Paper List

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Summary of Neural Network Matrix Product Operator: a Multi-dimensionally Integrable Machine Learning Potential, by Kentaro Hino and Yuki Kurashige
Summary of Ragraph: a General Retrieval-augmented Graph Learning Framework, by Xinke Jiang et al.
Summary of Can Language Models Perform Robust Reasoning in Chain-of-thought Prompting with Noisy Rationales?, by Zhanke Zhou et al.
Summary of Identifiability Guarantees For Causal Disentanglement From Purely Observational Data, by Ryan Welch et al.
Summary of Emgbench: Benchmarking Out-of-distribution Generalization and Adaptation For Electromyography, by Jehan Yang et al.
Summary of Adaptive Alignment: Dynamic Preference Adjustments Via Multi-objective Reinforcement Learning For Pluralistic Ai, by Hadassah Harland et al.
Summary of An Application Of the Holonomic Gradient Method to the Neural Tangent Kernel, by Akihiro Sakoda et al.
Summary of Sample-efficient Agnostic Boosting, by Udaya Ghai and Karan Singh
Summary of Online Consistency Of the Nearest Neighbor Rule, by Sanjoy Dasgupta and Geelon So
Summary of Anytime-constrained Equilibria in Polynomial Time, by Jeremy Mcmahan
Summary of Deep Convolutional Neural Networks on Multiclass Classification Of Three-dimensional Brain Images For Parkinson’s Disease Stage Prediction, by Guan-hua Huang et al.
Summary of Projected Neural Differential Equations For Learning Constrained Dynamics, by Alistair White et al.
Summary of Local Superior Soups: a Catalyst For Model Merging in Cross-silo Federated Learning, by Minghui Chen et al.
Summary of Provable Benefit Of Cutout and Cutmix For Feature Learning, by Junsoo Oh et al.
Summary of Wide Two-layer Networks Can Learn From Adversarial Perturbations, by Soichiro Kumano et al.
Summary of Towards Dynamic Message Passing on Graphs, by Junshu Sun et al.
Summary of Rethinking Inverse Reinforcement Learning: From Data Alignment to Task Alignment, by Weichao Zhou et al.
Summary of Automatically Learning Hybrid Digital Twins Of Dynamical Systems, by Samuel Holt and Tennison Liu and Mihaela Van Der Schaar
Summary of Zero-shot Class Unlearning Via Layer-wise Relevance Analysis and Neuronal Path Perturbation, by Wenhan Chang et al.
Summary of Aggregate-and-adapt Natural Language Prompts For Downstream Generalization Of Clip, by Chen Huang and Skyler Seto and Samira Abnar and David Grangier and Navdeep Jaitly and Josh Susskind
Summary of Towards Reliable Alignment: Uncertainty-aware Rlhf, by Debangshu Banerjee et al.
Summary of Ocean: Offline Chain-of-thought Evaluation and Alignment in Large Language Models, by Junda Wu et al.
Summary of A Non-monolithic Policy Approach Of Offline-to-online Reinforcement Learning, by Jaeyoon Kim et al.
Summary of Multi-fidelity Machine Learning For Uncertainty Quantification and Optimization, by Ruda Zhang and Negin Alemazkoor
Summary of Keep on Swimming: Real Attackers Only Need Partial Knowledge Of a Multi-model System, by Julian Collado et al.
Summary of Causality-driven Audits Of Model Robustness, by Nathan Drenkow et al.
Summary of Dash: Warm-starting Neural Network Training in Stationary Settings Without Loss Of Plasticity, by Baekrok Shin et al.
Summary of Kernel-based Function Approximation For Average Reward Reinforcement Learning: An Optimist No-regret Algorithm, by Sattar Vakili and Julia Olkhovskaya
Summary of Tangent Space Causal Inference: Leveraging Vector Fields For Causal Discovery in Dynamical Systems, by Kurt Butler et al.
Summary of Development and Comparative Analysis Of Machine Learning Models For Hypoxemia Severity Triage in Cbrne Emergency Scenarios Using Physiological and Demographic Data From Medical-grade Devices, by Santino Nanini et al.
Summary of The Belief State Transformer, by Edward S. Hu et al.
Summary of Tiny Transformers Excel at Sentence Compression, by Peter Belcak et al.
Summary of Dynamic Strategy Planning For Efficient Question Answering with Large Language Models, by Tanmay Parekh et al.
