Paper List

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Summary of Fairwire: Fair Graph Generation, by O. Deniz Kose and Yanning Shen
Summary of Denoising Diffusion Probabilistic Models in Six Simple Steps, by Richard E. Turner et al.
Summary of Densely Multiplied Physics Informed Neural Networks, by Feilong Jiang et al.
Summary of Hierarchical Delay Attribution Classification Using Unstructured Text in Train Management Systems, by Anton Borg et al.
Summary of Scafflsa: Taming Heterogeneity in Federated Linear Stochastic Approximation and Td Learning, by Paul Mangold et al.
Summary of A Quantitative Analysis Of Knowledge-learning Preferences in Large Language Models in Molecular Science, by Pengfei Liu et al.
Summary of Ovor: Oneprompt with Virtual Outlier Regularization For Rehearsal-free Class-incremental Learning, by Wei-cheng Huang et al.
Summary of Interpretable Multi-source Data Fusion Through Latent Variable Gaussian Process, by Sandipp Krishnan Ravi et al.
Summary of Read to Play (r2-play): Decision Transformer with Multimodal Game Instruction, by Yonggang Jin et al.
Summary of Attention with Markov: a Framework For Principled Analysis Of Transformers Via Markov Chains, by Ashok Vardhan Makkuva et al.
Summary of Tempered Calculus For Ml: Application to Hyperbolic Model Embedding, by Richard Nock and Ehsan Amid and Frank Nielsen and Alexander Soen and Manfred K. Warmuth
Summary of Informed Reinforcement Learning For Situation-aware Traffic Rule Exceptions, by Daniel Bogdoll et al.
Summary of Reinforcement Learning with Ensemble Model Predictive Safety Certification, by Sven Gronauer et al.
Summary of Scaling Laws For Downstream Task Performance in Machine Translation, by Berivan Isik et al.
Summary of Gradient Coding in Decentralized Learning For Evading Stragglers, by Chengxi Li and Mikael Skoglund
Summary of Variational Shapley Network: a Probabilistic Approach to Self-explaining Shapley Values with Uncertainty Quantification, by Mert Ketenci et al.
Summary of Cast: Clustering Self-attention Using Surrogate Tokens For Efficient Transformers, by Adjorn Van Engelenhoven et al.
Summary of Acute Kidney Injury Prediction For Non-critical Care Patients: a Retrospective External and Internal Validation Study, by Esra Adiyeke et al.
Summary of Musicrl: Aligning Music Generation to Human Preferences, by Geoffrey Cideron et al.
Summary of Can Mamba Learn How to Learn? a Comparative Study on In-context Learning Tasks, by Jongho Park et al.
Summary of Harmbench: a Standardized Evaluation Framework For Automated Red Teaming and Robust Refusal, by Mantas Mazeika et al.
Summary of Breaking Data Silos: Cross-domain Learning For Multi-agent Perception From Independent Private Sources, by Jinlong Li et al.
Summary of Cascast: Skillful High-resolution Precipitation Nowcasting Via Cascaded Modelling, by Junchao Gong et al.
Summary of A General Theory For Kernel Packets: From State Space Model to Compactly Supported Basis, by Liang Ding and Rui Tuo
Summary of Exploring the Effects Of Population and Employment Characteristics on Truck Flows: An Analysis Of Nextgen Nhts Origin-destination Data, by Majbah Uddin et al.
Summary of Positive Concave Deep Equilibrium Models, by Mateusz Gabor et al.
Summary of Reducing the Cost Of Quantum Chemical Data by Backpropagating Through Density Functional Theory, By Alexander Mathiasen et al.
Summary of Polyp-ddpm: Diffusion-based Semantic Polyp Synthesis For Enhanced Segmentation, by Zolnamar Dorjsembe et al.
Summary of Connecting the Dots: Collaborative Fine-tuning For Black-box Vision-language Models, by Zhengbo Wang et al.
Summary of Pac-bayesian Adversarially Robust Generalization Bounds For Graph Neural Network, by Tan Sun et al.
