Oral Papers
1,594 papers found • Page 1 of 32
$F^3Set$: Towards Analyzing Fast, Frequent, and Fine-grained Events from Videos
Zhaoyu Liu, Kan Jiang, Murong Ma et al.
$\mathcal{V}ista\mathcal{DPO}$: Video Hierarchical Spatial-Temporal Direct Preference Optimization for Large Video Models
Haojian Huang, Haodong Chen, Shengqiong Wu et al.
$\textit{HiMaCon:}$ Discovering Hierarchical Manipulation Concepts from Unlabeled Multi-Modal Data
Ruizhe Liu, Pei Zhou, Qian Luo et al.
$\text{S}^2$Q-VDiT: Accurate Quantized Video Diffusion Transformer with Salient Data and Sparse Token Distillation
Weilun Feng, Haotong Qin, Chuanguang Yang et al.
1000+ FPS 4D Gaussian Splatting for Dynamic Scene Rendering
Yuheng Yuan, Qiuhong Shen, Xingyi Yang et al.
1000 Layer Networks for Self-Supervised RL: Scaling Depth Can Enable New Goal-Reaching Capabilities
Kevin Wang, Ishaan Javali, Michał Bortkiewicz et al.
3DLLM-Mem: Long-Term Spatial-Temporal Memory for Embodied 3D Large Language Model
Wenbo Hu, Yining Hong, Yanjun Wang et al.
3D-RAD: A Comprehensive 3D Radiology Med-VQA Dataset with Multi-Temporal Analysis and Diverse Diagnostic Tasks
Xiaotang Gai, Jiaxiang Liu, Yichen Li et al.
3D StreetUnveiler with Semantic-aware 2DGS - a simple baseline
Jingwei Xu, Yikai Wang, Yiqun Zhao et al.
4DGCPro: Efficient Hierarchical 4D Gaussian Compression for Progressive Volumetric Video Streaming
Zihan Zheng, Zhenlong Wu, Houqiang Zhong et al.
4D-LRM: Large Space-Time Reconstruction Model From and To Any View at Any Time
Ziqiao Ma, Xuweiyi Chen, Shoubin Yu et al.
4D-VLA: Spatiotemporal Vision-Language-Action Pretraining with Cross-Scene Calibration
Jiahui Zhang, Yurui Chen, Yueming Xu et al.
4K4DGen: Panoramic 4D Generation at 4K Resolution
Renjie Li, Panwang Pan, Bangbang Yang et al.
6D Object Pose Tracking in Internet Videos for Robotic Manipulation
Georgy Ponimatkin, Martin Cífka, Tomas Soucek et al.
ABKD: Pursuing a Proper Allocation of the Probability Mass in Knowledge Distillation via $\alpha$-$\beta$-Divergence
Guanghui Wang, Zhiyong Yang, Zitai Wang et al.
Abstain Mask Retain Core: Time Series Prediction by Adaptive Masking Loss with Representation Consistency
Renzhao Liang, Sizhe Xu, Chenggang Xie et al.
Accelerating LLM Inference with Lossless Speculative Decoding Algorithms for Heterogeneous Vocabularies
Nadav Timor, Jonathan Mamou, Daniel Korat et al.
Accelerating Parallel Diffusion Model Serving with Residual Compression
Jiajun Luo, Yicheng Xiao, Jianru Xu et al.
Accelerating Task Generalisation with Multi-Level Skill Hierarchies
Thomas Cannon, Özgür Şimşek
Accident Anticipation via Temporal Occurrence Prediction
Tianhao Zhao, Yiyang Zou, Zihao Mao et al.
A Chaotic Dynamics Framework Inspired by Dorsal Stream for Event Signal Processing
yu chen, Jing Lian, Zhaofei Yu et al.
A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment
Edward Chang
A Clean Slate for Offline Reinforcement Learning
Matthew T Jackson, Uljad Berdica, Jarek Liesen et al.