Summary of Generative Forecasting Of Brain Activity Enhances Alzheimer’s Classification and Interpretation, by Yutong Gao et al.
Summary of Ra-pbrl: Provably Efficient Risk-aware Preference-based Reinforcement Learning, by Yujie Zhao et al.
Summary of Prosody As a Teaching Signal For Agent Learning: Exploratory Studies and Algorithmic Implications, by Matilda Knierim et al.
Summary of Bioncere: Non-contrastive Enhancement For Relation Extraction in Biomedical Texts, by Farshad Noravesh
Summary of End-to-end Ontology Learning with Large Language Models, by Andy Lo et al.
Summary of How Do Flow Matching Models Memorize and Generalize in Sample Data Subspaces?, by Weiguo Gao and Ming Li
Summary of Disentangling Interpretable Factors with Supervised Independent Subspace Principal Component Analysis, by Jiayu Su et al.
Summary of Stabilizing Linear Passive-aggressive Online Learning with Weighted Reservoir Sampling, by Skyler Wu et al.
Summary of Linearized Wasserstein Barycenters: Synthesis, Analysis, Representational Capacity, and Applications, by Matthew Werenski et al.
Summary of Global Convergence in Training Large-scale Transformers, by Cheng Gao and Yuan Cao and Zihao Li and Yihan He and Mengdi Wang and Han Liu and Jason Matthew Klusowski and Jianqing Fan
Summary of Domain-decomposed Image Classification Algorithms Using Linear Discriminant Analysis and Convolutional Neural Networks, by Axel Klawonn et al.
Summary of Random Heterogeneous Neurochaos Learning Architecture For Data Classification, by Remya Ajai a S et al.
Summary of Estimating Neural Network Robustness Via Lipschitz Constant and Architecture Sensitivity, by Abulikemu Abuduweili and Changliu Liu
Summary of Resource Governance in Networked Systems Via Integrated Variational Autoencoders and Reinforcement Learning, by Qiliang Chen et al.
Summary of Understanding Representation Of Deep Equilibrium Models From Neural Collapse Perspective, by Haixiang Sun et al.
Summary of Adaptive Network Intervention For Complex Systems: a Hierarchical Graph Reinforcement Learning Approach, by Qiliang Chen et al.
Summary of On the Optimality Of Dilated Entropy and Lower Bounds For Online Learning in Extensive-form Games, by Zhiyuan Fan et al.
Summary of Stepping Out Of the Shadows: Reinforcement Learning in Shadow Mode, by Philipp Gassert et al.
Summary of Flowllm: Flow Matching For Material Generation with Large Language Models As Base Distributions, by Anuroop Sriram et al.
Summary of Communication-efficient Federated Learning Over Wireless Channels Via Gradient Sketching, by Vineet Sunil Gattani et al.
Summary of Dynamic Information Sub-selection For Decision Support, by Hung-tien Huang et al.
Summary of Model-free Low-rank Reinforcement Learning Via Leveraged Entry-wise Matrix Estimation, by Stefan Stojanovic et al.
Summary of Mind the Gap: a Generalized Approach For Cross-modal Embedding Alignment, by Arihan Yadav et al.
Summary of Learning and Transferring Sparse Contextual Bigrams with Linear Transformers, by Yunwei Ren et al.
Summary of Learning Lipschitz Operators with Respect to Gaussian Measures with Near-optimal Sample Complexity, by Ben Adcock and Michael Griebel and Gregor Maier
Summary of Return Augmented Decision Transformer For Off-dynamics Reinforcement Learning, by Ruhan Wang et al.
Summary of Rethinking Deep Thinking: Stable Learning Of Algorithms Using Lipschitz Constraints, by Jay Bear et al.
Summary of Transformation-invariant Learning and Theoretical Guarantees For Ood Generalization, by Omar Montasser et al.
Summary of Mdcure: a Scalable Pipeline For Multi-document Instruction-following, by Gabrielle Kaili-may Liu et al.
Summary of Gradient-free Training Of Recurrent Neural Networks, by Erik Lien Bolager et al.
Summary of Protransformer: Robustify Transformers Via Plug-and-play Paradigm, by Zhichao Hou et al.
Summary of Does Equivariance Matter at Scale?, by Johann Brehmer et al.
Summary of Kinetix: Investigating the Training Of General Agents Through Open-ended Physics-based Control Tasks, by Michael Matthews et al.
