Papers
Estimating Generic 3D Room Structures from 2D Annotations
Denys Rozumnyi, Stefan Popov, Kevis-kokitsi Maninis et al.
Estimating Koopman operators with sketching to provably learn large scale dynamical systems
Giacomo Meanti, Antoine Chatalic, Vladimir Kostic et al.
Estimating Noise Correlations Across Continuous Conditions With Wishart Processes
Amin Nejatbakhsh, Isabel Garon, Alex Williams
Estimating Propensity for Causality-based Recommendation without Exposure Data
Zhongzhou Liu, Yuan Fang, Min Wu
Estimating Riemannian Metric with Noise-Contaminated Intrinsic Distance
Jiaming Qiu, Xiongtao Dai
Estimating the Rate-Distortion Function by Wasserstein Gradient Descent
Yibo Yang, Stephan Eckstein, Marcel Nutz et al.
Ethical Considerations for Responsible Data Curation
Jerone Andrews, Dora Zhao, William Thong et al.
Evaluating and Improving Tool-Augmented Computation-Intensive Math Reasoning
Beichen Zhang, Kun Zhou, Xilin Wei et al.
Evaluating and Inducing Personality in Pre-trained Language Models
Guangyuan Jiang, Manjie Xu, Song-Chun Zhu et al.
Evaluating Cognitive Maps and Planning in Large Language Models with CogEval
Ida Momennejad, Hosein Hasanbeig, Felipe Vieira Frujeri et al.
Evaluating Graph Neural Networks for Link Prediction: Current Pitfalls and New Benchmarking
Juanhui Li, Harry Shomer, Haitao Mao et al.
Evaluating Neuron Interpretation Methods of NLP Models
Yimin Fan, Fahim Dalvi, Nadir Durrani et al.
Evaluating Open-QA Evaluation
Cunxiang Wang, Sirui Cheng, Qipeng Guo et al.
Evaluating Post-hoc Explanations for Graph Neural Networks via Robustness Analysis
Junfeng Fang, Wei Liu, Yuan Gao et al.
Evaluating Robustness and Uncertainty of Graph Models Under Structural Distributional Shifts
Gleb Bazhenov, Denis Kuznedelev, Andrey Malinin et al.
Evaluating Self-Supervised Learning for Molecular Graph Embeddings
Hanchen Wang, Jean Kaddour, Shengchao Liu et al.
Evaluating the Moral Beliefs Encoded in LLMs
Nino Scherrer, Claudia Shi, Amir Feder et al.
Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance
Jonathan Crabbé, Mihaela van der Schaar
Event Stream GPT: A Data Pre-processing and Modeling Library for Generative, Pre-trained Transformers over Continuous-time Sequences of Complex Events
Matthew McDermott, Bret Nestor, Peniel Argaw et al.
Every Parameter Matters: Ensuring the Convergence of Federated Learning with Dynamic Heterogeneous Models Reduction
Hanhan Zhou, Tian Lan, Guru Prasadh Venkataramani et al.
EV-Eye: Rethinking High-frequency Eye Tracking through the Lenses of Event Cameras
Guangrong Zhao, Yurun Yang, Jingwei Liu et al.
EvoFed: Leveraging Evolutionary Strategies for Communication-Efficient Federated Learning
Mohammad Mahdi Rahimi, Hasnain Irshad Bhatti, Younghyun Park et al.
Evolutionary Neural Architecture Search for Transformer in Knowledge Tracing
Shangshang Yang, Xiaoshan Yu, Ye Tian et al.
Evolving Connectivity for Recurrent Spiking Neural Networks
Guan Wang, Yuhao Sun, Sijie Cheng et al.
Evolving Standardization for Continual Domain Generalization over Temporal Drift
Mixue Xie, Shuang Li, Longhui Yuan et al.