Paper List

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Summary of Transformers Are Ssms: Generalized Models and Efficient Algorithms Through Structured State Space Duality, by Tri Dao et al.
Summary of Graph External Attention Enhanced Transformer, by Jianqing Liang and Min Chen and Jiye Liang
Summary of Neural Network Verification with Branch-and-bound For General Nonlinearities, by Zhouxing Shi et al.
Summary of Recurrent Neural Networks: Vanishing and Exploding Gradients Are Not the End Of the Story, by Nicolas Zucchet et al.
Summary of Shape Constraints in Symbolic Regression Using Penalized Least Squares, by Viktor Martinek and Julia Reuter and Ophelia Frotscher and Sanaz Mostaghim and Markus Richter and Roland Herzog
Summary of Rough Transformers: Lightweight and Continuous Time Series Modelling Through Signature Patching, by Fernando Moreno-pino et al.
Summary of Pursuing Overall Welfare in Federated Learning Through Sequential Decision Making, by Seok-ju Hahn et al.
Summary of Online Convex Optimisation: the Optimal Switching Regret For All Segmentations Simultaneously, by Stephen Pasteris et al.
Summary of Rethinking Open-world Semi-supervised Learning: Distribution Mismatch and Inductive Inference, by Seongheon Park et al.
Summary of Einspace: Searching For Neural Architectures From Fundamental Operations, by Linus Ericsson et al.
Summary of Outliers and Calibration Sets Have Diminishing Effect on Quantization Of Modern Llms, by Davide Paglieri et al.
Summary of Self-augmented Preference Optimization: Off-policy Paradigms For Language Model Alignment, by Yueqin Yin and Zhendong Wang and Yujia Xie and Weizhu Chen and Mingyuan Zhou
Summary of Flow Matching Achieves Almost Minimax Optimal Convergence, by Kenji Fukumizu et al.
Summary of Enhancing Efficiency Of Safe Reinforcement Learning Via Sample Manipulation, by Shangding Gu et al.
Summary of Veni, Vindy, Vici: a Variational Reduced-order Modeling Framework with Uncertainty Quantification, by Paolo Conti et al.
Summary of Sheaf Hypernetworks For Personalized Federated Learning, by Bao Nguyen et al.
Summary of Fast Yet Safe: Early-exiting with Risk Control, by Metod Jazbec et al.
Summary of Concentration Bounds For Optimized Certainty Equivalent Risk Estimation, by Ayon Ghosh et al.
Summary of Effective Interplay Between Sparsity and Quantization: From Theory to Practice, by Simla Burcu Harma et al.
Summary of Pual: a Classifier on Trifurcate Positive-unlabeled Data, by Xiaoke Wang et al.
Summary of Amortizing Intractable Inference in Diffusion Models For Vision, Language, and Control, by Siddarth Venkatraman et al.
Summary of Lcq: Low-rank Codebook Based Quantization For Large Language Models, by Wen-pu Cai et al.
Summary of Sayself: Teaching Llms to Express Confidence with Self-reflective Rationales, by Tianyang Xu et al.
Summary of Neural Gaussian Scale-space Fields, by Felix Mujkanovic et al.
Summary of Adv-kd: Adversarial Knowledge Distillation For Faster Diffusion Sampling, by Kidist Amde Mekonnen et al.
Summary of No-regret Learning For Fair Multi-agent Social Welfare Optimization, by Mengxiao Zhang et al.
Summary of Conditioning Gan Without Training Dataset, by Kidist Amde Mekonnen
Summary of Unleashing the Potential Of Diffusion Models For Incomplete Data Imputation, by Hengrui Zhang et al.
Summary of Enhancing Counterfactual Image Generation Using Mahalanobis Distance with Distribution Preferences in Feature Space, by Yukai Zhang et al.
Summary of In-context Decision Transformer: Reinforcement Learning Via Hierarchical Chain-of-thought, by Sili Huang et al.
Summary of Cyclic Image Generation Using Chaotic Dynamics, by Takaya Tanaka et al.
Summary of Learning on Large Graphs Using Intersecting Communities, by Ben Finkelshtein et al.
Summary of Maximum Temperature Prediction Using Remote Sensing Data Via Convolutional Neural Network, by Lorenzo Innocenti et al.
