Paper List

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

Summary of Razor: Sharpening Knowledge by Cutting Bias with Unsupervised Text Rewriting, By Shuo Yang et al.
Summary of The Pitfalls Of Memorization: When Memorization Hurts Generalization, by Reza Bayat et al.
Summary of Privacy-preserving Customer Support: a Framework For Secure and Scalable Interactions, by Anant Prakash Awasthi et al.
Summary of Simvs: Simulating World Inconsistencies For Robust View Synthesis, by Alex Trevithick et al.
Summary of Stiv: Scalable Text and Image Conditioned Video Generation, by Zongyu Lin and Wei Liu and Chen Chen and Jiasen Lu and Wenze Hu and Tsu-jui Fu and Jesse Allardice and Zhengfeng Lai and Liangchen Song and Bowen Zhang and Cha Chen and Yiran Fei and Yifan Jiang and Lezhi Li and Yizhou Sun and Kai-wei Chang and Yinfei Yang
Summary of Predictive Modeling Of Homeless Service Assignment: a Representation Learning Approach, by Khandker Sadia Rahman et al.
Summary of Lora3d: Low-rank Self-calibration Of 3d Geometric Foundation Models, by Ziqi Lu et al.
Summary of Developing a Dataset-adaptive, Normalized Metric For Machine Learning Model Assessment: Integrating Size, Complexity, and Class Imbalance, by Serzhan Ossenov
Summary of Modeling High-resolution Spatio-temporal Wind with Deep Echo State Networks and Stochastic Partial Differential Equations, by Kesen Wang et al.
Summary of Buster: Implanting Semantic Backdoor Into Text Encoder to Mitigate Nsfw Content Generation, by Xin Zhao et al.
Summary of Temporal-aware Evaluation and Learning For Temporal Graph Neural Networks, by Junwei Su et al.
Summary of Ptsbench: a Comprehensive Post-training Sparsity Benchmark Towards Algorithms and Models, by Zining Wnag et al.
Summary of Conceptsearch: Towards Efficient Program Search Using Llms For Abstraction and Reasoning Corpus (arc), by Kartik Singhal et al.
Summary of Label Distribution Learning Using the Squared Neural Family on the Probability Simplex, by Daokun Zhang et al.
Summary of Nesya: Neurosymbolic Automata, by Nikolaos Manginas et al.
Summary of Addressing Key Challenges Of Adversarial Attacks and Defenses in the Tabular Domain: a Methodological Framework For Coherence and Consistency, by Yael Itzhakev et al.
Summary of Post-training Non-uniform Quantization For Convolutional Neural Networks, by Ahmed Luqman et al.
Summary of Towards Graph Foundation Models: a Study on the Generalization Of Positional and Structural Encodings, by Billy Joe Franks et al.
Summary of Modula: Mixture Of Domain-specific and Universal Lora For Multi-task Learning, by Yufei Ma et al.
Summary of Machine Learning Algorithms For Detecting Mental Stress in College Students, by Ashutosh Singh et al.
Summary of Dsfec: Efficient and Deployable Deep Radar Object Detection, by Gayathri Dandugula et al.
Summary of Impact Of Sampling Techniques and Data Leakage on Xgboost Performance in Credit Card Fraud Detection, by Siyaxolisa Kabane
Summary of Reconstructing Deep Neural Networks: Unleashing the Optimization Potential Of Natural Gradient Descent, by Weihua Liu et al.
Summary of A Causal World Model Underlying Next Token Prediction in Gpt, by Raanan Y. Rohekar et al.
Summary of Tazza: Shuffling Neural Network Parameters For Secure and Private Federated Learning, by Kichang Lee et al.
Summary of Score-matching-based Structure Learning For Temporal Data on Networks, by Hao Chen et al.
Summary of Ahsg: Adversarial Attacks on High-level Semantics in Graph Neural Networks, by Kai Yuan et al.
Summary of Mm-poe: Multiple Choice Reasoning Via. Process Of Elimination Using Multi-modal Models, by Sayak Chakrabarty et al.
Summary of A Method For Evaluating Hyperparameter Sensitivity in Reinforcement Learning, by Jacob Adkins et al.
Summary of Rate-in: Information-driven Adaptive Dropout Rates For Improved Inference-time Uncertainty Estimation, by Tal Zeevi et al.
Summary of Reinforcement Learning Policy As Macro Regulator Rather Than Macro Placer, by Ke Xue et al.
