Paper List

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Summary of Unscrambling Disease Progression at Scale: Fast Inference Of Event Permutations with Optimal Transport, by Peter A. Wijeratne et al.
Summary of Personalizing Low-rank Bayesian Neural Networks Via Federated Learning, by Boning Zhang et al.
Summary of Debug Smarter, Not Harder: Ai Agents For Error Resolution in Computational Notebooks, by Konstantin Grotov et al.
Summary of Transfer Learning on Transformers For Building Energy Consumption Forecasting — a Comparative Study, by Robert Spencer et al.
Summary of Improving Graph Neural Networks by Learning Continuous Edge Directions, By Seong Ho Pahng and Sahand Hormoz
Summary of A Communication and Computation Efficient Fully First-order Method For Decentralized Bilevel Optimization, by Min Wen and Chengchang Liu and Ahmed Abdelmoniem and Yipeng Zhou and Yuedong Xu
Summary of Fedmse: Federated Learning For Iot Network Intrusion Detection, by Van Tuan Nguyen and Razvan Beuran
Summary of Estimating the Causal Effects Of T Cell Receptors, by Eli N. Weinstein et al.
Summary of Inverse Reinforcement Learning From Non-stationary Learning Agents, by Kavinayan P. Sivakumar et al.
Summary of Preview-based Category Contrastive Learning For Knowledge Distillation, by Muhe Ding et al.
Summary of Hierarchical Conditional Multi-task Learning For Streamflow Modeling, by Shaoming Xu et al.
Summary of A Mirror Descent Perspective Of Smoothed Sign Descent, by Shuyang Wang et al.
Summary of Beyond Autoregression: Discrete Diffusion For Complex Reasoning and Planning, by Jiacheng Ye et al.
Summary of Causalchat: Interactive Causal Model Development and Refinement Using Large Language Models, by Yanming Zhang et al.
Summary of Auto Detecting Cognitive Events Using Machine Learning on Pupillary Data, by Quang Dang et al.
Summary of Heavy-tailed Diffusion Models, by Kushagra Pandey et al.
Summary of Labsafety Bench: Benchmarking Llms on Safety Issues in Scientific Labs, by Yujun Zhou et al.
Summary of In-context Learning For Mixture Of Linear Regressions: Existence, Generalization and Training Dynamics, by Yanhao Jin et al.
Summary of Xpert: Extended Persistence Transformer, by Sehun Kim
Summary of Combining Hough Transform and Deep Learning Approaches to Reconstruct Ecg Signals From Printouts, by Felix Krones and Ben Walker and Terry Lyons and Adam Mahdi
Summary of Flexi-fuzz Least Squares Svm For Alzheimer’s Diagnosis: Tackling Noise, Outliers, and Class Imbalance, by Mushir Akhtar et al.
Summary of Comparative Evaluation Of Clustered Federated Learning Methods, by Michael Ben Ali (irit) et al.
Summary of Montessori-instruct: Generate Influential Training Data Tailored For Student Learning, by Xiaochuan Li et al.
Summary of Identifying Privacy Personas, by Olena Hrynenko and Andrea Cavallaro
Summary of Sliding Puzzles Gym: a Scalable Benchmark For State Representation in Visual Reinforcement Learning, by Bryan L. M. De Oliveira et al.
Summary of Latent Weight Diffusion: Generating Policies From Trajectories, by Shashank Hegde et al.
Summary of From Barriers to Tactics: a Behavioral Science-informed Agentic Workflow For Personalized Nutrition Coaching, by Eric Yang et al.
Summary of Human Action Anticipation: a Survey, by Bolin Lai et al.
Summary of Tensor Decomposition with Unaligned Observations, by Runshi Tang and Tamara Kolda and Anru R. Zhang
Summary of Gradual Domain Adaptation Via Manifold-constrained Distributionally Robust Optimization, by Amir Hossein Saberi et al.
Summary of From Isolated Conversations to Hierarchical Schemas: Dynamic Tree Memory Representation For Llms, by Alireza Rezazadeh et al.
Summary of On Partial Prototype Collapse in the Dino Family Of Self-supervised Methods, by Hariprasath Govindarajan et al.
Summary of Data-driven Rainfall Prediction at a Regional Scale: a Case Study with Ghana, by Indrajit Kalita et al.
