Paper List

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Summary of Lola: Llm-assisted Online Learning Algorithm For Content Experiments, by Zikun Ye et al.
Summary of Acco: Accumulate While You Communicate, Hiding Communications in Distributed Llm Training, by Adel Nabli (mlia et al.
Summary of Frequency Enhanced Pre-training For Cross-city Few-shot Traffic Forecasting, by Zhanyu Liu et al.
Summary of A Hybrid Numerical Methodology Coupling Reduced Order Modeling and Graph Neural Networks For Non-parametric Geometries: Applications to Structural Dynamics Problems, by Victor Matray (lmps) et al.
Summary of Applying Fine-tuned Llms For Reducing Data Needs in Load Profile Analysis, by Yi Hu et al.
Summary of A Temporal Kolmogorov-arnold Transformer For Time Series Forecasting, by Remi Genet and Hugo Inzirillo
Summary of Ai-sampler: Adversarial Learning Of Markov Kernels with Involutive Maps, by Evgenii Egorov and Ricardo Valperga et al.
Summary of Kolmogorov-arnold Networks For Time Series: Bridging Predictive Power and Interpretability, by Kunpeng Xu et al.
Summary of Towards Efficient Mixture Of Experts: a Holistic Study Of Compression Techniques, by Shwai He et al.
Summary of Guiding a Diffusion Model with a Bad Version Of Itself, by Tero Karras et al.
Summary of Fairness-optimized Synthetic Ehr Generation For Arbitrary Downstream Predictive Tasks, by Mirza Farhan Bin Tarek et al.
Summary of Uncertainty Of Joint Neural Contextual Bandit, by Hongbo Guo et al.
Summary of Topviewrs: Vision-language Models As Top-view Spatial Reasoners, by Chengzu Li et al.
Summary of Mitigate Position Bias in Large Language Models Via Scaling a Single Dimension, by Yijiong Yu et al.
Summary of Loki: Low-rank Keys For Efficient Sparse Attention, by Prajwal Singhania et al.
Summary of Parrot: Multilingual Visual Instruction Tuning, by Hai-long Sun et al.
Summary of To Believe or Not to Believe Your Llm, by Yasin Abbasi Yadkori et al.
Summary of Robust and Highly Scalable Estimation Of Directional Couplings From Time-shifted Signals, by Louis Rouillard et al.
Summary of Are Ppo-ed Language Models Hackable?, by Suraj Anand and David Getzen
Summary of Cross-modal Safety Alignment: Is Textual Unlearning All You Need?, by Trishna Chakraborty et al.
Summary of Learning to Grok: Emergence Of In-context Learning and Skill Composition in Modular Arithmetic Tasks, by Tianyu He et al.
Summary of Pretrained Mobility Transformer: a Foundation Model For Human Mobility, by Xinhua Wu et al.
Summary of Spatiotemporal Predictions Of Toxic Urban Plumes Using Deep Learning, by Yinan Wang et al.
Summary of Constrained or Unconstrained? Neural-network-based Equation Discovery From Data, by Grant Norman et al.
Summary of Amosl: Adaptive Modality-wise Structure Learning in Multi-view Graph Neural Networks For Enhanced Unified Representation, by Peiyu Liang and Hongchang Gao and Xubin He
Summary of Progressive Confident Masking Attention Network For Audio-visual Segmentation, by Yuxuan Wang et al.
Summary of System-aware Neural Ode Processes For Few-shot Bayesian Optimization, by Jixiang Qing et al.
Summary of Feddr+: Stabilizing Dot-regression with Global Feature Distillation For Federated Learning, by Seongyoon Kim et al.
Summary of Label-wise Aleatoric and Epistemic Uncertainty Quantification, by Yusuf Sale et al.
Summary of Language Models Do Hard Arithmetic Tasks Easily and Hardly Do Easy Arithmetic Tasks, by Andrew Gambardella et al.
Summary of Using Self-supervised Learning Can Improve Model Fairness, by Sofia Yfantidou et al.
Summary of Finding Nemo: Localizing Neurons Responsible For Memorization in Diffusion Models, by Dominik Hintersdorf et al.
Summary of Learning to Edit Visual Programs with Self-supervision, by R. Kenny Jones et al.