Summary of Federated Random Forest For Partially Overlapping Clinical Data, by Youngjun Park et al.
Summary of Trajectory Forecasting Through Low-rank Adaptation Of Discrete Latent Codes, by Riccardo Benaglia et al.
Summary of Opentensor: Reproducing Faster Matrix Multiplication Discovering Algorithms, by Yiwen Sun et al.
Summary of Information Theoretic Text-to-image Alignment, by Chao Wang et al.
Summary of Share Your Secrets For Privacy! Confidential Forecasting with Vertical Federated Learning, by Aditya Shankar et al.
Summary of Improving Generalization and Convergence by Enhancing Implicit Regularization, By Mingze Wang et al.
Summary of Reinforcement Learning For Sociohydrology, by Tirthankar Roy et al.
Summary of Intersectional Unfairness Discovery, by Gezheng Xu et al.
Summary of Gs-phong: Meta-learned 3d Gaussians For Relightable Novel View Synthesis, by Yumeng He et al.
Summary of Ovis: Structural Embedding Alignment For Multimodal Large Language Model, by Shiyin Lu et al.
Summary of Model Interpretation and Explainability: Towards Creating Transparency in Prediction Models, by Donald Kridel et al.
Summary of Selective Knowledge Sharing For Personalized Federated Learning Under Capacity Heterogeneity, by Zheng Wang et al.
Summary of Link: Learning Joint Representations Of Design and Performance Spaces Through Contrastive Learning For Mechanism Synthesis, by Amin Heyrani Nobari et al.
Summary of Generalized Semi-supervised Learning Via Self-supervised Feature Adaptation, by Jiachen Liang et al.
Summary of Deep Learning Without Weight Symmetry, by Li Ji-an et al.
Summary of Masked Language Modeling Becomes Conditional Density Estimation For Tabular Data Synthesis, by Seunghwan An et al.
Summary of Advancing Financial Risk Prediction Through Optimized Lstm Model Performance and Comparative Analysis, by Ke Xu et al.
Summary of Searching For Internal Symbols Underlying Deep Learning, by Jung H. Lee et al.
Summary of Vision-language Meets the Skeleton: Progressively Distillation with Cross-modal Knowledge For 3d Action Representation Learning, by Yang Chen et al.
Summary of Superfast Selection For Decision Tree Algorithms, by Huaduo Wang and Gopal Gupta
Summary of Sparse-proxskip: Accelerated Sparse-to-sparse Training in Federated Learning, by Georg Meinhardt et al.
Summary of “forgetting” in Machine Learning and Beyond: a Survey, by Alyssa Shuang Sha et al.
Summary of Stochastic Optimal Control For Diffusion Bridges in Function Spaces, by Byoungwoo Park et al.
Summary of Linear Contracts in Multitasking: Robustness, Uniformity, and Learning, by Shiliang Zuo
Summary of Heterophilous Distribution Propagation For Graph Neural Networks, by Zhuonan Zheng et al.
Summary of Shotluck Holmes: a Family Of Efficient Small-scale Large Language Vision Models For Video Captioning and Summarization, by Richard Luo et al.
Summary of Reward-based Input Construction For Cross-document Relation Extraction, by Byeonghu Na et al.
Summary of Sign Is Not a Remedy: Multiset-to-multiset Message Passing For Learning on Heterophilic Graphs, by Langzhang Liang et al.
Summary of Weak Robust Compatibility Between Learning Algorithms and Counterfactual Explanation Generation Algorithms, by Ao Xu et al.
Summary of Position Coupling: Improving Length Generalization Of Arithmetic Transformers Using Task Structure, by Hanseul Cho et al.
Summary of Provably Efficient Interactive-grounded Learning with Personalized Reward, by Mengxiao Zhang et al.
Summary of Spot: Text Source Prediction From Originality Score Thresholding, by Edouard Yvinec et al.
Summary of How Multilingual Are Large Language Models Fine-tuned For Translation?, by Aquia Richburg and Marine Carpuat
Summary of Deep Modeling Of Non-gaussian Aleatoric Uncertainty, by Aastha Acharya et al.
