Paper List

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Summary of Rpmixer: Shaking Up Time Series Forecasting with Random Projections For Large Spatial-temporal Data, by Chin-chia Michael Yeh et al.
Summary of Rethinking Self-distillation: Label Averaging and Enhanced Soft Label Refinement with Partial Labels, by Hyeonsu Jeong and Hye Won Chung
Summary of Developing An Optimal Model For Predicting the Severity Of Wheat Stem Rust (case Study Of Arsi and Bale Zone), by Tewodrose Altaye
Summary of Backdoor Attack Against One-class Sequential Anomaly Detection Models, by He Cheng and Shuhan Yuan
Summary of Thompson Sampling in Partially Observable Contextual Bandits, by Hongju Park and Mohamad Kazem Shirani Faradonbeh
Summary of An Evaluation Of Real-time Adaptive Sampling Change Point Detection Algorithm Using Kcusum, by Vijayalakshmi Saravanan et al.
Summary of Discrete Probabilistic Inference As Control in Multi-path Environments, by Tristan Deleu et al.
Summary of Interpretable Generative Adversarial Imitation Learning, by Wenliang Liu et al.
Summary of Hi-gan: Hierarchical Inpainting Gan with Auxiliary Inputs For Combined Rgb and Depth Inpainting, by Ankan Dash et al.
Summary of What to Do When Your Discrete Optimization Is the Size Of a Neural Network?, by Hugo Silva and Martha White
Summary of Large Language Models For Forecasting and Anomaly Detection: a Systematic Literature Review, by Jing Su et al.
Summary of Exploration-driven Policy Optimization in Rlhf: Theoretical Insights on Efficient Data Utilization, by Yihan Du et al.
Summary of Prompt-based Bias Calibration For Better Zero/few-shot Learning Of Language Models, by Kang He et al.
Summary of Can We Soft Prompt Llms For Graph Learning Tasks?, by Zheyuan Liu et al.
Summary of Transductive Learning Is Compact, by Julian Asilis et al.
Summary of Biomistral: a Collection Of Open-source Pretrained Large Language Models For Medical Domains, by Yanis Labrak et al.
Summary of Interpreting Clip with Sparse Linear Concept Embeddings (splice), by Usha Bhalla et al.
Summary of Revisiting Experience Replayable Conditions, by Taisuke Kobayashi
Summary of Datadreamer: a Tool For Synthetic Data Generation and Reproducible Llm Workflows, by Ajay Patel et al.
Summary of Subgraph-level Universal Prompt Tuning, by Junhyun Lee et al.
Summary of Pretext Training Algorithms For Event Sequence Data, by Yimu Wang et al.
Summary of Logelectra: Self-supervised Anomaly Detection For Unstructured Logs, by Yuuki Yamanaka et al.
Summary of Manifpt: Defining and Analyzing Fingerprints Of Generative Models, by Hae Jin Song et al.
Summary of Uncertainty Quantification For In-context Learning Of Large Language Models, by Chen Ling et al.
Summary of Fedanchor: Enhancing Federated Semi-supervised Learning with Label Contrastive Loss For Unlabeled Clients, by Xinchi Qiu et al.
Summary of Self-consistent Validation For Machine Learning Electronic Structure, by Gengyuan Hu et al.
Summary of Multi-excitation Projective Simulation with a Many-body Physics Inspired Inductive Bias, by Philip A. Lemaitre et al.
Summary of Bitdelta: Your Fine-tune May Only Be Worth One Bit, by James Liu et al.
Summary of Samformer: Unlocking the Potential Of Transformers in Time Series Forecasting with Sharpness-aware Minimization and Channel-wise Attention, by Romain Ilbert et al.
Summary of Bridging Associative Memory and Probabilistic Modeling, by Rylan Schaeffer et al.
Summary of Recovering the Pre-fine-tuning Weights Of Generative Models, by Eliahu Horwitz et al.
Summary of Rewards-in-context: Multi-objective Alignment Of Foundation Models with Dynamic Preference Adjustment, by Rui Yang et al.
Summary of Self-play Fine-tuning Of Diffusion Models For Text-to-image Generation, by Huizhuo Yuan and Zixiang Chen and Kaixuan Ji and Quanquan Gu
Summary of Hierarchical State Space Models For Continuous Sequence-to-sequence Modeling, by Raunaq Bhirangi et al.
