Paper List

We recommend you use the search box as this list is very long.

Summary of Interpretable Brain-inspired Representations Improve Rl Performance on Visual Navigation Tasks, by Moritz Lange et al.
Summary of Federated Bayesian Network Ensembles, by Florian Van Daalen et al.
Summary of Mlfef: Machine Learning Fusion Model with Empirical Formula to Explore the Momentum in Competitive Sports, by Ruixin Peng et al.
Summary of Stochastic Approximation with Delayed Updates: Finite-time Rates Under Markovian Sampling, by Arman Adibi et al.
Summary of Generative Kaleidoscopic Networks, by Harsh Shrivastava
Summary of Hu at Semeval-2024 Task 8a: Can Contrastive Learning Learn Embeddings to Detect Machine-generated Text?, by Shubhashis Roy Dipta and Sadat Shahriar
Summary of Generation Meets Verification: Accelerating Large Language Model Inference with Smart Parallel Auto-correct Decoding, by Hanling Yi et al.
Summary of Learning the Unlearned: Mitigating Feature Suppression in Contrastive Learning, by Jihai Zhang et al.
Summary of Microstructures and Accuracy Of Graph Recall by Large Language Models, By Yanbang Wang et al.
Summary of Easy As Abcs: Unifying Boltzmann Q-learning and Counterfactual Regret Minimization, by Luca D’amico-wong et al.
Summary of Unist: a Prompt-empowered Universal Model For Urban Spatio-temporal Prediction, by Yuan Yuan et al.
Summary of Self-guided Robust Graph Structure Refinement, by Yeonjun in et al.
Summary of Communication-efficient Distributed Learning with Local Immediate Error Compensation, by Yifei Cheng et al.
Summary of Stochastic Hessian Fittings with Lie Groups, by Xi-lin Li
Summary of Lora Training in the Ntk Regime Has No Spurious Local Minima, by Uijeong Jang et al.
Summary of Finite-time Error Analysis Of Online Model-based Q-learning with a Relaxed Sampling Model, by Han-dong Lim et al.
Summary of A Mechanistic Analysis Of a Transformer Trained on a Symbolic Multi-step Reasoning Task, by Jannik Brinkmann et al.
Summary of Generative Semi-supervised Graph Anomaly Detection, by Hezhe Qiao et al.
Summary of Spatio-temporal Few-shot Learning Via Diffusive Neural Network Generation, by Yuan Yuan et al.
Summary of Energy-efficient Edge Learning Via Joint Data Deepening-and-prefetching, by Sujin Kook et al.
Summary of Slade: Detecting Dynamic Anomalies in Edge Streams Without Labels Via Self-supervised Learning, by Jongha Lee et al.
Summary of Aicattack: Adversarial Image Captioning Attack with Attention-based Optimization, by Jiyao Li et al.
Summary of Mini-hes: a Parallelizable Second-order Latent Factor Analysis Model, by Jialiang Wang et al.
Summary of Learning the Topology and Behavior Of Discrete Dynamical Systems, by Zirou Qiu et al.
Summary of Learning Memory Kernels in Generalized Langevin Equations, by Quanjun Lang et al.
Summary of Invertible Fourier Neural Operators For Tackling Both Forward and Inverse Problems, by Da Long and Shandian Zhe
Summary of Numerical Claim Detection in Finance: a New Financial Dataset, Weak-supervision Model, and Market Analysis, by Agam Shah et al.
Summary of Prospector Heads: Generalized Feature Attribution For Large Models & Data, by Gautam Machiraju et al.
Summary of The Effectiveness Of Random Forgetting For Robust Generalization, by Vijaya Raghavan T Ramkumar et al.
Summary of Monte Carlo with Kernel-based Gibbs Measures: Guarantees For Probabilistic Herding, by Martin Rouault et al.
Summary of Compression Repair For Feedforward Neural Networks Based on Model Equivalence Evaluation, by Zihao Mo et al.
Summary of Extraction Of Nonlinearity in Neural Networks with Koopman Operator, by Naoki Sugishita et al.
Summary of Spml: a Dsl For Defending Language Models Against Prompt Attacks, by Reshabh K Sharma and Vinayak Gupta and Dan Grossman
Summary of Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance, by Chiraag Kaushik et al.
