, Pratyusha Sharma et al.
Learning Hierarchical World Models with Adaptive Temporal Abstractions from Discrete Latent Dynamics
Christian Gumbsch, Noor Sajid, Georg Martius et al.
Learning interpretable control inputs and dynamics underlying animal locomotion
Thomas Soares Mullen, Marine Schimel, Guillaume Hennequin et al.
Learning Latent Dynamic Robust Representations for World Models
Ruixiang Sun, Hongyu Zang, Xin Li et al.
Learning Multi-Faceted Prototypical User Interests
Nhu-Thuat Tran, Hady W. Lauw
Learning Scale-Aware Spatio-temporal Implicit Representation for Event-based Motion Deblurring
Wei Yu, Jianing Li, Shengping Zhang et al.
Learning semilinear neural operators: A unified recursive framework for prediction and data assimilation.
Ashutosh Singh, Ricardo Borsoi, Deniz Erdogmus et al.
Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure for Decision-Making
Vivek Myers, Chongyi Zheng, Anca Dragan et al.
Learning to Act without Actions
Dominik Schmidt, Minqi Jiang
Leveraging Generative Models for Unsupervised Alignment of Neural Time Series Data
Ayesha Vermani, Il Memming Park, Josue Nassar
LLCP: Learning Latent Causal Processes for Reasoning-based Video Question Answer
Guangyi Chen, Yuke Li, Xiao Liu et al.
LLM-grounded Video Diffusion Models
Long Lian, Baifeng Shi, Adam Yala et al.
Longitudinal Targeted Minimum Loss-based Estimation with Temporal-Difference Heterogeneous Transformer
Toru Shirakawa, Yi Li, Yulun Wu et al.
Long Range Propagation on Continuous-Time Dynamic Graphs
Alessio Gravina, Giulio Lovisotto, Claudio Gallicchio et al.
Look, Remember and Reason: Grounded Reasoning in Videos with Language Models
Apratim Bhattacharyya, Sunny Panchal, Reza Pourreza et al.
LRR: Language-Driven Resamplable Continuous Representation against Adversarial Tracking Attacks
Jianlang Chen, Xuhong Ren, Qing Guo et al.
Manipulating dropout reveals an optimal balance of efficiency and robustness in biological and machine visual systems
Jacob Prince, Gabriel Fajardo, George Alvarez et al.