Poster Papers
24,624 papers found • Page 73 of 493
Conference
Distilling Multi-modal Large Language Models for Autonomous Driving
Deepti Hegde, Rajeev Yasarla, Hong Cai et al.
Distilling Parallel Gradients for Fast ODE Solvers of Diffusion Models
Beier Zhu, Ruoyu Wang, Tong Zhao et al.
Distilling Reinforcement Learning Algorithms for In-Context Model-Based Planning
Jaehyeon Son, Soochan Lee, Gunhee Kim
Distilling Spatially-Heterogeneous Distortion Perception for Blind Image Quality Assessment
Xudong Li, Wenjie Nie, Yan Zhang et al.
Distilling Spectral Graph for Object-Context Aware Open-Vocabulary Semantic Segmentation
Chanyoung Kim, Dayun Ju, Woojung Han et al.
Distilling Structural Representations into Protein Sequence Models
Jeffrey Ouyang-Zhang, Chengyue Gong, Yue Zhao et al.
Distilling the Knowledge in Data Pruning
Emanuel Ben Baruch, Adam Botach, Igor Kviatkovsky et al.
DisTime: Distribution-based Time Representation for Video Large Language Models
yingsen zeng, Zepeng Huang, Yujie Zhong et al.
Distinguishing Cause from Effect with Causal Velocity Models
Johnny Xi, Hugh Dance, Peter Orbanz et al.
Distinguish Then Exploit: Source-free Open Set Domain Adaptation via Weight Barcode Estimation and Sparse Label Assignment
Weiming Liu, Jun Dan, Fan Wang et al.
Dist Loss: Enhancing Regression in Few-Shot Region through Distribution Distance Constraint
Guangkun Nie, Gongzheng Tang, Shenda Hong
Distortion of AI Alignment: Does Preference Optimization Optimize for Preferences?
Paul Gölz, Nika Haghtalab, Kunhe Yang
Distributed Conformal Prediction via Message Passing
Haifeng Wen, Hong XING, Osvaldo Simeone
Distributed Differentially Private Data Analytics via Secure Sketching
Jakob Burkhardt, Hannah Keller, Claudio Orlandi et al.
Distributed Event-Based Learning via ADMM
Guner Dilsad ER, Sebastian Trimpe, Michael Muehlebach
Distributed mediation analysis with communication efficiency
Shaomin Li
Distributed Multi-Agent Bandits Over Erdős-Rényi Random Networks
Jingyuan Liu, Hao Qiu, Lin Yang et al.
Distributed Nonparametric Estimation: from Sparse to Dense Samples per Terminal
Deheng Yuan, Tao Guo, Zhongyi Huang
Distributed Parallel Gradient Stacking(DPGS): Solving Whole Slide Image Stacking Challenge in Multi-Instance Learning
Boyuan Wu, wang, Xianwei Lin et al.
Distributed Retraction-Free and Communication-Efficient Optimization on the Stiefel Manifold
Yilong Song, Peijin Li, Bin Gao et al.
Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference
Nadav Timor, Jonathan Mamou, Daniel Korat et al.
Distributional Adversarial Attacks and Training in Deep Hedging
Guangyi He, Tobias Sutter, Lukas Gonon
Distributional Associations vs In-Context Reasoning: A Study of Feed-forward and Attention Layers
Lei Chen, Joan Bruna, Alberto Bietti
Distributional Autoencoders Know the Score
Andrej Leban
Distributional Diffusion Models with Scoring Rules
Valentin De Bortoli, Alexandre Galashov, J Swaroop Guntupalli et al.
Distribution-Aligned Decoding for Efficient LLM Task Adaptation
Senkang Hu, Xudong Han, Jinqi Jiang et al.
Distributional LLM-as-a-Judge
Luyu Chen, Zeyu Zhang, Haoran Tan et al.
Distributionally Robust Active Learning for Gaussian Process Regression
Shion Takeno, Yoshito Okura, Yu Inatsu et al.
Distributionally Robust Feature Selection
Maitreyi Swaroop, Tamar Krishnamurti, Bryan Wilder
Distributionally Robust Learning for Multi-source Unsupervised Domain Adaptation
Zhenyu Wang, Peter Bühlmann, Zijian Guo
Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping
Guangyi Liu, Suzan Iloglu, Michael Caldara et al.
Distributionally Robust Performative Optimization
Zhuangzhuang Jia, Yijie Wang, Roy Dong et al.
Distributionally Robust Policy Learning under Concept Drifts
Jingyuan Wang, Zhimei Ren, Ruohan Zhan et al.
Distribution-Aware Tensor Decomposition for Compression of Convolutional Neural Networks
Alper KALLE, Théo Rudkiewicz, Mohamed Ouerfelli et al.
Distribution Backtracking Builds A Faster Convergence Trajectory for Diffusion Distillation
Shengyuan Zhang, Ling Yang, Zejian Li et al.
Distribution-Free Data Uncertainty for Neural Network Regression
Domokos M. Kelen, Ádám Jung, Péter Kersch et al.
Distribution Learning Meets Graph Structure Sampling
Arnab Bhattacharyya, Sutanu Gayen, Philips George John et al.
Distribution Prototype Diffusion Learning for Open-set Supervised Anomaly Detection
Fuyun Wang, Tong Zhang, Yuanzhi Wang et al.
Distribution-Specific Agnostic Conditional Classification With Halfspaces
Jizhou Huang, Brendan Juba
Distributive Fairness in Large Language Models: Evaluating Alignment with Human Values
Hadi Hosseini, Samarth Khanna
DistRL: An Asynchronous Distributed Reinforcement Learning Framework for On-Device Control Agent
Taiyi Wang, Zhihao Wu, Jianheng Liu et al.
DiT4SR: Taming Diffusion Transformer for Real-World Image Super-Resolution
Zheng-Peng Duan, jiawei zhang, Xin Jin et al.
DiTaiListener: Controllable High Fidelity Listener Video Generation with Diffusion
Maksim Siniukov, Di Chang, Minh Tran et al.
DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation
Dongya Jia, Zhuo Chen, Jiawei Chen et al.
Dita: Scaling Diffusion Transformer for Generalist Vision-Language-Action Policy
Zhi Hou, Tianyi Zhang, Yuwen Xiong et al.
DiTASK: Multi-Task Fine-Tuning with Diffeomorphic Transformations
Krishna Sri Ipsit Mantri, Carola-Bibiane Schönlieb, Bruno Ribeiro et al.
Ditch the Denoiser: Emergence of Noise Robustness in Self-Supervised Learning from Data Curriculum
Wenquan Lu, Jiaqi Zhang, Hugues Van Assel et al.
DiTCtrl: Exploring Attention Control in Multi-Modal Diffusion Transformer for Tuning-Free Multi-Prompt Longer Video Generation
Minghong Cai, Xiaodong Cun, Xiaoyu Li et al.
DiTFastAttnV2: Head-wise Attention Compression for Multi-Modality Diffusion Transformers
Hanling Zhang, Rundong Su, Zhihang Yuan et al.
DitHub: A Modular Framework for Incremental Open-Vocabulary Object Detection
Chiara Cappellino, Gianluca Mancusi, Matteo Mosconi et al.