Paper List

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Summary of Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling, by Hyungi Lee et al.
Summary of Adaptive Bounding Box Uncertainties Via Two-step Conformal Prediction, by Alexander Timans et al.
Summary of Graph Data Condensation Via Self-expressive Graph Structure Reconstruction, by Zhanyu Liu et al.
Summary of Convergence Of Some Convex Message Passing Algorithms to a Fixed Point, by Vaclav Voracek et al.
Summary of Autoeval Done Right: Using Synthetic Data For Model Evaluation, by Pierre Boyeau et al.
Summary of A Pid-controlled Non-negative Tensor Factorization Model For Analyzing Missing Data in Nilm, by Dengyu Shi
Summary of Adaptive Hyperparameter Optimization For Continual Learning Scenarios, by Rudy Semola et al.
Summary of A Unified Model For Spatio-temporal Prediction Queries with Arbitrary Modifiable Areal Units, by Liyue Chen et al.
Summary of Fwin Transformer For Dengue Prediction Under Climate and Ocean Influence, by Nhat Thanh Tran et al.
Summary of An Efficient Learning-based Solver Comparable to Metaheuristics For the Capacitated Arc Routing Problem, by Runze Guo et al.
Summary of Aug-kd: Anchor-based Mixup Generation For Out-of-domain Knowledge Distillation, by Zihao Tang et al.
Summary of The Cram Method For Efficient Simultaneous Learning and Evaluation, by Zeyang Jia et al.
Summary of Interpreting What Typical Fault Signals Look Like Via Prototype-matching, by Qian Chen and Xingjian Dong and Zhike Peng
Summary of A Converting Autoencoder Toward Low-latency and Energy-efficient Dnn Inference at the Edge, by Hasanul Mahmud et al.
Summary of Leveraging Graph Neural Networks For Supporting Automatic Triage Of Patients, by Annamaria Defilippo and Pierangelo Veltri and Pietro Lio’ and Pietro Hiram Guzzi
Summary of Ant Colony Sampling with Gflownets For Combinatorial Optimization, by Minsu Kim et al.
Summary of Explainable Learning with Gaussian Processes, by Kurt Butler et al.
Summary of Improving Deep Learning with Prior Knowledge and Cognitive Models: a Survey on Enhancing Explainability, Adversarial Robustness and Zero-shot Learning, by Fuseinin Mumuni and Alhassan Mumuni
Summary of All in One: Multi-task Prompting For Graph Neural Networks (extended Abstract), by Xiangguo Sun et al.
Summary of Falcon: Flop-aware Combinatorial Optimization For Neural Network Pruning, by Xiang Meng et al.
Summary of Gaussian Loss Smoothing Enables Certified Training with Tight Convex Relaxations, by Stefan Balauca et al.
Summary of Class Imbalance in Object Detection: An Experimental Diagnosis and Study Of Mitigation Strategies, by Nieves Crasto
Summary of Comq: a Backpropagation-free Algorithm For Post-training Quantization, by Aozhong Zhang et al.
Summary of Impact Of Noisy Supervision in Foundation Model Learning, by Hao Chen et al.
Summary of A Geospatial Approach to Predicting Desert Locust Breeding Grounds in Africa, by Ibrahim Salihu Yusuf et al.
Summary of Cood: Combined Out-of-distribution Detection Using Multiple Measures For Anomaly & Novel Class Detection in Large-scale Hierarchical Classification, by L. E. Hogeweg et al.
Summary of Semantic Residual Prompts For Continual Learning, by Martin Menabue et al.
Summary of On the Generalization Ability Of Unsupervised Pretraining, by Yuyang Deng et al.
Summary of Unveiling the Significance Of Toddler-inspired Reward Transition in Goal-oriented Reinforcement Learning, by Junseok Park et al.
Summary of Benign Overfitting in Leaky Relu Networks with Moderate Input Dimension, by Kedar Karhadkar et al.
Summary of Cost-sensitive Learning to Defer to Multiple Experts with Workload Constraints, by Jean V. Alves et al.
Summary of Responsible Artificial Intelligence: a Structured Literature Review, by Sabrina Goellner et al.
Summary of Counterfactual Reasoning with Knowledge Graph Embeddings, by Lena Zellinger et al.
