Papers
11,015 papers found
INSIDE: LLMs' Internal States Retain the Power of Hallucination Detection
Chao Chen, Kai Liu, Ze Chen et al.
InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation
Xingchao Liu, Xiwen Zhang, Jianzhu Ma et al.
#InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models
Keming Lu, Hongyi Yuan, Zheng Yuan et al.
Instant3D: Fast Text-to-3D with Sparse-view Generation and Large Reconstruction Model
Jiahao Li, Hao Tan, Kai Zhang et al.
InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists
Yulu Gan, Sungwoo Park, Alexander Marcel Schubert et al.
InstructDET: Diversifying Referring Object Detection with Generalized Instructions
Ronghao Dang, Jiangyan Feng, Haodong Zhang et al.
Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions
Taehyeon Kim, Joonkee Kim, Gihun Lee et al.
InstructPix2NeRF: Instructed 3D Portrait Editing from a Single Image
Jianhui Li, Shilong Liu, Zidong Liu et al.
InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior
Chenguo Lin, Yadong MU
Integrating Planning and Deep Reinforcement Learning via Automatic Induction of Task Substructures
Jung-Chun Liu, Chi-Hsien Chang, Shao-Hua Sun et al.
Intelligent Switching for Reset-Free RL
Darshan Patil, Janarthanan Rajendran, Glen Berseth et al.
Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning
Yun-Hin Chan, Rui Zhou, Running Zhao et al.
InternVid: A Large-scale Video-Text Dataset for Multimodal Understanding and Generation
Yi Wang, Yinan He, Yizhuo Li et al.
InterpGNN: Understand and Improve Generalization Ability of Transdutive GNNs through the Lens of Interplay between Train and Test Nodes
Jiawei Sun, Kailai Li, Ruoxin Chen et al.
Interpretable Diffusion via Information Decomposition
Xianghao Kong, Ollie Liu, Han Li et al.
Interpretable Meta-Learning of Physical Systems
Matthieu Blanke, Marc Lelarge
Interpretable Sparse System Identification: Beyond Recent Deep Learning Techniques on Time-Series Prediction
Xiaoyi Liu, Duxin Chen, Wenjia Wei et al.
Interpreting CLIP's Image Representation via Text-Based Decomposition
Yossi Gandelsman, Alexei A Efros, Jacob Steinhardt
Interpreting Robustness Proofs of Deep Neural Networks
Debangshu Banerjee, Avaljot Singh, Gagandeep Singh
Interventional Fairness on Partially Known Causal Graphs: A Constrained Optimization Approach
Aoqi Zuo, Yiqing Li, Susan Wei et al.
Intriguing Properties of Data Attribution on Diffusion Models
Xiaosen Zheng, Tianyu Pang, Chao Du et al.
Intriguing Properties of Generative Classifiers
Priyank Jaini, Kevin Clark, Robert Geirhos
Invariance-based Learning of Latent Dynamics
Kai Lagemann, Christian Lagemann, Sach Mukherjee
Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
Shida Wang, Zhong Li, Qianxiao Li
Investigating the Benefits of Projection Head for Representation Learning
Yihao Xue, Eric Gan, Jiayi Ni et al.