Summary of Diagonalisation Sgd: Fast & Convergent Sgd For Non-differentiable Models Via Reparameterisation and Smoothing, by Dominik Wagner et al.
Summary of Mars: Meaning-aware Response Scoring For Uncertainty Estimation in Generative Llms, by Yavuz Faruk Bakman et al.
Summary of Reinforcement Learning As a Parsimonious Alternative to Prediction Cascades: a Case Study on Image Segmentation, by Bharat Srikishan et al.
Summary of Evaluating the Effectiveness Of Index-based Treatment Allocation, by Niclas Boehmer et al.
Summary of Dynamic Multi-network Mining Of Tensor Time Series, by Kohei Obata et al.
Summary of Uncovering Latent Human Wellbeing in Language Model Embeddings, by Pedro Freire et al.
Summary of Towards Theoretical Understandings Of Self-consuming Generative Models, by Shi Fu et al.
Summary of What Evidence Do Language Models Find Convincing?, by Alexander Wan et al.
Summary of Statistical Test on Diffusion Model-based Anomaly Detection by Selective Inference, By Teruyuki Katsuoka et al.
Summary of Optimal Parallelization Strategies For Active Flow Control in Deep Reinforcement Learning-based Computational Fluid Dynamics, by Wang Jia and Hang Xu
Summary of Graph Out-of-distribution Generalization Via Causal Intervention, by Qitian Wu et al.
Summary of Large Language Model-driven Meta-structure Discovery in Heterogeneous Information Network, by Lin Chen et al.
Summary of Advancing Translation Preference Modeling with Rlhf: a Step Towards Cost-effective Solution, by Nuo Xu et al.
Summary of Empirical Density Estimation Based on Spline Quasi-interpolation with Applications to Copulas Clustering Modeling, by Cristiano Tamborrino et al.
Summary of A Temporally Disentangled Contrastive Diffusion Model For Spatiotemporal Imputation, by Yakun Chen et al.
Summary of Continual Learning on Graphs: Challenges, Solutions, and Opportunities, by Xikun Zhang et al.
Summary of Polypnextlstm: a Lightweight and Fast Polyp Video Segmentation Network Using Convnext and Convlstm, by Debayan Bhattacharya et al.
Summary of Revisiting Zeroth-order Optimization For Memory-efficient Llm Fine-tuning: a Benchmark, by Yihua Zhang et al.
Summary of Simplifying Hyperparameter Tuning in Online Machine Learning — the Spotrivergui, by Thomas Bartz-beielstein
Summary of Self-evolving Autoencoder Embedded Q-network, by J. Senthilnath et al.
Summary of Logical Closed Loop: Uncovering Object Hallucinations in Large Vision-language Models, by Junfei Wu et al.
Summary of Discrete Neural Algorithmic Reasoning, by Gleb Rodionov et al.
Summary of In-context Learning with Transformers: Softmax Attention Adapts to Function Lipschitzness, by Liam Collins et al.
Summary of Towards Versatile Graph Learning Approach: From the Perspective Of Large Language Models, by Lanning Wei et al.
Summary of Programmatic Reinforcement Learning: Navigating Gridworlds, by Guruprerana Shabadi et al.
Summary of Dynamic Planning in Hierarchical Active Inference, by Matteo Priorelli and Ivilin Peev Stoianov
Summary of Interpretable Short-term Load Forecasting Via Multi-scale Temporal Decomposition, by Yuqi Jiang et al.
Summary of Learning Conditional Invariances Through Non-commutativity, by Abhra Chaudhuri et al.
Summary of Challenging the Black Box: a Comprehensive Evaluation Of Attribution Maps Of Cnn Applications in Agriculture and Forestry, by Lars Nieradzik et al.
Summary of Ransomware Detection Using Stacked Autoencoder For Feature Selection, by Mike Nkongolo and Mahmut Tokmak
Summary of A Practical Method For Generating String Counterfactuals, by Matan Avitan et al.
Summary of Probabilistic Routing For Graph-based Approximate Nearest Neighbor Search, by Kejing Lu et al.
Summary of Variational Entropy Search For Adjusting Expected Improvement, by Nuojin Cheng and Stephen Becker
Summary of Multi Task Inverse Reinforcement Learning For Common Sense Reward, by Neta Glazer et al.