Summary of Q-star Meets Scalable Posterior Sampling: Bridging Theory and Practice Via Hyperagent, by Yingru Li et al.
Summary of Simple, Unified Analysis Of Johnson-lindenstrauss with Applications, by Yingru Li
Summary of Parametric Learning Of Time-advancement Operators For Unstable Flame Evolution, by Rixin Yu and Erdzan Hodzic
Summary of A Dynamical View Of the Question Of Why, by Mehdi Fatemi and Sindhu Gowda
Summary of A Data-driven Supervised Machine Learning Approach to Estimating Global Ambient Air Pollution Concentrations with Associated Prediction Intervals, by Liam J Berrisford et al.
Summary of Personalized Federated Learning For Statistical Heterogeneity, by Muhammad Firdaus and Kyung-hyune Rhee
Summary of A Strongreject For Empty Jailbreaks, by Alexandra Souly et al.
Summary of Susfl: Energy-aware Federated Learning-based Monitoring For Sustainable Smart Farms, by Dian Chen et al.
Summary of Information Capacity Regret Bounds For Bandits with Mediator Feedback, by Khaled Eldowa et al.
Summary of Nyctale: Neuro-evidence Transformer For Adaptive and Personalized Lung Nodule Invasiveness Prediction, by Sadaf Khademi et al.
Summary of Quick: Quantization-aware Interleaving and Conflict-free Kernel For Efficient Llm Inference, by Taesu Kim et al.
Summary of Review Of the Learning-based Camera and Lidar Simulation Methods For Autonomous Driving Systems, by Hamed Haghighi et al.
Summary of Pics: Pipeline For Image Captioning and Search, by Grant Rosario et al.
Summary of Mim-refiner: a Contrastive Learning Boost From Intermediate Pre-trained Representations, by Benedikt Alkin and Lukas Miklautz and Sepp Hochreiter and Johannes Brandstetter
Summary of Classification Diffusion Models: Revitalizing Density Ratio Estimation, by Shahar Yadin et al.
Summary of Adaptive Federated Learning in Heterogeneous Wireless Networks with Independent Sampling, by Jiaxiang Geng et al.
Summary of Parameter-tuning-free Data Entry Error Unlearning with Adaptive Selective Synaptic Dampening, by Stefan Schoepf et al.
Summary of Selective Reflection-tuning: Student-selected Data Recycling For Llm Instruction-tuning, by Ming Li et al.
Summary of Deep Learning Based Situation Awareness For Multiple Missiles Evasion, by Edvards Scukins et al.
Summary of Towards Reducing Diagnostic Errors with Interpretable Risk Prediction, by Denis Jered Mcinerney et al.
Summary of Generating Visual Stimuli From Eeg Recordings Using Transformer-encoder Based Eeg Encoder and Gan, by Rahul Mishra et al.
Summary of Nonlinear Spiked Covariance Matrices and Signal Propagation in Deep Neural Networks, by Zhichao Wang et al.
Summary of Ges: Generalized Exponential Splatting For Efficient Radiance Field Rendering, by Abdullah Hamdi et al.
Summary of Is Continual Learning Ready For Real-world Challenges?, by Theodora Kontogianni et al.
Summary of Benchmarking Federated Strategies in Peer-to-peer Federated Learning For Biomedical Data, by Jose L. Salmeron et al.
Summary of Tracking Changing Probabilities Via Dynamic Learners, by Omid Madani
Summary of Openmathinstruct-1: a 1.8 Million Math Instruction Tuning Dataset, by Shubham Toshniwal et al.
Summary of Large Scale Constrained Clustering with Reinforcement Learning, by Benedikt Schesch et al.
Summary of Reward Generalization in Rlhf: a Topological Perspective, by Tianyi Qiu et al.
Summary of Crafting a Good Prompt or Providing Exemplary Dialogues? a Study Of In-context Learning For Persona-based Dialogue Generation, by Jiashu Pu et al.
Summary of Why Are Sensitive Functions Hard For Transformers?, by Michael Hahn et al.
Summary of Hierarchy Representation Of Data in Machine Learnings, by Han Yegang et al.