Summary of Improved Convergence Rate Of Knn Graph Laplacians, by Yixuan Tan et al.
Summary of Grounding by Trying: Llms with Reinforcement Learning-enhanced Retrieval, By Sheryl Hsu et al.
Summary of Comal: a Convergent Meta-algorithm For Aligning Llms with General Preferences, by Yixin Liu et al.
Summary of Partial Channel Dependence with Channel Masks For Time Series Foundation Models, by Seunghan Lee et al.
Summary of Emergence Of Meta-stable Clustering in Mean-field Transformer Models, by Giuseppe Bruno et al.
Summary of Aligning Audio-visual Joint Representations with An Agentic Workflow, by Shentong Mo et al.
Summary of Very Fast Bayesian Additive Regression Trees on Gpu, by Giacomo Petrillo
Summary of Attribute-to-delete: Machine Unlearning Via Datamodel Matching, by Kristian Georgiev et al.
Summary of A Monte Carlo Framework For Calibrated Uncertainty Estimation in Sequence Prediction, by Qidong Yang et al.
Summary of Emma: End-to-end Multimodal Model For Autonomous Driving, by Jyh-jing Hwang et al.
Summary of Multi-student Diffusion Distillation For Better One-step Generators, by Yanke Song et al.
Summary of Proportional Fairness in Non-centroid Clustering, by Ioannis Caragiannis et al.
Summary of Slowfast-vgen: Slow-fast Learning For Action-driven Long Video Generation, by Yining Hong et al.
Summary of Provable Acceleration For Diffusion Models Under Minimal Assumptions, by Gen Li et al.
Summary of Cliperase: Efficient Unlearning Of Visual-textual Associations in Clip, by Tianyu Yang et al.
Summary of Mole: Enhancing Human-centric Text-to-image Diffusion Via Mixture Of Low-rank Experts, by Jie Zhu et al.
Summary of Sequential Order-robust Mamba For Time Series Forecasting, by Seunghan Lee et al.
Summary of Controllable Game Level Generation: Assessing the Effect Of Negative Examples in Gan Models, by Mahsa Bazzaz and Seth Cooper
Summary of Exploring Gradient Subspaces: Addressing and Overcoming Lora’s Limitations in Federated Fine-tuning Of Large Language Models, by Navyansh Mahla et al.
Summary of Unified Triplet-level Hallucination Evaluation For Large Vision-language Models, by Junjie Wu et al.
Summary of Why Fine-grained Labels in Pretraining Benefit Generalization?, by Guan Zhe Hong et al.
Summary of Federated Learning Under Periodic Client Participation and Heterogeneous Data: a New Communication-efficient Algorithm and Analysis, by Michael Crawshaw et al.
Summary of Revisiting Mae Pre-training For 3d Medical Image Segmentation, by Tassilo Wald et al.
Summary of Provably Optimal Memory Capacity For Modern Hopfield Models: Transformer-compatible Dense Associative Memories As Spherical Codes, by Jerry Yao-chieh Hu et al.
Summary of Fair-tat: Improving Model Fairness Using Targeted Adversarial Training, by Tejaswini Medi et al.
Summary of The Good, the Bad, and the Ugly: the Role Of Ai Quality Disclosure in Lie Detection, by Haimanti Bhattacharya et al.
Summary of Foldtree: a Ulda-based Decision Tree Framework For Efficient Oblique Splits and Feature Selection, by Siyu Wang
Summary of Hibo: Hierarchical Bayesian Optimization Via Adaptive Search Space Partitioning, by Wenxuan Li et al.
Summary of Qwo: Speeding Up Permutation-based Causal Discovery in Ligams, by Mohammad Shahverdikondori et al.
Summary of Visualpredicator: Learning Abstract World Models with Neuro-symbolic Predicates For Robot Planning, by Yichao Liang et al.
Summary of Directional Anomaly Detection, by Oliver Urs Lenz et al.
Summary of Fourier Amplitude and Correlation Loss: Beyond Using L2 Loss For Skillful Precipitation Nowcasting, by Chiu-wai Yan et al.
Summary of Flextsf: a Universal Forecasting Model For Time Series with Variable Regularities, by Jingge Xiao et al.
Summary of Scipip: An Llm-based Scientific Paper Idea Proposer, by Wenxiao Wang et al.