Papers
Improving Interpretation Faithfulness for Vision Transformers
Lijie Hu, Yixin Liu, Ninghao Liu et al.
Improving Neural Additive Models with Bayesian Principles
Kouroche Bouchiat, Alexander Immer, Hugo Yèche et al.
Improving Neural Logic Machines via Failure Reflection
Zhiming Li, Yushi Cao, Yan Zheng et al.
Improving Open-Ended Text Generation via Adaptive Decoding
Wenhong Zhu, Hongkun Hao, Zhiwei He et al.
Improving Prototypical Visual Explanations with Reward Reweighing, Reselection, and Retraining
Aaron Jiaxun Li, Robin Netzorg, Zhihan Cheng et al.
Improving Robustness to Multiple Spurious Correlations by Multi-Objective Optimization
Nayeong Kim, Juwon Kang, Sungsoo Ahn et al.
Improving Sample Efficiency of Model-Free Algorithms for Zero-Sum Markov Games
Songtao Feng, Ming Yin, Yu-Xiang Wang et al.
Improving SAM Requires Rethinking its Optimization Formulation
Wanyun Xie, Fabian Latorre, Kimon Antonakopoulos et al.
Improving Sharpness-Aware Minimization by Lookahead
Runsheng Yu, Youzhi Zhang, James Kwok
Improving Token-Based World Models with Parallel Observation Prediction
Lior Cohen, Kaixin Wang, Bingyi Kang et al.
Improving Transformers with Dynamically Composable Multi-Head Attention
Da Xiao, Qingye Meng, Shengping Li et al.
IM-Unpack: Training and Inference with Arbitrarily Low Precision Integers
Zhanpeng Zeng, Karthikeyan Sankaralingam, Vikas Singh
Incentivized Learning in Principal-Agent Bandit Games
Antoine Scheid, Daniil Tiapkin, Etienne Boursier et al.
In-context Convergence of Transformers
Yu Huang, Yuan Cheng, Yingbin Liang
In-Context Decision Transformer: Reinforcement Learning via Hierarchical Chain-of-Thought
Sili Huang, Jifeng Hu, Hechang Chen et al.
In-Context Freeze-Thaw Bayesian Optimization for Hyperparameter Optimization
Herilalaina Rakotoarison, Steven Adriaensen, Neeratyoy Mallik et al.
In-Context Language Learning: Architectures and Algorithms
Ekin Akyürek, Bailin Wang, Yoon Kim et al.
In-Context Learning Agents Are Asymmetric Belief Updaters
Johannes A. Schubert, Akshay Kumar Jagadish, Marcel Binz et al.
In-context Learning on Function Classes Unveiled for Transformers
Zhijie Wang, Bo Jiang, Shuai Li
In-Context Principle Learning from Mistakes
Tianjun Zhang, Aman Madaan, Luyu Gao et al.
In-Context Reinforcement Learning for Variable Action Spaces
Viacheslav Sinii, Alexander Nikulin, Vladislav Kurenkov et al.
In-Context Sharpness as Alerts: An Inner Representation Perspective for Hallucination Mitigation
Shiqi Chen, Miao Xiong, Junteng Liu et al.
In-Context Unlearning: Language Models as Few-Shot Unlearners
Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju
In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering
Sheng Liu, Haotian Ye, Lei Xing et al.
Incorporating Information into Shapley Values: Reweighting via a Maximum Entropy Approach
Darya Biparva, Donatello Materassi