Summary of Multiple Choice Questions and Large Languages Models: a Case Study with Fictional Medical Data, by Maxime Griot et al.
Summary of Grootvl: Tree Topology Is All You Need in State Space Model, by Yicheng Xiao et al.
Summary of Improved Modelling Of Federated Datasets Using Mixtures-of-dirichlet-multinomials, by Jonathan Scott et al.
Summary of Contextual Dynamic Pricing: Algorithms, Optimality, and Local Differential Privacy Constraints, by Zifeng Zhao et al.
Summary of Harnessing Neural Unit Dynamics For Effective and Scalable Class-incremental Learning, by Depeng Li et al.
Summary of A Generalized Apprenticeship Learning Framework For Modeling Heterogeneous Student Pedagogical Strategies, by Md Mirajul Islam et al.
Summary of Federated Class-incremental Learning with Hierarchical Generative Prototypes, by Riccardo Salami et al.
Summary of Offline Bayesian Aleatoric and Epistemic Uncertainty Quantification and Posterior Value Optimisation in Finite-state Mdps, by Filippo Valdettaro and A. Aldo Faisal
Summary of Meta-learners For Partially-identified Treatment Effects Across Multiple Environments, by Jonas Schweisthal et al.
Summary of An Empirical Study Into Clustering Of Unseen Datasets with Self-supervised Encoders, by Scott C. Lowe et al.
Summary of Landscape-aware Growing: the Power Of a Little Lag, by Stefani Karp et al.
Summary of Reinforcement Learning with Lookahead Information, by Nadav Merlis
Summary of Description Boosting For Zero-shot Entity and Relation Classification, by Gabriele Picco et al.
Summary of Analyzing the Benefits Of Prototypes For Semi-supervised Category Learning, by Liyi Zhang et al.
Summary of Graph Neural Networks Do Not Always Oversmooth, by Bastian Epping et al.
Summary of A Study Of Optimizations For Fine-tuning Large Language Models, by Arjun Singh et al.
Summary of Test-time Regret Minimization in Meta Reinforcement Learning, by Mirco Mutti et al.
Summary of An Axiomatic Approach to Loss Aggregation and An Adapted Aggregating Algorithm, by Armando J. Cabrera Pacheco and Rabanus Derr and Robert C. Williamson
Summary of Composite Quantile Regression with Xgboost Using the Novel Arctan Pinball Loss, by Laurens Sluijterman et al.
Summary of How to Explore with Belief: State Entropy Maximization in Pomdps, by Riccardo Zamboni et al.
Summary of Learning-rate-free Stochastic Optimization Over Riemannian Manifolds, by Daniel Dodd et al.
Summary of Effects Of Exponential Gaussian Distribution on (double Sampling) Randomized Smoothing, by Youwei Shu et al.
Summary of Disentangled Representation Via Variational Autoencoder For Continuous Treatment Effect Estimation, by Ruijing Cui et al.
Summary of Generative Conditional Distributions by Neural (entropic) Optimal Transport, By Bao Nguyen et al.
Summary of Pefad: a Parameter-efficient Federated Framework For Time Series Anomaly Detection, by Ronghui Xu et al.
Summary of Continual Unsupervised Out-of-distribution Detection, by Lars Doorenbos et al.
Summary of On Affine Homotopy Between Language Encoders, by Robin Sm Chan et al.
Summary of A Survey Of Transformer Enabled Time Series Synthesis, by Alexander Sommers et al.
Summary of Extended Mind Transformers, by Phoebe Klett and Thomas Ahle
Summary of Cluster-aware Similarity Diffusion For Instance Retrieval, by Jifei Luo et al.
Summary of Polynomial-augmented Neural Networks (panns) with Weak Orthogonality Constraints For Enhanced Function and Pde Approximation, by Madison Cooley et al.
Summary of Relu-kan: New Kolmogorov-arnold Networks That Only Need Matrix Addition, Dot Multiplication, and Relu, by Qi Qiu et al.
Summary of Longssm: on the Length Extension Of State-space Models in Language Modelling, by Shida Wang
Summary of Kernel Vs. Kernel: Exploring How the Data Structure Affects Neural Collapse, by Vignesh Kothapalli et al.
