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