Summary of Transformers Learn Low Sensitivity Functions: Investigations and Implications, by Bhavya Vasudeva et al.
Summary of Selma: Learning and Merging Skill-specific Text-to-image Experts with Auto-generated Data, by Jialu Li et al.
Summary of The Pitfalls Of Next-token Prediction, by Gregor Bachmann et al.
Summary of Acquiring Diverse Skills Using Curriculum Reinforcement Learning with Mixture Of Experts, by Onur Celik et al.
Summary of Guiding Llms the Right Way: Fast, Non-invasive Constrained Generation, by Luca Beurer-kellner et al.
Summary of A Representation-learning Game For Classes Of Prediction Tasks, by Neria Uzan and Nir Weinberger
Summary of Bayesian Diffusion Models For 3d Shape Reconstruction, by Haiyang Xu et al.
Summary of Survival Modeling Using Deep Learning, Machine Learning and Statistical Methods: a Comparative Analysis For Predicting Mortality After Hospital Admission, by Ziwen Wang et al.
Summary of Evacuation Management Framework Towards Smart City-wide Intelligent Emergency Interactive Response System, by Anuj Abraham and Yi Zhang and Shitala Prasad
Summary of Multi-agent Reinforcement Learning with a Hierarchy Of Reward Machines, by Xuejing Zheng et al.
Summary of Provable Mutual Benefits From Federated Learning in Privacy-sensitive Domains, by Nikita Tsoy et al.
Summary of Streamlining in the Riemannian Realm: Efficient Riemannian Optimization with Loopless Variance Reduction, by Yury Demidovich et al.
Summary of Spatial Features Of Co2 For Occupancy Detection in a Naturally Ventilated School Building, by Qirui Huang et al.
Summary of Advancing Graph Neural Networks with Hl-hgat: a Hodge-laplacian and Attention Mechanism Approach For Heterogeneous Graph-structured Data, by Jinghan Huang et al.
Summary of Probabilistic Contrastive Learning For Long-tailed Visual Recognition, by Chaoqun Du et al.
Summary of On the Approximation Of Kernel Functions, by Paul Dommel and Alois Pichler
Summary of Koopman Ensembles For Probabilistic Time Series Forecasting, by Anthony Frion et al.
Summary of Alarm: Align Language Models Via Hierarchical Rewards Modeling, by Yuhang Lai et al.
Summary of Average Calibration Error: a Differentiable Loss For Improved Reliability in Image Segmentation, by Theodore Barfoot and Luis Garcia-peraza-herrera and Ben Glocker and Tom Vercauteren
Summary of Xb-maml: Learning Expandable Basis Parameters For Effective Meta-learning with Wide Task Coverage, by Jae-jun Lee et al.
Summary of Leveraging Internal Representations Of Model For Magnetic Image Classification, by Adarsh N L et al.
Summary of Multistep Consistency Models, by Jonathan Heek et al.
Summary of On the Global Convergence Of Policy Gradient in Average Reward Markov Decision Processes, by Navdeep Kumar et al.
Summary of Monotone Individual Fairness, by Yahav Bechavod
Summary of Efficient First-order Algorithms For Large-scale, Non-smooth Maximum Entropy Models with Application to Wildfire Science, by Gabriel P. Langlois et al.
Summary of In-context Exploration-exploitation For Reinforcement Learning, by Zhenwen Dai et al.
Summary of Constructing Variables Using Classifiers As An Aid to Regression: An Empirical Assessment, by Colin Troisemaine et al.
Summary of Can Llms Separate Instructions From Data? and What Do We Even Mean by That?, By Egor Zverev et al.
Summary of Towards An Educational Tool For Supporting Neonatologists in the Delivery Room, by Giorgio Leonardi et al.
Summary of Quantifying the Sensitivity Of Inverse Reinforcement Learning to Misspecification, by Joar Skalse and Alessandro Abate
Summary of A Differential Geometric View and Explainability Of Gnn on Evolving Graphs, by Yazheng Liu et al.
Summary of Joint-embedding Masked Autoencoder For Self-supervised Learning Of Dynamic Functional Connectivity From the Human Brain, by Jungwon Choi et al.
Summary of Prediction Of Wort Density with Lstm Network, by Derk Rembold et al.
Summary of Graph Neural Network with Two Uplift Estimators For Label-scarcity Individual Uplift Modeling, by Dingyuan Zhu et al.