Summary of On Provable Privacy Vulnerabilities Of Graph Representations, by Ruofan Wu et al.
Summary of More Flexible Pac-bayesian Meta-learning by Learning Learning Algorithms, By Hossein Zakerinia et al.
Summary of Analysis Of Linear Mode Connectivity Via Permutation-based Weight Matching, by Akira Ito et al.
Summary of Link Prediction with Relational Hypergraphs, by Xingyue Huang et al.
Summary of Deep Learning For Multivariate Time Series Imputation: a Survey, by Jun Wang et al.
Summary of Retrieve to Explain: Evidence-driven Predictions with Language Models, by Ravi Patel et al.
Summary of Entropy-regularized Diffusion Policy with Q-ensembles For Offline Reinforcement Learning, by Ruoqi Zhang et al.
Summary of An Optimal House Price Prediction Algorithm: Xgboost, by Hemlata Sharma et al.
Summary of Improved Generalization Of Weight Space Networks Via Augmentations, by Aviv Shamsian et al.
Summary of Provably Learning a Multi-head Attention Layer, by Sitan Chen et al.
Summary of The Use Of a Large Language Model For Cyberbullying Detection, by Bayode Ogunleye et al.
Summary of A Hard-to-beat Baseline For Training-free Clip-based Adaptation, by Zhengbo Wang et al.
Summary of An Exploration Of Clustering Algorithms For Customer Segmentation in the Uk Retail Market, by Jeen Mary John et al.
Summary of Efficient Generation Of Hidden Outliers For Improved Outlier Detection, by Jose Cribeiro-ramallo et al.
Summary of The Challenges Of the Nonlinear Regime For Physics-informed Neural Networks, by Andrea Bonfanti et al.
Summary of Moment: a Family Of Open Time-series Foundation Models, by Mononito Goswami et al.
Summary of Challenges in Mechanistically Interpreting Model Representations, by Satvik Golechha et al.
Summary of Distillm: Towards Streamlined Distillation For Large Language Models, by Jongwoo Ko et al.
Summary of A Phase Transition Between Positional and Semantic Learning in a Solvable Model Of Dot-product Attention, by Hugo Cui et al.
Summary of Employee Turnover Analysis Using Machine Learning Algorithms, by Mahyar Karimi et al.
Summary of Learning Metrics That Maximise Power For Accelerated A/b-tests, by Olivier Jeunen and Aleksei Ustimenko
Summary of Return-aligned Decision Transformer, by Tsunehiko Tanaka et al.
Summary of Elastic Feature Consolidation For Cold Start Exemplar-free Incremental Learning, by Simone Magistri et al.
Summary of Discovery Of the Hidden World with Large Language Models, by Chenxi Liu et al.
Summary of In-context Learning Agents Are Asymmetric Belief Updaters, by Johannes A. Schubert et al.
Summary of A Comparison Between Humans and Ai at Recognizing Objects in Unusual Poses, by Netta Ollikka et al.
Summary of Space Group Constrained Crystal Generation, by Rui Jiao et al.
Summary of Cross Entropy Versus Label Smoothing: a Neural Collapse Perspective, by Li Guo et al.
Summary of Neural Rank Collapse: Weight Decay and Small Within-class Variability Yield Low-rank Bias, by Emanuele Zangrando et al.
Summary of Efficient Sketches For Training Data Attribution and Studying the Loss Landscape, by Andrea Schioppa
Summary of Bayesian Uncertainty For Gradient Aggregation in Multi-task Learning, by Idan Achituve et al.
Summary of Efficient Availability Attacks Against Supervised and Contrastive Learning Simultaneously, by Yihan Wang and Yifan Zhu and Xiao-shan Gao
Summary of Understanding the Effect Of Noise in Llm Training Data with Algorithmic Chains Of Thought, by Alex Havrilla et al.
Summary of Digital Twin Mobility Profiling: a Spatio-temporal Graph Learning Approach, by Xin Chen et al.
Summary of An Invariance Constrained Deep Learning Network For Pde Discovery, by Chao Chen et al.
