Poster Papers
24,624 papers found • Page 74 of 493
Conference
DiTTo-TTS: Diffusion Transformers for Scalable Text-to-Speech without Domain-Specific Factors
Keon Lee, Dong Won Kim, Jaehyeon Kim et al.
Divergence-enhanced Knowledge-guided Context Optimization for Visual-Language Prompt Tuning
Yilun Li, Miaomiao Cheng, Xu Han et al.
Divergence of Neural Tangent Kernel in Classification Problems
Zixiong Yu, Songtao Tian, Guhan Chen
Divergence-Regularized Discounted Aggregation: Equilibrium Finding in Multiplayer Partially Observable Stochastic Games
Runyu Lu, Yuanheng Zhu, Dongbin Zhao
Diverging Preferences: When do Annotators Disagree and do Models Know?
Michael Zhang, Zhilin Wang, Jena Hwang et al.
DiverseFlow: Sample-Efficient Diverse Mode Coverage in Flows
Mashrur M. Morshed, Vishnu Naresh Boddeti
Diverse Influence Component Analysis: A Geometric Approach to Nonlinear Mixture Identifiability
Hoang Son Nguyen, Xiao Fu
Diverse Preference Learning for Capabilities and Alignment
Stewart Slocum, Asher Parker-Sartori, Dylan Hadfield-Menell
Diverse Prototypical Ensembles Improve Robustness to Subpopulation Shift
Nguyen Nhat Minh To, Paul Wilson, Viet Nguyen et al.
Diversified Flow Matching with Translation Identifiability
Sagar Shrestha, Xiao Fu
Diversifying Parallel Ergodic Search: A Signature Kernel Evolution Strategy
Sreevardhan Sirigiri, Christian Hughes, Ian Abraham et al.
Diversity as a Reward: Fine-Tuning LLMs on a Mixture of Domain-Undetermined Data
Zhenqing Ling, Daoyuan Chen, Liuyi Yao et al.
Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization
Michael S Yao, James Gee, Osbert Bastani
Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents
Kexun Zhang, Weiran Yao, Zuxin Liu et al.
Diversity-Enhanced Distribution Alignment for Dataset Distillation
Hongcheng Li, Yucan Zhou, Xiaoyan Gu et al.
Diversity Is All You Need for Contrastive Learning: Spectral Bounds on Gradient Magnitudes
Peter Ochieng
Diversity-oriented Deep Multi-modal Clustering
Wang Yanzheng, Xin Yang, Yujun Wang et al.
Diversity-Rewarded CFG Distillation
Geoffrey Cideron, Andrea Agostinelli, Johan Ferret et al.
DIVE: Taming DINO for Subject-Driven Video Editing
Yi Huang, Wei Xiong, He Zhang et al.
Divide and Conquer: Exploring Language-centric Tree Reasoning for Video Question-Answering
Zhaohe Liao, Jiangtong Li, Siyu Sun et al.
Divide-and-Conquer for Enhancing Unlabeled Learning, Stability, and Plasticity in Semi-supervised Continual Learning
Yue Duan, Taicai Chen, Lei Qi et al.
Divide and Conquer: Heterogeneous Noise Integration for Diffusion-based Adversarial Purification
Gaozheng Pei, Shaojie Lyu, Gong Chen et al.
Divide and Conquer: Learning Label Distribution with Subtasks
Haitao Wu, Weiwei Li, Xiuyi Jia
Divide and Translate: Compositional First-Order Logic Translation and Verification for Complex Logical Reasoning
Hyun Ryu, Gyeongman Kim, Hyemin S. Lee et al.
Diving into Self-Evolving Training for Multimodal Reasoning
Wei Liu, Junlong Li, Xiwen Zhang et al.
Diving into the Fusion of Monocular Priors for Generalized Stereo Matching
Chengtang Yao, Lidong Yu, Zhidan Liu et al.