Summary of Post-training Statistical Calibration For Higher Activation Sparsity, by Vui Seng Chua et al.
Summary of Effective Reward Specification in Deep Reinforcement Learning, by Julien Roy
Summary of Monte Carlo Tree Search Based Space Transfer For Black-box Optimization, by Shukuan Wang et al.
Summary of A New Federated Learning Framework Against Gradient Inversion Attacks, by Pengxin Guo et al.
Summary of Graph Neural Networks Are More Than Filters: Revisiting and Benchmarking From a Spectral Perspective, by Yushun Dong et al.
Summary of Epidemiological Model Calibration Via Graybox Bayesian Optimization, by Puhua Niu et al.
Summary of A Progressive Image Restoration Network For High-order Degradation Imaging in Remote Sensing, by Yujie Feng et al.
Summary of Hierarchical Split Federated Learning: Convergence Analysis and System Optimization, by Zheng Lin et al.
Summary of Crackess: a Self-prompting Crack Segmentation System For Edge Devices, by Yingchu Wang et al.
Summary of Taylor Outlier Exposure, by Kohei Fukuda et al.
Summary of Incremental Gaussian Mixture Clustering For Data Streams, by Aniket Bhanderi et al.
Summary of Maple: a Framework For Active Preference Learning Guided by Large Language Models, By Saaduddin Mahmud et al.
Summary of Parseval Regularization For Continual Reinforcement Learning, by Wesley Chung et al.
Summary of Optimization Can Learn Johnson Lindenstrauss Embeddings, by Nikos Tsikouras et al.
Summary of Moderating the Generalization Of Score-based Generative Model, by Wan Jiang et al.
Summary of A Dynamical Systems-inspired Pruning Strategy For Addressing Oversmoothing in Graph Neural Networks, by Biswadeep Chakraborty et al.
Summary of Taen: a Model-constrained Tikhonov Autoencoder Network For Forward and Inverse Problems, by Hai V. Nguyen et al.
Summary of Genai4uq: a Software For Inverse Uncertainty Quantification Using Conditional Generative Models, by Ming Fan et al.
Summary of Sequential Compression Layers For Efficient Federated Learning in Foundational Models, by Navyansh Mahla et al.
Summary of Fm2ds: Few-shot Multimodal Multihop Data Synthesis with Knowledge Distillation For Question Answering, by Amirhossein Abaskohi et al.
Summary of Deep Learning For Cross-border Transaction Anomaly Detection in Anti-money Laundering Systems, by Qian Yu et al.
Summary of Data Augmentation with Variational Autoencoder For Imbalanced Dataset, by Samuel Stocksieker et al.
Summary of Generalized Least Squares Kernelized Tensor Factorization, by Mengying Lei and Lijun Sun
Summary of Advancing Clinical Trial Outcomes Using Deep Learning and Predictive Modelling: Bridging Precision Medicine and Patient-centered Care, by Sydney Anuyah et al.
Summary of A Note on Sample Complexity Of Interactive Imitation Learning with Log Loss, by Yichen Li et al.
Summary of Moe-cap: Benchmarking Cost, Accuracy and Performance Of Sparse Mixture-of-experts Systems, by Yao Fu et al.
Summary of Optimizing Personalized Federated Learning Through Adaptive Layer-wise Learning, by Weihang Chen et al.
Summary of Enhancing Radioisotope Identification in Gamma Spectra with Transfer Learning, by Peter Lalor
Summary of Sequential Controlled Langevin Diffusions, by Junhua Chen et al.
Summary of Creative Portraiture: Exploring Creative Adversarial Networks and Conditional Creative Adversarial Networks, by Sebastian Hereu et al.
Summary of Streaming Private Continual Counting Via Binning, by Joel Daniel Andersson et al.
Summary of Covered Forest: Fine-grained Generalization Analysis Of Graph Neural Networks, by Antonis Vasileiou et al.
Summary of A Review Of Human Emotion Synthesis Based on Generative Technology, by Fei Ma et al.
Summary of Deep Learning-enhanced Preconditioning For Efficient Conjugate Gradient Solvers in Large-scale Pde Systems, by Rui Li et al.
Summary of Bridging the Gap For Test-time Multimodal Sentiment Analysis, by Zirun Guo et al.
Summary of Unlocking Trilevel Learning with Level-wise Zeroth Order Constraints: Distributed Algorithms and Provable Non-asymptotic Convergence, by Yang Jiao et al.
