Papers
Interactive Multi-fidelity Learning for Cost-effective Adaptation of Language Model with Sparse Human Supervision
Jiaxin Zhang, Zhuohang Li, Kamalika Das et al.
Interactive Visual Reasoning under Uncertainty
Manjie Xu, Guangyuan Jiang, Wei Liang et al.
InterCode: Standardizing and Benchmarking Interactive Coding with Execution Feedback
John Yang, Akshara Prabhakar, Karthik Narasimhan et al.
Interpretability at Scale: Identifying Causal Mechanisms in Alpaca
Zhengxuan Wu, Atticus Geiger, Thomas Icard et al.
Interpretable and Explainable Logical Policies via Neurally Guided Symbolic Abstraction
Quentin Delfosse, Hikaru Shindo, Devendra Dhami et al.
Interpretable Graph Networks Formulate Universal Algebra Conjectures
Francesco Giannini, Stefano Fioravanti, Oguzhan Keskin et al.
Interpretable Prototype-based Graph Information Bottleneck
Sangwoo Seo, Sungwon Kim, Chanyoung Park
Interpretable Reward Redistribution in Reinforcement Learning: A Causal Approach
Yudi Zhang, Yali Du, Biwei Huang et al.
Interpreting Unsupervised Anomaly Detection in Security via Rule Extraction
Ruoyu Li, Qing Li, Yu Zhang et al.
Intervention Generalization: A View from Factor Graph Models
Gecia Bravo-Hermsdorff, David Watson, Jialin Yu et al.
Into the LAION’s Den: Investigating Hate in Multimodal Datasets
Abeba Birhane, vinay prabhu, Sanghyun Han et al.
Into the Single Cell Multiverse: an End-to-End Dataset for Procedural Knowledge Extraction in Biomedical Texts
Ruth Dannenfelser, Jeffrey Zhong, Ran Zhang et al.
Intra-Modal Proxy Learning for Zero-Shot Visual Categorization with CLIP
Qi Qian, Yuanhong Xu, Juhua Hu
Intriguing Properties of Quantization at Scale
Arash Ahmadian, Saurabh Dash, Hongyu Chen et al.
Intrinsic Dimension Estimation for Robust Detection of AI-Generated Texts
Eduard Tulchinskii, Kristian Kuznetsov, Laida Kushnareva et al.
Invariant Anomaly Detection under Distribution Shifts: A Causal Perspective
João Carvalho, Mengtao Zhang, Robin Geyer et al.
Invariant Learning via Probability of Sufficient and Necessary Causes
Mengyue Yang, Zhen Fang, Yonggang Zhang et al.
Inverse Dynamics Pretraining Learns Good Representations for Multitask Imitation
David Brandfonbrener, Ofir Nachum, Joan Bruna
Inverse Preference Learning: Preference-based RL without a Reward Function
Joey Hejna, Dorsa Sadigh
Inverse Reinforcement Learning with the Average Reward Criterion
Feiyang Wu, Jingyang Ke, Anqi Wu
Investigating how ReLU-networks encode symmetries
Georg Bökman, Fredrik Kahl
IPMix: Label-Preserving Data Augmentation Method for Training Robust Classifiers
Zhenglin Huang, Xiaoan Bao, Na Zhang et al.
iSCAN: Identifying Causal Mechanism Shifts among Nonlinear Additive Noise Models
Tianyu Chen, Kevin Bello, Bryon Aragam et al.
Is Distance Matrix Enough for Geometric Deep Learning?
Zian Li, Xiyuan Wang, Yinan Huang et al.
Is Heterogeneity Notorious? Taming Heterogeneity to Handle Test-Time Shift in Federated Learning
Yue Tan, Chen Chen, Weiming Zhuang et al.