Summary of Online Learning and Information Exponents: on the Importance Of Batch Size, and Time/complexity Tradeoffs, by Luca Arnaboldi et al.
Summary of Iteration Head: a Mechanistic Study Of Chain-of-thought, by Vivien Cabannes et al.
Summary of Activation Bottleneck: Sigmoidal Neural Networks Cannot Forecast a Straight Line, by Maximilian Toller and Hussain Hussain and Bernhard C Geiger
Summary of Condtsf: One-line Plugin Of Dataset Condensation For Time Series Forecasting, by Jianrong Ding et al.
Summary of Radar Spectra-language Model For Automotive Scene Parsing, by Mariia Pushkareva et al.
Summary of Saver: Optimal Data Collection Strategy For Safe Policy Evaluation in Tabular Mdp, by Subhojyoti Mukherjee et al.
Summary of Branches: Efficiently Seeking Optimal Sparse Decision Trees with Ao*, by Ayman Chaouki et al.
Summary of On the Statistical Representation Properties Of the Perturb-softmax and the Perturb-argmax Probability Distributions, by Hedda Cohen Indelman et al.
Summary of Aroma: Preserving Spatial Structure For Latent Pde Modeling with Local Neural Fields, by Louis Serrano et al.
Summary of One-shot Federated Learning with Bayesian Pseudocoresets, by Tim D’hondt et al.
Summary of Dncs Require More Planning Steps, by Yara Shamshoum et al.
Summary of Fast and Scalable Multi-kernel Encoder Classifier, by Cencheng Shen
Summary of On the Recoverability Of Causal Relations From Temporally Aggregated I.i.d. Data, by Shunxing Fan et al.
Summary of Random Policy Evaluation Uncovers Policies Of Generative Flow Networks, by Haoran He and Emmanuel Bengio and Qingpeng Cai and Ling Pan
Summary of Sltrain: a Sparse Plus Low-rank Approach For Parameter and Memory Efficient Pretraining, by Andi Han et al.
Summary of Smcl: Saliency Masked Contrastive Learning For Long-tailed Recognition, by Sanglee Park et al.
Summary of On the Limitations Of Fractal Dimension As a Measure Of Generalization, by Charlie B. Tan et al.
Summary of Multiway Multislice Phate: Visualizing Hidden Dynamics Of Rnns Through Training, by Jiancheng Xie et al.
Summary of A Comparative Study Of Sampling Methods with Cross-validation in the Fedhome Framework, by Arash Ahmadi et al.
Summary of Can Dense Connectivity Benefit Outlier Detection? An Odyssey with Nas, by Hao Fu et al.
Summary of What Improves the Generalization Of Graph Transformers? a Theoretical Dive Into the Self-attention and Positional Encoding, by Hongkang Li et al.
Summary of Bayesian Mesh Optimization For Graph Neural Networks to Enhance Engineering Performance Prediction, by Jangseop Park and Namwoo Kang
Summary of Parameterizing Federated Continual Learning For Reproducible Research, by Bart Cox et al.
Summary of Mamba As Decision Maker: Exploring Multi-scale Sequence Modeling in Offline Reinforcement Learning, by Jiahang Cao et al.
Summary of On the Mode-seeking Properties Of Langevin Dynamics, by Xiwei Cheng et al.
Summary of Ffnet: Metamixer-based Efficient Convolutional Mixer Design, by Seokju Yun et al.
Summary of Inference Attacks: a Taxonomy, Survey, and Promising Directions, by Feng Wu et al.
Summary of Verifying the Generalization Of Deep Learning to Out-of-distribution Domains, by Guy Amir et al.
Summary of Dfa-gnn: Forward Learning Of Graph Neural Networks by Direct Feedback Alignment, By Gongpei Zhao et al.
Summary of A Unifying Framework For Action-conditional Self-predictive Reinforcement Learning, by Khimya Khetarpal et al.
Summary of Qroa: a Black-box Query-response Optimization Attack on Llms, by Hussein Jawad et al.
Summary of Cap: a Context-aware Neural Predictor For Nas, by Han Ji et al.
Summary of Graph Adversarial Diffusion Convolution, by Songtao Liu et al.