Paper List

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Summary of A Theoretical Analysis Of Soft-label Vs Hard-label Training in Neural Networks, by Saptarshi Mandal et al.
Summary of Justrank: Benchmarking Llm Judges For System Ranking, by Ariel Gera et al.
Summary of Neptune: the Long Orbit to Benchmarking Long Video Understanding, by Arsha Nagrani et al.
Summary of Wait-less Offline Tuning and Re-solving For Online Decision Making, by Jingruo Sun et al.
Summary of Owl-1: Omni World Model For Consistent Long Video Generation, by Yuanhui Huang et al.
Summary of Hidden Biases Of End-to-end Driving Datasets, by Julian Zimmerlin et al.
Summary of Doe-1: Closed-loop Autonomous Driving with Large World Model, by Wenzhao Zheng et al.
Summary of An Algorithm-centered Approach to Model Streaming Data, by Fabian Hinder et al.
Summary of Mmd-opt : Maximum Mean Discrepancy Based Sample Efficient Collision Risk Minimization For Autonomous Driving, by Basant Sharma et al.
Summary of The Utility and Complexity Of In- and Out-of-distribution Machine Unlearning, by Youssef Allouah et al.
Summary of A Brief Discussion on Kpi Development in Public Administration, by Simona Fioretto et al.
Summary of Evaluating Adversarial Attacks on Traffic Sign Classifiers Beyond Standard Baselines, by Svetlana Pavlitska et al.
Summary of Uplift Modeling with Continuous Treatments: a Predict-then-optimize Approach, by Simon De Vos et al.
Summary of Gelora: Geometric Adaptive Ranks For Efficient Lora Fine-tuning, by Abdessalam Ed-dib et al.
Summary of When Can Memorization Improve Fairness?, by Bob Pepin et al.
Summary of Single-view Graph Contrastive Learning with Soft Neighborhood Awareness, by Qingqiang Sun et al.
Summary of Crvq: Channel-relaxed Vector Quantization For Extreme Compression Of Llms, by Yuzhuang Xu et al.
Summary of Dynamic Prompt Allocation and Tuning For Continual Test-time Adaptation, by Chaoran Cui et al.
Summary of Optimising Tinyml with Quantization and Distillation Of Transformer and Mamba Models For Indoor Localisation on Edge Devices, by Thanaphon Suwannaphong et al.
Summary of Transfer Learning Of Rssi to Improve Indoor Localisation Performance, by Thanaphon Suwannaphong et al.
Summary of Auto-regressive Moving Diffusion Models For Time Series Forecasting, by Jiaxin Gao et al.
Summary of Quantitative Evaluation Of Motif Sets in Time Series, by Daan Van Wesenbeeck et al.
Summary of Distribution Free Uncertainty Quantification in Neuroscience-inspired Deep Operators, by Shailesh Garg and Souvik Chakraborty
Summary of A Comprehensive Interpretable Machine Learning Framework For Mild Cognitive Impairment and Alzheimer’s Disease Diagnosis, by Maria Eleftheria Vlontzou et al.
Summary of Hybrid Variable Spiking Graph Neural Networks For Energy-efficient Scientific Machine Learning, by Isha Jain and Shailesh Garg and Shaurya Shriyam and Souvik Chakraborty
Summary of Diffusion Model with Representation Alignment For Protein Inverse Folding, by Chenglin Wang et al.
Summary of A Geometry-aware Message Passing Neural Network For Modeling Aerodynamics Over Airfoils, by Jacob Helwig et al.
Summary of Belted and Ensembled Neural Network For Linear and Nonlinear Sufficient Dimension Reduction, by Yin Tang and Bing Li
Summary of Posterior Approximation Using Stochastic Gradient Ascent with Adaptive Stepsize, by Kart-leong Lim et al.
Summary of Identity-preserving Pose-guided Character Animation Via Facial Landmarks Transformation, by Lianrui Mu et al.
Summary of A Wander Through the Multimodal Landscape: Efficient Transfer Learning Via Low-rank Sequence Multimodal Adapter, by Zirun Guo et al.
Summary of A Physics-informed Transformer Neural Operator For Learning Generalized Solutions Of Initial Boundary Value Problems, by Sumanth Kumar Boya et al.
Summary of Training Physical Neural Networks For Analog In-memory Computing, by Yusuke Sakemi et al.