Summary of Detection Of Unobserved Common Causes Based on Nml Code in Discrete, Mixed, and Continuous Variables, by Masatoshi Kobayashi et al.
Summary of Rl-msa: a Reinforcement Learning-based Multi-line Bus Scheduling Approach, by Yingzhuo Liu
Summary of Sardet-100k: Towards Open-source Benchmark and Toolkit For Large-scale Sar Object Detection, by Yuxuan Li et al.
Summary of Tactical Decision Making For Autonomous Trucks by Deep Reinforcement Learning with Total Cost Of Operation Based Reward, By Deepthi Pathare et al.
Summary of Adaptive Federated Learning Over the Air, by Chenhao Wang et al.
Summary of Decentralized and Lifelong-adaptive Multi-agent Collaborative Learning, by Shuo Tang et al.
Summary of Omh: Structured Sparsity Via Optimally Matched Hierarchy For Unsupervised Semantic Segmentation, by Baran Ozaydin et al.
Summary of Unraveling the Mystery Of Scaling Laws: Part I, by Hui Su et al.
Summary of Enhancing Joint Motion Prediction For Individuals with Limb Loss Through Model Reprogramming, by Sharmita Dey et al.
Summary of Scalable Online Exploration Via Coverability, by Philip Amortila et al.
Summary of Ffad: a Novel Metric For Assessing Generated Time Series Data Utilizing Fourier Transform and Auto-encoder, by Yang Chen et al.
Summary of Contextgpt: Infusing Llms Knowledge Into Neuro-symbolic Activity Recognition Models, by Luca Arrotta et al.
Summary of Evaluating the Energy Efficiency Of Few-shot Learning For Object Detection in Industrial Settings, by Georgios Tsoumplekas et al.
Summary of Distributionally Generative Augmentation For Fair Facial Attribute Classification, by Fengda Zhang et al.
Summary of Elephants Never Forget: Testing Language Models For Memorization Of Tabular Data, by Sebastian Bordt et al.
Summary of Peeraid: Improving Adversarial Distillation From a Specialized Peer Tutor, by Jaewon Jung et al.
Summary of Unpacking Tokenization: Evaluating Text Compression and Its Correlation with Model Performance, by Omer Goldman et al.
Summary of Physics-guided Abnormal Trajectory Gap Detection, by Arun Sharma et al.
Summary of Understanding and Mitigating Human-labelling Errors in Supervised Contrastive Learning, by Zijun Long and Lipeng Zhuang and George Killick and Richard Mccreadie and Gerardo Aragon Camarasa and Paul Henderson
Summary of Analysis Of Total Variation Minimization For Clustered Federated Learning, by A. Jung
Summary of Nonparametric Automatic Differentiation Variational Inference with Spline Approximation, by Yuda Shao et al.
Summary of Optimal Policy Sparsification and Low Rank Decomposition For Deep Reinforcement Learning, by Vikram Goddla
Summary of Fake or Compromised? Making Sense Of Malicious Clients in Federated Learning, by Hamid Mozaffari et al.
Summary of A Reductions Approach to Risk-sensitive Reinforcement Learning with Optimized Certainty Equivalents, by Kaiwen Wang et al.
Summary of From Instructions to Constraints: Language Model Alignment with Automatic Constraint Verification, by Fei Wang et al.
Summary of Finite-time Error Analysis Of Soft Q-learning: Switching System Approach, by Narim Jeong and Donghwan Lee
Summary of Feataug: Automatic Feature Augmentation From One-to-many Relationship Tables, by Danrui Qi et al.
Summary of Distributional Successor Features Enable Zero-shot Policy Optimization, by Chuning Zhu et al.
Summary of Pre-trained Model Recommendation For Downstream Fine-tuning, by Jiameng Bai et al.
Summary of Towards Robust Out-of-distribution Generalization Bounds Via Sharpness, by Yingtian Zou et al.
Summary of Deepsafempc: Deep Learning-based Model Predictive Control For Safe Multi-agent Reinforcement Learning, by Xuefeng Wang et al.
Summary of On the Diminishing Returns Of Width For Continual Learning, by Etash Guha et al.
Summary of What Makes Quantization For Large Language Models Hard? An Empirical Study From the Lens Of Perturbation, by Zhuocheng Gong et al.