Summary of Pre-training Of Lightweight Vision Transformers on Small Datasets with Minimally Scaled Images, by Jen Hong Tan
Summary of Enhanced Sampling Of Robust Molecular Datasets with Uncertainty-based Collective Variables, by Aik Rui Tan et al.
Summary of Fed-cvlc: Compressing Federated Learning Communications with Variable-length Codes, by Xiaoxin Su et al.
Summary of The Instinctive Bias: Spurious Images Lead to Illusion in Mllms, by Tianyang Han et al.
Summary of Reinforcement Learning From Bagged Reward, by Yuting Tang and Xin-qiang Cai and Yao-xiang Ding and Qiyu Wu and Guoqing Liu and Masashi Sugiyama
Summary of Learning a Decision Tree Algorithm with Transformers, by Yufan Zhuang et al.
Summary of Eero: Early Exit with Reject Option For Efficient Classification with Limited Budget, by Florian Valade (lama) et al.
Summary of Airphynet: Harnessing Physics-guided Neural Networks For Air Quality Prediction, by Kethmi Hirushini Hettige et al.
Summary of No-regret Reinforcement Learning in Smooth Mdps, by Davide Maran et al.
Summary of Weakly Supervised Anomaly Detection Via Knowledge-data Alignment, by Haihong Zhao et al.
Summary of Face Detection: Present State and Research Directions, by Purnendu Prabhat et al.
Summary of Seabo: a Simple Search-based Method For Offline Imitation Learning, by Jiafei Lyu et al.
Summary of Expediting In-network Federated Learning by Voting-based Consensus Model Compression, By Xiaoxin Su et al.
Summary of Masked Graph Autoencoder with Non-discrete Bandwidths, by Ziwen Zhao et al.
Summary of Asymptotic Generalization Error Of a Single-layer Graph Convolutional Network, by O. Duranthon et al.
Summary of Revorder: a Novel Method For Enhanced Arithmetic in Language Models, by Si Shen et al.
Summary of Estimating Barycenters Of Distributions with Neural Optimal Transport, by Alexander Kolesov et al.
Summary of On Gauge Freedom, Conservativity and Intrinsic Dimensionality Estimation in Diffusion Models, by Christian Horvat and Jean-pascal Pfister
Summary of Lens: a Foundation Model For Network Traffic, by Qineng Wang et al.
Summary of Operator Svd with Neural Networks Via Nested Low-rank Approximation, by J. Jon Ryu et al.
Summary of Cambranch: Contrastive Learning with Augmented Milps For Branching, by Jiacheng Lin et al.
Summary of Learning to Generate Explainable Stock Predictions Using Self-reflective Large Language Models, by Kelvin J.l. Koa et al.
Summary of On the Emergence Of Cross-task Linearity in the Pretraining-finetuning Paradigm, by Zhanpeng Zhou et al.
Summary of Transductive Reward Inference on Graph, by Bohao Qu et al.
Summary of Symbol Correctness in Deep Neural Networks Containing Symbolic Layers, by Aaron Bembenek et al.
Summary of Partial Gromov-wasserstein Metric, by Yikun Bai et al.
Summary of Logical Specifications-guided Dynamic Task Sampling For Reinforcement Learning Agents, by Yash Shukla et al.
Summary of Pard: Permutation-invariant Autoregressive Diffusion For Graph Generation, by Lingxiao Zhao et al.
Summary of Estimating the Local Learning Coefficient at Scale, by Zach Furman et al.
Summary of Unified Discrete Diffusion For Categorical Data, by Lingxiao Zhao et al.
Summary of Clarify: Improving Model Robustness with Natural Language Corrections, by Yoonho Lee et al.
Summary of Similarity-based Neighbor Selection For Graph Llms, by Rui Li et al.
Summary of Statistical Test For Anomaly Detections by Variational Auto-encoders, By Daiki Miwa et al.
Summary of Learning Granger Causality From Instance-wise Self-attentive Hawkes Processes, by Dongxia Wu et al.
Summary of Deep Outdated Fact Detection in Knowledge Graphs, by Huiling Tu et al.