Summary of Data-driven Stochastic Ac-opf Using Gaussian Processes, by Mile Mitrovic
Summary of Reinforcement Learning to Maximise Wind Turbine Energy Generation, by Daniel Soler et al.
Summary of Random Projection Neural Networks Of Best Approximation: Convergence Theory and Practical Applications, by Gianluca Fabiani
Summary of K-semstamp: a Clustering-based Semantic Watermark For Detection Of Machine-generated Text, by Abe Bohan Hou et al.
Summary of Graphkd: Exploring Knowledge Distillation Towards Document Object Detection with Structured Graph Creation, by Ayan Banerjee et al.
Summary of Evaluating the Stability Of Deep Learning Latent Feature Spaces, by Ademide O. Mabadeje and Michael J. Pyrcz
Summary of Aligning Modalities in Vision Large Language Models Via Preference Fine-tuning, by Yiyang Zhou et al.
Summary of A Multispectral Automated Transfer Technique (matt) For Machine-driven Image Labeling Utilizing the Segment Anything Model (sam), by James E. Gallagher et al.
Summary of Loretta: Low-rank Economic Tensor-train Adaptation For Ultra-low-parameter Fine-tuning Of Large Language Models, by Yifan Yang et al.
Summary of Optex: Expediting First-order Optimization with Approximately Parallelized Iterations, by Yao Shu et al.
Summary of Attractor Memory For Long-term Time Series Forecasting: a Chaos Perspective, by Jiaxi Hu et al.
Summary of Improved Indoor Localization with Machine Learning Techniques For Iot Applications, by M.w.p. Maduranga
Summary of Infuserki: Enhancing Large Language Models with Knowledge Graphs Via Infuser-guided Knowledge Integration, by Fali Wang et al.
Summary of A Curious Case Of Searching For the Correlation Between Training Data and Adversarial Robustness Of Transformer Textual Models, by Cuong Dang et al.
Summary of Leia: Facilitating Cross-lingual Knowledge Transfer in Language Models with Entity-based Data Augmentation, by Ikuya Yamada and Ryokan Ri
Summary of Beyond Generalization: a Survey Of Out-of-distribution Adaptation on Graphs, by Shuhan Liu et al.
Summary of Trust Regions For Explanations Via Black-box Probabilistic Certification, by Amit Dhurandhar et al.
Summary of Efficient Low-rank Matrix Estimation, Experimental Design, and Arm-set-dependent Low-rank Bandits, by Kyoungseok Jang et al.
Summary of How to Make the Gradients Small Privately: Improved Rates For Differentially Private Non-convex Optimization, by Andrew Lowy et al.
Summary of Uncertainty Quantification Of Graph Convolution Neural Network Models Of Evolving Processes, by Jeremiah Hauth et al.
Summary of Minimally Supervised Topological Projections Of Self-organizing Maps For Phase Of Flight Identification, by Zimeng Lyu et al.
Summary of Maintaining Adversarial Robustness in Continuous Learning, by Xiaolei Ru et al.
Summary of Achieving Linear Speedup in Asynchronous Federated Learning with Heterogeneous Clients, by Xiaolu Wang et al.
Summary of Adadagrad: Adaptive Batch Size Schemes For Adaptive Gradient Methods, by Tim Tsz-kit Lau et al.
Summary of Adaptive Split Balancing For Optimal Random Forest, by Yuqian Zhang et al.
Summary of Heal: Brain-inspired Hyperdimensional Efficient Active Learning, by Yang Ni et al.
Summary of Neural Networks with (low-precision) Polynomial Approximations: New Insights and Techniques For Accuracy Improvement, by Chi Zhang et al.
Summary of Zerog: Investigating Cross-dataset Zero-shot Transferability in Graphs, by Yuhan Li et al.
Summary of Be Persistent: Towards a Unified Solution For Mitigating Shortcuts in Deep Learning, by Hadi M. Dolatabadi et al.
Summary of Aligning Large Language Models by On-policy Self-judgment, By Sangkyu Lee et al.
Summary of Learning with Imbalanced Noisy Data by Preventing Bias in Sample Selection, By Huafeng Liu et al.
Summary of Debiased Offline Representation Learning For Fast Online Adaptation in Non-stationary Dynamics, by Xinyu Zhang et al.