Paper List

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Summary of Enhanced Anomaly Detection in Automotive Systems Using Saad: Statistical Aggregated Anomaly Detection, by Dacian Goina et al.
Summary of Federated Incomplete Multi-view Clustering with Heterogeneous Graph Neural Networks, by Xueming Yan et al.
Summary of A Mathematical Certification For Positivity Conditions in Neural Networks with Applications to Partial Monotonicity and Ethical Ai, by Alejandro Polo-molina et al.
Summary of Imfl-aigc: Incentive Mechanism Design For Federated Learning Empowered by Artificial Intelligence Generated Content, By Guangjing Huang et al.
Summary of Distildoc: Knowledge Distillation For Visually-rich Document Applications, by Jordy Van Landeghem et al.
Summary of Residual Learning and Context Encoding For Adaptive Offline-to-online Reinforcement Learning, by Mohammadreza Nakhaei et al.
Summary of Mail: Improving Imitation Learning with Mamba, by Xiaogang Jia et al.
Summary of Leveraging Large Language Models For Web Scraping, by Aman Ahluwalia et al.
Summary of Dataset Enhancement with Instance-level Augmentations, by Orest Kupyn et al.
Summary of Learning Positional Encodings in Transformers Depends on Initialization, by Takuya Ito et al.
Summary of Conformal Load Prediction with Transductive Graph Autoencoders, by Rui Luo and Nicolo Colombo
Summary of Pre-training Identification Of Graph Winning Tickets in Adaptive Spatial-temporal Graph Neural Networks, by Wenying Duan et al.
Summary of Decoupling the Class Label and the Target Concept in Machine Unlearning, by Jianing Zhu et al.
Summary of Vessel Re-identification and Activity Detection in Thermal Domain For Maritime Surveillance, by Yasod Ginige et al.
Summary of Measuring Model Variability Using Robust Non-parametric Testing, by Sinjini Banerjee et al.
Summary of Graphfm: a Comprehensive Benchmark For Graph Foundation Model, by Yuhao Xu et al.
Summary of Causality For Tabular Data Synthesis: a High-order Structure Causal Benchmark Framework, by Ruibo Tu et al.
Summary of Is Programming by Example Solved By Llms?, By Wen-ding Li et al.
Summary of Deep Learning From Strongly Mixing Observations: Sparse-penalized Regularization and Minimax Optimality, by William Kengne and Modou Wade
Summary of A Survey Of Pipeline Tools For Data Engineering, by Anthony Mbata and Yaji Sripada and Mingjun Zhong
Summary of Docsynthv2: a Practical Autoregressive Modeling For Document Generation, by Sanket Biswas et al.
Summary of Large Language Models Must Be Taught to Know What They Don’t Know, by Sanyam Kapoor et al.
Summary of Time-constrained Robust Mdps, by Adil Zouitine et al.
Summary of Cpapers: a Dataset Of Situated and Multimodal Interactive Conversations in Scientific Papers, by Anirudh Sundar et al.
Summary of A Federated Online Restless Bandit Framework For Cooperative Resource Allocation, by Jingwen Tong et al.
Summary of Asymptotic Unbiased Sample Sampling to Speed Up Sharpness-aware Minimization, by Jiaxin Deng et al.
Summary of A Novel Approach to Graph Distinction Through Geneos and Permutants, by Giovanni Bocchi and Massimo Ferri and Patrizio Frosini
Summary of Explore-go: Leveraging Exploration For Generalisation in Deep Reinforcement Learning, by Max Weltevrede et al.
Summary of Differentially Private Prototypes For Imbalanced Transfer Learning, by Dariush Wahdany et al.
Summary of Cfg++: Manifold-constrained Classifier Free Guidance For Diffusion Models, by Hyungjin Chung et al.
Summary of A Concept-based Explainability Framework For Large Multimodal Models, by Jayneel Parekh et al.
Summary of Learnable & Interpretable Model Combination in Dynamical Systems Modeling, by Tobias Thummerer and Lars Mikelsons
Summary of Balancing Molecular Information and Empirical Data in the Prediction Of Physico-chemical Properties, by Johannes Zenn et al.
Summary of Inductive Global and Local Manifold Approximation and Projection, by Jungeum Kim and Xiao Wang
Summary of Confidence Interval Estimation Of Predictive Performance in the Context Of Automl, by Konstantinos Paraschakis et al.
