Papers
Integrating Intermediate Layer Optimization and Projected Gradient Descent for Solving Inverse Problems with Diffusion Models
Yang Zheng, Wen Li, Zhaoqiang Liu
Integration-free Kernels for Equivariant Gaussian Process Modelling
Tim Steinert, David Ginsbourger, August Lykke-Møller et al.
Interaction-Aware Gaussian Weighting for Clustered Federated Learning
Alessandro Licciardi, Davide Leo, Eros Fanı̀ et al.
Interchangeable Token Embeddings for Extendable Vocabulary and Alpha-Equivalence
İlker Işık, Ramazan Gokberk Cinbis, Ebru Aydin Gol
Internal Causal Mechanisms Robustly Predict Language Model Out-of-Distribution Behaviors
Jing Huang, Junyi Tao, Thomas Icard et al.
Interpolating Neural Network-Tensor Decomposition (INN-TD): a scalable and interpretable approach for large-scale physics-based problems
Jiachen Guo, Xiaoyu Xie, Chanwook Park et al.
Interpreting CLIP with Hierarchical Sparse Autoencoders
Vladimir Zaigrajew, Hubert Baniecki, Przemyslaw Biecek
Interpreting the Repeated Token Phenomenon in Large Language Models
Itay Yona, Ilia Shumailov, Jamie Hayes et al.
Intersectional Fairness in Reinforcement Learning with Large State and Constraint Spaces
Eric Eaton, Marcel Hussing, Michael Kearns et al.
IntLoRA: Integral Low-rank Adaptation of Quantized Diffusion Models
Hang Guo, Yawei Li, Tao Dai et al.
Introducing 3D Representation for Dense Volume-to-Volume Translation via Score Fusion
Xiyue Zhu, Dou Hoon Kwark, Ruike Zhu et al.
Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning
Changsheng Wang, Yihua Zhang, Jinghan Jia et al.
Invariant Deep Uplift Modeling for Incentive Assignment in Online Marketing via Probability of Necessity and Sufficiency
Zexu Sun, Qiyu Han, Hao Yang et al.
Inverse Bridge Matching Distillation
Nikita Gushchin, David Li, Daniil Selikhanovych et al.
Inverse Flow and Consistency Models
Yuchen Zhang, Jian Zhou
Inverse Optimization via Learning Feasible Regions
Ke Ren, Peyman Mohajerin Esfahani, Angelos Georghiou
Inverse Problem Sampling in Latent Space Using Sequential Monte Carlo
Idan Achituve, Hai Victor Habi, Amir Rosenfeld et al.
Inverse problems with experiment-guided AlphaFold
Sai Advaith Maddipatla, Nadav Bojan, Meital Bojan et al.
Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors
Jingyang Ke, Feiyang Wu, Jiyi Wang et al.
Investigating Non-Transitivity in LLM-as-a-Judge
Yi Xu, Laura Ruis, Tim Rocktäschel et al.
Investigating the Overlooked Hessian Structure: From CNNs to LLMs
Qian-Yuan Tang, Yufei Gu, Yunfeng Cai et al.
IRBridge: Solving Image Restoration Bridge with Pre-trained Generative Diffusion Models
Hanting Wang, Tao Jin, Wang Lin et al.
Is Best-of-N the Best of Them? Coverage, Scaling, and Optimality in Inference-Time Alignment
Audrey Huang, Adam Block, Qinghua Liu et al.
Is Complex Query Answering Really Complex?
Cosimo Gregucci, Bo Xiong, Daniel Hernández et al.
Is Noise Conditioning Necessary for Denoising Generative Models?
Qiao Sun, Zhicheng Jiang, Hanhong Zhao et al.