Summary of Provable Benefits Of Complex Parameterizations For Structured State Space Models, by Yuval Ran-milo et al.
Summary of Rethinking Optimal Transport in Offline Reinforcement Learning, by Arip Asadulaev et al.
Summary of Fedpae: Peer-adaptive Ensemble Learning For Asynchronous and Model-heterogeneous Federated Learning, by Brianna Mueller et al.
Summary of Reward-free World Models For Online Imitation Learning, by Shangzhe Li et al.
Summary of Interpreting Inflammation Prediction Model Via Tag-based Cohort Explanation, by Fanyu Meng et al.
Summary of In-context Learning and Occam’s Razor, by Eric Elmoznino et al.
Summary of St-moe-bert: a Spatial-temporal Mixture-of-experts Framework For Long-term Cross-city Mobility Prediction, by Haoyu He et al.
Summary of A Statistical Machine Learning Approach For Adapting Reduced-order Models Using Projected Gaussian Process, by Xiao Liu and Xinchao Liu
Summary of Towards Effective Planning Strategies For Dynamic Opinion Networks, by Bharath Muppasani et al.
Summary of Efficient Sparse Pca Via Block-diagonalization, by Alberto Del Pia et al.
Summary of How Numerical Precision Affects Mathematical Reasoning Capabilities Of Llms, by Guhao Feng et al.
Summary of Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens, by Lijie Fan et al.
Summary of Exogenous Matching: Learning Good Proposals For Tractable Counterfactual Estimation, by Yikang Chen et al.
Summary of Transformers Utilization in Chart Understanding: a Review Of Recent Advances & Future Trends, by Mirna Al-shetairy et al.
Summary of Mixed-curvature Decision Trees and Random Forests, by Philippe Chlenski et al.
Summary of Gbct: An Efficient and Adaptive Granular-ball Clustering Algorithm For Complex Data, by Shuyin Xia et al.
Summary of Fitv2: Scalable and Improved Flexible Vision Transformer For Diffusion Model, by Zidong Wang and Zeyu Lu and Di Huang and Cai Zhou and Wanli Ouyang and and Lei Bai
Summary of On Diffusion Models For Multi-agent Partial Observability: Shared Attractors, Error Bounds, and Composite Flow, by Tonghan Wang et al.
Summary of Nonlinear Stochastic Gradient Descent and Heavy-tailed Noise: a Unified Framework and High-probability Guarantees, by Aleksandar Armacki et al.
Summary of Benchmarking Transcriptomics Foundation Models For Perturbation Analysis : One Pca Still Rules Them All, by Ihab Bendidi et al.
Summary of Goal Inference From Open-ended Dialog, by Rachel Ma et al.
Summary of Enhancing Generalization in Sparse Mixture Of Experts Models: the Case For Increased Expert Activation in Compositional Tasks, by Jinze Zhao
Summary of Trojan Prompt Attacks on Graph Neural Networks, by Minhua Lin et al.
Summary of Debiasing Large Vision-language Models by Ablating Protected Attribute Representations, By Neale Ratzlaff et al.
Summary of On the Learn-to-optimize Capabilities Of Transformers in In-context Sparse Recovery, by Renpu Liu et al.
Summary of Recurrent Neural Goodness-of-fit Test For Time Series, by Aoran Zhang et al.
Summary of Adversarial Inception For Bounded Backdoor Poisoning in Deep Reinforcement Learning, by Ethan Rathbun et al.
Summary of Personalized Adaptation Via In-context Preference Learning, by Allison Lau et al.
Summary of Graph Neural Flows For Unveiling Systemic Interactions Among Irregularly Sampled Time Series, by Giangiacomo Mercatali et al.
Summary of Auditing and Enforcing Conditional Fairness Via Optimal Transport, by Mohsen Ghassemi et al.
Summary of Change Detection in Multivariate Data Streams: Online Analysis with Kernel-quanttree, by Michelangelo Olmo Nogara Notarianni et al.
Summary of Enhancing Retail Sales Forecasting with Optimized Machine Learning Models, by Priyam Ganguly and Isha Mukherjee
Summary of The Mystery Of the Pathological Path-star Task For Language Models, by Arvid Frydenlund
Summary of Dplm-2: a Multimodal Diffusion Protein Language Model, by Xinyou Wang et al.