Summary of Mitigating the Impact Of Labeling Errors on Training Via Rockafellian Relaxation, by Louis L. Chen et al.
Summary of Wavecastnet: An Ai-enabled Wavefield Forecasting Framework For Earthquake Early Warning, by Dongwei Lyu et al.
Summary of Aquatic Navigation: a Challenging Benchmark For Deep Reinforcement Learning, by Davide Corsi et al.
Summary of Sleepernets: Universal Backdoor Poisoning Attacks Against Reinforcement Learning Agents, by Ethan Rathbun et al.
Summary of Q-learning As a Monotone Scheme, by Lingyi Yang
Summary of Fully Unconstrained Online Learning, by Ashok Cutkosky and Zakaria Mhammedi
Summary of On the Connection Between Non-negative Matrix Factorization and Latent Dirichlet Allocation, by Benedikt Geiger et al.
Summary of Perplexed by Perplexity: Perplexity-based Data Pruning with Small Reference Models, By Zachary Ankner et al.
Summary of Towards a General Recipe For Combinatorial Optimization with Multi-filter Gnns, by Frederik Wenkel et al.
Summary of Uncertainty Quantification For Deep Learning, by Peter Jan Van Leeuwen and J. Christine Chiu and C. Kevin Yang
Summary of Diffusion Actor-critic: Formulating Constrained Policy Iteration As Diffusion Noise Regression For Offline Reinforcement Learning, by Linjiajie Fang et al.
Summary of Certifying Global Robustness For Deep Neural Networks, by You Li et al.
Summary of Can Machine Learning Assist in Diagnosis Of Primary Immune Thrombocytopenia? a Feasibility Study, by Haroon Miah et al.
Summary of Generative Ai For Deep Reinforcement Learning: Framework, Analysis, and Use Cases, by Geng Sun et al.
Summary of Enhancing Generative Molecular Design Via Uncertainty-guided Fine-tuning Of Variational Autoencoders, by a N M Nafiz Abeer et al.
Summary of The Point Of View Of a Sentiment: Towards Clinician Bias Detection in Psychiatric Notes, by Alissa A. Valentine et al.
Summary of Class-based Time Series Data Augmentation to Mitigate Extreme Class Imbalance For Solar Flare Prediction, by Junzhi Wen et al.
Summary of Back to the Basics on Predicting Transfer Performance, by Levy Chaves et al.
Summary of Exploring the Practicality Of Federated Learning: a Survey Towards the Communication Perspective, by Khiem Le et al.
Summary of Enhancing Performance For Highly Imbalanced Medical Data Via Data Regularization in a Federated Learning Setting, by Georgios Tsoumplekas et al.
Summary of Sharpness-aware Minimization Enhances Feature Quality Via Balanced Learning, by Jacob Mitchell Springer et al.
Summary of Deep Learning For Computing Convergence Rates Of Markov Chains, by Yanlin Qu et al.
Summary of Knockout: a Simple Way to Handle Missing Inputs, by Minh Nguyen et al.
Summary of Algorithmic Fairness in Performative Policy Learning: Escaping the Impossibility Of Group Fairness, by Seamus Somerstep et al.
Summary of Fully-inductive Node Classification on Arbitrary Graphs, by Jianan Zhao et al.
Summary of Understanding Encoder-decoder Structures in Machine Learning Using Information Measures, by Jorge F. Silva and Victor Faraggi and Camilo Ramirez and Alvaro Egana and Eduardo Pavez
Summary of Statistical Properties Of Robust Satisficing, by Zhiyi Li et al.
Summary of Scaling Laws For the Value Of Individual Data Points in Machine Learning, by Ian Covert et al.
Summary of Entire-id: An Extensive and Diverse Dataset For Person Re-identification, by Serdar Yildiz et al.
Summary of Performance Of Npg in Countable State-space Average-cost Rl, by Yashaswini Murthy et al.
Summary of Sparsity Regularization Via Tree-structured Environments For Disentangled Representations, by Elliot Layne et al.
Summary of Mteb-french: Resources For French Sentence Embedding Evaluation and Analysis, by Mathieu Ciancone et al.
Summary of Policy Trees For Prediction: Interpretable and Adaptive Model Selection For Machine Learning, by Dimitris Bertsimas and Matthew Peroni