Summary of Accelerating Parallel Sampling Of Diffusion Models, by Zhiwei Tang et al.
Summary of Data Augmentation and Transfer Learning Approaches Applied to Facial Expressions Recognition, by Enrico Randellini and Leonardo Rigutini and Claudio Sacca’
Summary of Fast Vocabulary Transfer For Language Model Compression, by Leonidas Gee and Andrea Zugarini and Leonardo Rigutini and Paolo Torroni
Summary of Symmetry-breaking Augmentations For Ad Hoc Teamwork, by Ravi Hammond et al.
Summary of Loraretriever: Input-aware Lora Retrieval and Composition For Mixed Tasks in the Wild, by Ziyu Zhao et al.
Summary of Risk-sensitive Soft Actor-critic For Robust Deep Reinforcement Learning Under Distribution Shifts, by Tobias Enders et al.
Summary of Privacy Attacks in Decentralized Learning, by Abdellah El Mrini et al.
Summary of Self-augmented In-context Learning For Unsupervised Word Translation, by Yaoyiran Li et al.
Summary of Diffusion Models Meet Contextual Bandits with Large Action Spaces, by Imad Aouali
Summary of Rs-dpo: a Hybrid Rejection Sampling and Direct Preference Optimization Method For Alignment Of Large Language Models, by Saeed Khaki et al.
Summary of Negative Impact Of Heavy-tailed Uncertainty and Error Distributions on the Reliability Of Calibration Statistics For Machine Learning Regression Tasks, by Pascal Pernot
Summary of Short-form Videos and Mental Health: a Knowledge-guided Neural Topic Model, by Jiaheng Xie et al.
Summary of How Flawed Is Ece? An Analysis Via Logit Smoothing, by Muthu Chidambaram et al.
Summary of Balancing the Causal Effects in Class-incremental Learning, by Junhao Zheng et al.
Summary of Optimal Parameter and Neuron Pruning For Out-of-distribution Detection, by Chao Chen et al.
Summary of Some Targets Are Harder to Identify Than Others: Quantifying the Target-dependent Membership Leakage, by Achraf Azize et al.
Summary of Class-balanced and Reinforced Active Learning on Graphs, by Chengcheng Yu et al.
Summary of Criterion Collapse and Loss Distribution Control, by Matthew J. Holland
Summary of Mc-dbn: a Deep Belief Network-based Model For Modality Completion, by Zihong Luo et al.
Summary of Examining Pathological Bias in a Generative Adversarial Network Discriminator: a Case Study on a Stylegan3 Model, by Alvin Grissom Ii et al.
Summary of Utilizing Gans For Fraud Detection: Model Training with Synthetic Transaction Data, by Mengran Zhu et al.
Summary of All in One and One For All: a Simple Yet Effective Method Towards Cross-domain Graph Pretraining, by Haihong Zhao et al.
Summary of Performative Reinforcement Learning in Gradually Shifting Environments, by Ben Rank et al.
Summary of Recommendations For Baselines and Benchmarking Approximate Gaussian Processes, by Sebastian W. Ober et al.
Summary of Covidhealth: a Benchmark Twitter Dataset and Machine Learning Based Web Application For Classifying Covid-19 Discussions, by Mahathir Mohammad Bishal et al.
Summary of Do Causal Predictors Generalize Better to New Domains?, by Vivian Y. Nastl and Moritz Hardt
Summary of Lapdoc: Layout-aware Prompting For Documents, by Marcel Lamott et al.
Summary of Explaining Kernel Clustering Via Decision Trees, by Maximilian Fleissner et al.
Summary of Recurrent Reinforcement Learning with Memoroids, by Steven Morad et al.
Summary of Generative Representational Instruction Tuning, by Niklas Muennighoff et al.
Summary of Buster: a “business Transaction Entity Recognition” Dataset, by Andrea Zugarini and Andrew Zamai and Marco Ernandes and Leonardo Rigutini
Summary of Generative Ai in the Construction Industry: a State-of-the-art Analysis, by Ridwan Taiwo et al.
Summary of Fedlion: Faster Adaptive Federated Optimization with Fewer Communication, by Zhiwei Tang et al.
Summary of Multi-word Tokenization For Sequence Compression, by Leonidas Gee et al.