Summary of Generating Floorplans For Various Building Functionalities Via Latent Diffusion Model, by Mohamed R. Ibrahim et al.
Summary of Balancing Efficiency and Effectiveness: An Llm-infused Approach For Optimized Ctr Prediction, by Guoxiao Zhang et al.
Summary of Mining Limited Data Sufficiently: a Bert-inspired Approach For Csi Time Series Application in Wireless Communication and Sensing, by Zijian Zhao et al.
Summary of Stock Type Prediction Model Based on Hierarchical Graph Neural Network, by Jianhua Yao et al.
Summary of Fp=xint:a Low-bit Series Expansion Algorithm For Post-training Quantization, by Boyang Zhang et al.
Summary of Lms-autotsf: Learnable Multi-scale Decomposition and Integrated Autocorrelation For Time Series Forecasting, by Ibrahim Delibasoglu and Sanjay Chakraborty and Fredrik Heintz
Summary of Lossless Model Compression Via Joint Low-rank Factorization Optimization, by Boyang Zhang et al.
Summary of Vq4all: Efficient Neural Network Representation Via a Universal Codebook, by Juncan Deng et al.
Summary of Predicting Subway Passenger Flows Under Incident Situation with Causality, by Xiannan Huang et al.
Summary of Efficient User History Modeling with Amortized Inference For Deep Learning Recommendation Models, by Lars Hertel et al.
Summary of Safewatch: An Efficient Safety-policy Following Video Guardrail Model with Transparent Explanations, by Zhaorun Chen et al.
Summary of When Every Token Counts: Optimal Segmentation For Low-resource Language Models, by Bharath Raj S et al.
Summary of Analysing Public Transport User Sentiment on Low Resource Multilingual Data, by Rozina L. Myoya et al.
Summary of Digital Twin-empowered Voltage Control For Power Systems, by Jiachen Xu et al.
Summary of Machine Unlearning Doesn’t Do What You Think: Lessons For Generative Ai Policy, Research, and Practice, by A. Feder Cooper et al.
Summary of Diffusing Differentiable Representations, by Yash Savani et al.
Summary of Toward Ai-driven Digital Organism: Multiscale Foundation Models For Predicting, Simulating and Programming Biology at All Levels, by Le Song et al.
Summary of Extreme Automl: Analysis Of Classification, Regression, and Nlp Performance, by Edward Ratner et al.
Summary of Understanding Gradient Descent Through the Training Jacobian, by Nora Belrose et al.
Summary of In-application Defense Against Evasive Web Scans Through Behavioral Analysis, by Behzad Ousat et al.
Summary of A Physics-constrained Neural Differential Equation Framework For Data-driven Snowpack Simulation, by Andrew Charbonneau et al.
Summary of Guidance Is All You Need: Temperature-guided Reasoning in Large Language Models, by Eyad Gomaa et al.
Summary of Feature Group Tabular Transformer: a Novel Approach to Traffic Crash Modeling and Causality Analysis, by Oscar Lares et al.
Summary of Enhancing Llms For Physics Problem-solving Using Reinforcement Learning with Human-ai Feedback, by Avinash Anand et al.
Summary of Stably Unactivated Neurons in Relu Neural Networks, by Natalie Brownlowe et al.
Summary of Detecting Fake News on Social Media: a Novel Reliability Aware Machine-crowd Hybrid Intelligence-based Method, by Yidong Chai et al.
Summary of Aps-lstm: Exploiting Multi-periodicity and Diverse Spatial Dependencies For Flood Forecasting, by Jun Feng et al.
Summary of Gruvader: Sentiment-informed Stock Market Prediction, by Akhila Mamillapalli et al.
Summary of Innovative Sentiment Analysis and Prediction Of Stock Price Using Finbert, Gpt-4 and Logistic Regression: a Data-driven Approach, by Olamilekan Shobayo et al.
Summary of A Neural Model Of Rule Discovery with Relatively Short-term Sequence Memory, by Naoya Arakawa
Summary of Hardware Implementation Of Timely Reliable Bayesian Decision-making Using Memristors, by Lekai Song et al.
Summary of Mdiff: Exploiting Multimodal Score-based Diffusion Models For New Fashion Product Performance Forecasting, by Andrea Avogaro et al.
Summary of Partition Of Unity Physics-informed Neural Networks (pou-pinns): An Unsupervised Framework For Physics-informed Domain Decomposition and Mixtures Of Experts, by Arturo Rodriguez et al.