Divot: Diffusion Powers Video Tokenizer for Comprehension and Generation
Yuying Ge, Yizhuo Li, Yixiao Ge et al.
DivPrune: Diversity-based Visual Token Pruning for Large Multimodal Models
Saeed Ranjbar Alvar, Gursimran Singh, Mohammad Akbari et al.
DKC: Differentiated Knowledge Consolidation for Cloth-Hybrid Lifelong Person Re-identification
Zhenyu Cui, Jiahuan Zhou, Yuxin Peng
DKDM: Data-Free Knowledge Distillation for Diffusion Models with Any Architecture
Qianlong Xiang, Miao Zhang, Yuzhang Shang et al.
DKDR: Dynamic Knowledge Distillation for Reliability in Federated Learning
Yueyang Yuan, Wenke Huang, Guancheng Wan et al.
dKV-Cache: The Cache for Diffusion Language Models
Xinyin Ma, Runpeng Yu, Gongfan Fang et al.
DL2G: Degradation-guided Local-to-Global Restoration for Eyeglass Reflection Removal
Yizhilv, Xiao Lu, Hong Ding et al.
DLEFT-MKC: Dynamic Late Fusion Multiple Kernel Clustering with Robust Tensor Learning via Min-Max Optimization
Yi Zhang, Siwei Wang, Jiyuan Liu et al.
DLFR-Gen: Diffusion-based Video Generation with Dynamic Latent Frame Rate
Zhihang Yuan, Rui Xie, Yuzhang Shang et al.
DLoFT: Gradient-Decoupled Fine-Tuning for Generalizable Long Chain-of-Thought Reasoning
Sitong Wu, Haoru Tan, Jingyao Li et al.
DLP: Dynamic Layerwise Pruning in Large Language Models
Yuli Chen, Bo Cheng, Jiale Han et al.
DM-EFS: Dynamically Multiplexed Expanded Features Set Form for Robust and Efficient Small Object Detection
Aashish Sharma
DMesh++: An Efficient Differentiable Mesh for Complex Shapes
Sanghyun Son, Matheus Gadelha, Yang Zhou et al.
DMM: Distributed Matrix Mechanism for Differentially-Private Federated Learning Based on Constant-Overhead Linear Secret Resharing
Alexander Bienstock, Ujjwal Kumar, Antigoni Polychroniadou
DMol: A Highly Efficient and Chemical Motif-Preserving Molecule Generation Platform
Peizhi Niu, Yu-Hsiang Wang, Vishal Rana et al.
DMQ: Dissecting Outliers of Diffusion Models for Post-Training Quantization
Dongyeun Lee, jiwan hur, Hyounguk Shon et al.
DNF-Intrinsic: Deterministic Noise-Free Diffusion for Indoor Inverse Rendering
Rongjia Zheng, Qing Zhang, Chengjiang Long et al.
DNF: Unconditional 4D Generation with Dictionary-based Neural Fields
Xinyi Zhang, Naiqi Li, Angela Dai
DnLUT: Ultra-Efficient Color Image Denoising via Channel-Aware Lookup Tables
Sidi Yang, Binxiao Huang, Yulun Zhang et al.
Do as I do (Safely): Mitigating Task-Specific Fine-tuning Risks in Large Language Models
Francisco Eiras, Aleksandar Petrov, Philip Torr et al.
Do as We Do, Not as You Think: the Conformity of Large Language Models
Zhiyuan Weng, Guikun Chen, Wenguan Wang
Do Automatic Factuality Metrics Measure Factuality? A Critical Evaluation
Sanjana Ramprasad, Byron Wallace
Do Bayesian Neural Networks Actually Behave Like Bayesian Models?
Gábor Pituk, Vik Shirvaikar, Tom Rainforth
Dobi-SVD: Differentiable SVD for LLM Compression and Some New Perspectives
Qinsi Wang, Jinghan Ke, Masayoshi Tomizuka et al.