Summary of Counterfactual-based Root Cause Analysis For Dynamical Systems, by Juliane Weilbach et al.
Summary of Short-long Convolutions Help Hardware-efficient Linear Attention to Focus on Long Sequences, by Zicheng Liu et al.
Summary of Probing Implicit Bias in Semi-gradient Q-learning: Visualizing the Effective Loss Landscapes Via the Fokker–planck Equation, by Shuyu Yin et al.
Summary of Quantmoe-bench: Examining Post-training Quantization For Mixture-of-experts, by Pingzhi Li et al.
Summary of Attention-based Learning For Fluid State Interpolation and Editing in a Time-continuous Framework, by Bruno Roy
Summary of Minimal Communication-cost Statistical Learning, by Milad Sefidgaran et al.
Summary of Forward-euler Time-discretization For Wasserstein Gradient Flows Can Be Wrong, by Yewei Xu et al.
Summary of Runtime Freezing: Dynamic Class Loss For Multi-organ 3d Segmentation, by James Willoughby et al.
Summary of Sources Of Gain: Decomposing Performance in Conditional Average Dose Response Estimation, by Christopher Bockel-rickermann et al.
Summary of Geniu: a Restricted Data Access Unlearning For Imbalanced Data, by Chenhao Zhang et al.
Summary of An Empirical Study Of Mamba-based Language Models, by Roger Waleffe et al.
Summary of A Finite-sample Analysis Of An Actor-critic Algorithm For Mean-variance Optimization in a Discounted Mdp, by Tejaram Sangadi et al.
Summary of When Do Skills Help Reinforcement Learning? a Theoretical Analysis Of Temporal Abstractions, by Zhening Li et al.
Summary of Grounding Multimodal Large Language Models in Actions, by Andrew Szot et al.
Summary of Ablation Based Counterfactuals, by Zheng Dai et al.
Summary of Graph Transductive Defense: a Two-stage Defense For Graph Membership Inference Attacks, by Peizhi Niu et al.
Summary of Near-optimal Learning and Planning in Separated Latent Mdps, by Fan Chen et al.
Summary of Efficient Neural Common Neighbor For Temporal Graph Link Prediction, by Xiaohui Zhang et al.
Summary of A Generic Layer Pruning Method For Signal Modulation Recognition Deep Learning Models, by Yao Lu et al.
Summary of Defining and Detecting Vulnerability in Human Evaluation Guidelines: a Preliminary Study Towards Reliable Nlg Evaluation, by Jie Ruan et al.
Summary of Large Language Model Unlearning Via Embedding-corrupted Prompts, by Chris Yuhao Liu et al.
Summary of How Interpretable Are Interpretable Graph Neural Networks?, by Yongqiang Chen et al.
Summary of Better Than Random: Reliable Nlg Human Evaluation with Constrained Active Sampling, by Jie Ruan et al.
Summary of It Takes Two: on the Seamlessness Between Reward and Policy Model in Rlhf, by Taiming Lu et al.
Summary of Heuristic Learning with Graph Neural Networks: a Unified Framework For Link Prediction, by Juzheng Zhang et al.
Summary of Reinforcement Learning For High-level Strategic Control in Tower Defense Games, by Joakim Bergdahl et al.
Summary of Meta-learning Neural Procedural Biases, by Christian Raymond et al.
Summary of Blowfish: Topological and Statistical Signatures For Quantifying Ambiguity in Semantic Search, by Thomas Roland Barillot and Alex De Castro
Summary of Interpetable Target-feature Aggregation For Multi-task Learning Based on Bias-variance Analysis, by Paolo Bonetti et al.
Summary of Real Sampling: Boosting Factuality and Diversity Of Open-ended Generation Via Asymptotic Entropy, by Haw-shiuan Chang et al.
Summary of Fully Adaptive Regret-guaranteed Algorithm For Control Of Linear Quadratic Systems, by Jafar Abbaszadeh Chekan and Cedric Langbort
Summary of Personalized Product Assortment with Real-time 3d Perception and Bayesian Payoff Estimation, by Porter Jenkins et al.
Summary of Dualbind: a Dual-loss Framework For Protein-ligand Binding Affinity Prediction, by Meng Liu et al.
Summary of Self-attention-based Non-linear Basis Transformations For Compact Latent Space Modelling Of Dynamic Optical Fibre Transmission Matrices, by Yijie Zheng et al.
