Oral Papers

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

232

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.

370

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.