A Closed-Form Solution for Fast and Reliable Adaptive Testing
Yan Zhuang, Chenye Ke, Zirui Liu et al.
Action Dubber: Timing Audible Actions via Inflectional Flow
Wenlong Wan, Weiying Zheng, Tianyi Xiang et al.
Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional
Sanjeev Raja, Martin Šípka, Michael Psenka et al.
Action Sequence Augmentation for Action Anticipation
Yihui Qiu, Deepu Rajan
Active Fine-Tuning of Multi-Task Policies
Marco Bagatella, Jonas Hübotter, Georg Martius et al.
Act Only When It Pays: Efficient Reinforcement Learning for LLM Reasoning via Selective Rollouts
Haizhong Zheng, Yang Zhou, Brian Bartoldson et al.
Adaptive Context Length Optimization with Low-Frequency Truncation for Multi-Agent Reinforcement Learning
Wenchang Duan, Yaoliang Yu, Jiwan He et al.
Adaptive Estimation and Learning under Temporal Distribution Shift
Dheeraj Baby, Yifei Tang, Hieu Nguyen et al.
Adaptive Quantization in Generative Flow Networks for Probabilistic Sequential Prediction
Nadhir Hassen, Zhen Zhang, Johan Verjans
Adaptive Surrogate Gradients for Sequential Reinforcement Learning in Spiking Neural Networks
Korneel Van den Berghe, Stein Stroobants, Vijay Janapa Reddi et al.
Adaptive Time Encoding for Irregular Multivariate Time-Series Classification
Sangho Lee, Kyeongseo Min, Youngdoo Son et al.
AdaSplash: Adaptive Sparse Flash Attention
Nuno Gonçalves, Marcos V. Treviso, Andre Martins
A data and task-constrained mechanistic model of the mouse outer retina shows robustness to contrast variations
Kyra Kadhim, Jonas Beck, Ziwei Huang et al.
AdaTS: Learning Adaptive Time Series Representations via Dynamic Soft Contrasts
Denizhan Kara, Tomoyoshi Kimura, Jinyang Li et al.
Addressing Mark Imbalance in Integration-free Marked Temporal Point Processes
Sishun Liu, KE DENG, Yongli Ren et al.
Addressing Misspecification in Simulation-based Inference through Data-driven Calibration
Antoine Wehenkel, Juan L. Gamella, Ozan Sener et al.
Adjoint Schrödinger Bridge Sampler
Guan-Horng Liu, Jaemoo Choi, Yongxin Chen et al.
A Driving-Style-Adaptive Framework for Vehicle Trajectory Prediction
Di Wen, Yu Wang, Zhigang Wu et al.
Advanced Sign Language Video Generation with Compressed and Quantized Multi-Condition Tokenization
Cong Wang, Zexuan Deng, Zhiwei Jiang et al.
Advancing Expert Specialization for Better MoE
Hongcan Guo, Haolang Lu, Guoshun Nan et al.
Adversarial Training for Defense Against Label Poisoning Attacks
Melis Ilayda Bal, Volkan Cevher, Michael Muehlebach
AdvWave: Stealthy Adversarial Jailbreak Attack against Large Audio-Language Models
Mintong Kang, Chejian Xu, Bo Li
Aeolus: A Multi-structural Flight Delay Dataset
Lin Xu, Xinyun Yuan, Yuxuan Liang et al.
AffectGPT: A New Dataset, Model, and Benchmark for Emotion Understanding with Multimodal Large Language Models
Zheng Lian, Haoyu Chen, Lan Chen et al.
A Finite Sample Analysis of Distributional TD Learning with Linear Function Approximation
Yang Peng, Kaicheng Jin, Liangyu Zhang et al.
AGC-Drive: A Large-Scale Dataset for Real-World Aerial-Ground Collaboration in Driving Scenarios
Yunhao Hou, Bochao Zou, Min Zhang et al.
A Generalization Result for Convergence in Learning-to-Optimize
Michael Sucker, Peter Ochs