Summary of Unifying Interpretability and Explainability For Alzheimer’s Disease Progression Prediction, by Raja Farrukh Ali and Stephanie Milani and John Woods and Emmanuel Adenij and Ayesha Farooq and Clayton Mansel and Jeffrey Burns and William Hsu
Summary of A Critical Look at Tokenwise Reward-guided Text Generation, by Ahmad Rashid et al.
Summary of Regularizing and Aggregating Clients with Class Distribution For Personalized Federated Learning, by Gyuejeong Lee and Daeyoung Choi
Summary of From Variance to Veracity: Unbundling and Mitigating Gradient Variance in Differentiable Bundle Adjustment Layers, by Swaminathan Gurumurthy et al.
Summary of To Be Continuous, or to Be Discrete, Those Are Bits Of Questions, by Yiran Wang and Masao Utiyama
Summary of Are Objective Explanatory Evaluation Metrics Trustworthy? An Adversarial Analysis, by Prithwijit Chowdhury et al.
Summary of The Max-min Formulation Of Multi-objective Reinforcement Learning: From Theory to a Model-free Algorithm, by Giseung Park et al.
Summary of Alps: Improved Optimization For Highly Sparse One-shot Pruning For Large Language Models, by Xiang Meng et al.
Summary of Booksql: a Large Scale Text-to-sql Dataset For Accounting Domain, by Rahul Kumar and Amar Raja Dibbu and Shrutendra Harsola and Vignesh Subrahmaniam and Ashutosh Modi
Summary of Self-distillation Learning Based on Temporal-spatial Consistency For Spiking Neural Networks, by Lin Zuo and Yongqi Ding and Mengmeng Jing and Kunshan Yang and Yunqian Yu
Summary of Faithfill: Faithful Inpainting For Object Completion Using a Single Reference Image, by Rupayan Mallick et al.
Summary of Carbon Market Simulation with Adaptive Mechanism Design, by Han Wang et al.
Summary of Asymptotically Optimal Regret For Black-box Predict-then-optimize, by Samuel Tan and Peter I. Frazier
Summary of Kernelwarehouse: Rethinking the Design Of Dynamic Convolution, by Chao Li et al.
Summary of Small Scale Data-free Knowledge Distillation, by He Liu et al.
Summary of Investigating the Potential Of Using Large Language Models For Scheduling, by Deddy Jobson et al.
Summary of Gfpack++: Improving 2d Irregular Packing by Learning Gradient Field with Attention, By Tianyang Xue et al.
Summary of A Novel Method For Identifying Rice Seed Purity Based on Hybrid Machine Learning Algorithms, by Phan Thi-thu-hong et al.
Summary of Rate-preserving Reductions For Blackwell Approachability, by Christoph Dann et al.
Summary of Streamfp: Learnable Fingerprint-guided Data Selection For Efficient Stream Learning, by Tongjun Shi et al.
Summary of Mambalrp: Explaining Selective State Space Sequence Models, by Farnoush Rezaei Jafari et al.
Summary of When Is An Embedding Model More Promising Than Another?, by Maxime Darrin et al.
Summary of Equivariance Via Minimal Frame Averaging For More Symmetries and Efficiency, by Yuchao Lin et al.
Summary of Generating Human Understandable Explanations For Node Embeddings, by Zohair Shafi et al.
Summary of Optune: Efficient Online Preference Tuning, by Lichang Chen et al.
Summary of Adversarial Machine Unlearning, by Zonglin Di et al.
Summary of Treeffuser: Probabilistic Predictions Via Conditional Diffusions with Gradient-boosted Trees, by Nicolas Beltran-velez et al.
Summary of A Prisma Driven Systematic Review Of Publicly Available Datasets For Benchmark and Model Developments For Industrial Defect Detection, by Can Akbas et al.
Summary of Ai Radiologist: Revolutionizing Liver Tissue Segmentation with Convolutional Neural Networks and a Clinician-friendly Gui, by Ayman Al-kababji and Faycal Bensaali and Sarada Prasad Dakua and Yassine Himeur
Summary of Label Smoothing Improves Machine Unlearning, by Zonglin Di et al.
Summary of A Deep Learning Approach to Detect Complete Safety Equipment For Construction Workers Based on Yolov7, by Md. Shariful Islam et al.