Summary of Analyzing Deep Transformer Models For Time Series Forecasting Via Manifold Learning, by Ilya Kaufman and Omri Azencot
Summary of Arbitrarily-conditioned Multi-functional Diffusion For Multi-physics Emulation, by Da Long et al.
Summary of Adversarial Testing As a Tool For Interpretability: Length-based Overfitting Of Elementary Functions in Transformers, by Patrik Zavoral et al.
Summary of Discrete Distributions Are Learnable From Metastable Samples, by Abhijith Jayakumar et al.
Summary of Artificial Kuramoto Oscillatory Neurons, by Takeru Miyato et al.
Summary of A Common Pitfall Of Margin-based Language Model Alignment: Gradient Entanglement, by Hui Yuan et al.
Summary of Unearthing Skill-level Insights For Understanding Trade-offs Of Foundation Models, by Mazda Moayeri et al.
Summary of The Disparate Benefits Of Deep Ensembles, by Kajetan Schweighofer et al.
Summary of Active-dormant Attention Heads: Mechanistically Demystifying Extreme-token Phenomena in Llms, by Tianyu Guo et al.
Summary of Orso: Accelerating Reward Design Via Online Reward Selection and Policy Optimization, by Chen Bo Calvin Zhang et al.
Summary of A Unified View Of Delta Parameter Editing in Post-trained Large-scale Models, by Qiaoyu Tang et al.
Summary of Lighttransfer: Your Long-context Llm Is Secretly a Hybrid Model with Effortless Adaptation, by Xuan Zhang et al.
Summary of Influence Functions For Scalable Data Attribution in Diffusion Models, by Bruno Mlodozeniec et al.
Summary of Retrospective Learning From Interactions, by Zizhao Chen et al.
Summary of Diffusing States and Matching Scores: a New Framework For Imitation Learning, by Runzhe Wu et al.
Summary of Autoal: Automated Active Learning with Differentiable Query Strategy Search, by Yifeng Wang et al.
Summary of Latent Space Chain-of-embedding Enables Output-free Llm Self-evaluation, by Yiming Wang et al.
Summary of Efficient Function Placement in Virtual Networks: An Online Learning Approach, by Wei Huang and Richard Combes and Hind Castel-taleb and Badii Jouaber
Summary of Fine-tuning Discrete Diffusion Models Via Reward Optimization with Applications to Dna and Protein Design, by Chenyu Wang et al.
Summary of On the Role Of Attention Heads in Large Language Model Safety, by Zhenhong Zhou et al.
Summary of Automated Model Discovery For Tensional Homeostasis: Constitutive Machine Learning in Growth and Remodeling, by Hagen Holthusen and Tim Brepols and Kevin Linka and Ellen Kuhl
Summary of On-device Federated Learning in Smartphones For Detecting Depression From Reddit Posts, by Mustofa Ahmed et al.
Summary of Crystalx: Ultra-precision Crystal Structure Resolution and Error Correction Using Deep Learning, by Kaipeng Zheng et al.
Summary of Generation Through the Lens Of Learning Theory, by Jiaxun Li et al.
Summary of Movie Gen: a Cast Of Media Foundation Models, by Adam Polyak et al.
Summary of Reducing the Transformer Architecture to a Minimum, by Bernhard Bermeitinger et al.
Summary of Generative Conformal Prediction with Vectorized Non-conformity Scores, by Minxing Zheng et al.
Summary of Improved Convergence Rate For Diffusion Probabilistic Models, by Gen Li et al.
Summary of Supervised Kernel Thinning, by Albert Gong et al.
Summary of Single-timescale Multi-sequence Stochastic Approximation Without Fixed Point Smoothness: Theories and Applications, by Yue Huang et al.
Summary of Theory on Score-mismatched Diffusion Models and Zero-shot Conditional Samplers, by Yuchen Liang and Peizhong Ju and Yingbin Liang and Ness Shroff
Summary of Gder: Safeguarding Efficiency, Balancing, and Robustness Via Prototypical Graph Pruning, by Guibin Zhang et al.
Summary of Mixeval-x: Any-to-any Evaluations From Real-world Data Mixtures, by Jinjie Ni et al.