Summary of Learning and Current Prediction Of Pmsm Drive Via Differential Neural Networks, by Wenjie Mei et al.
Summary of Ringformer: a Ring-enhanced Graph Transformer For Organic Solar Cell Property Prediction, by Zhihao Ding et al.
Summary of Pulling the Carpet Below the Learner’s Feet: Genetic Algorithm to Learn Ensemble Machine Learning Model During Concept Drift, by Teddy Lazebnik
Summary of Beyond Confusion: a Fine-grained Dialectical Examination Of Human Activity Recognition Benchmark Datasets, by Daniel Geissler et al.
Summary of Dial-in Llm: Human-aligned Llm-in-the-loop Intent Clustering For Customer Service Dialogues, by Mengze Hong et al.
Summary of Safe Active Learning For Gaussian Differential Equations, by Leon Glass and Katharina Ensinger and Christoph Zimmer
Summary of Go with the Flow: Fast Diffusion For Gaussian Mixture Models, by George Rapakoulias et al.
Summary of Multi-view Clustering Via Unified Multi-kernel Learning and Matrix Factorization, by Chenxing Jia et al.
Summary of Svasp: Self-versatility Adversarial Style Perturbation For Cross-domain Few-shot Learning, by Wenqian Li et al.
Summary of Neural Networks For Threshold Dynamics Reconstruction, by Elisa Negrini et al.
Summary of Filter-then-generate: Large Language Models with Structure-text Adapter For Knowledge Graph Completion, by Ben Liu et al.
Summary of Integrated Trucks Assignment and Scheduling Problem with Mixed Service Mode Docks: a Q-learning Based Adaptive Large Neighborhood Search Algorithm, by Yueyi Li et al.
Summary of In-dataset Trajectory Return Regularization For Offline Preference-based Reinforcement Learning, by Songjun Tu et al.
Summary of How to Re-enable Pde Loss For Physical Systems Modeling Under Partial Observation, by Haodong Feng et al.
Summary of Latent Safety-constrained Policy Approach For Safe Offline Reinforcement Learning, by Prajwal Koirala et al.
Summary of Test-time Alignment Via Hypothesis Reweighting, by Yoonho Lee et al.
Summary of Harp: a Challenging Human-annotated Math Reasoning Benchmark, by Albert S. Yue et al.
Summary of Disentangling Impact Of Capacity, Objective, Batchsize, Estimators, and Step-size on Flow Vi, by Abhinav Agrawal and Justin Domke
Summary of Grothendieck Graph Neural Networks Framework: An Algebraic Platform For Crafting Topology-aware Gnns, by Amirreza Shiralinasab Langari et al.
Summary of Precise Asymptotics and Refined Regret Of Variance-aware Ucb, by Yingying Fan et al.
Summary of Words Of War: Exploring the Presidential Rhetorical Arsenal with Deep Learning, by Wyatt Scott et al.
Summary of Towards Modeling Evolving Longitudinal Health Trajectories with a Transformer-based Deep Learning Model, by Hans Moen et al.
Summary of Fawac: Feasibility Informed Advantage Weighted Regression For Persistent Safety in Offline Reinforcement Learning, by Prajwal Koirala et al.
Summary of Lexico: Extreme Kv Cache Compression Via Sparse Coding Over Universal Dictionaries, by Junhyuck Kim et al.
Summary of Smmf: Square-matricized Momentum Factorization For Memory-efficient Optimization, by Kwangryeol Park and Seulki Lee
Summary of Efficient Reinforcement Learning For Optimal Control with Natural Images, by Peter N. Loxley
Summary of Neural Interactive Proofs, by Lewis Hammond and Sam Adam-day
Summary of Radiology Report Generation Via Multi-objective Preference Optimization, by Ting Xiao et al.
Summary of Federated Foundation Models on Heterogeneous Time Series, by Shengchao Chen et al.
Summary of Rethinking Multi-objective Learning Through Goal-conditioned Supervised Learning, by Shijun Li et al.
Summary of Multi-scale Heterogeneous Text-attributed Graph Datasets From Diverse Domains, by Yunhui Liu et al.
Summary of Deep Clustering Using Dirichlet Process Gaussian Mixture and Alpha Jensen-shannon Divergence Clustering Loss, by Kart-leong Lim
Summary of Mosld: An Extremely Parameter-efficient Mixture-of-shared Loras For Multi-task Learning, by Lulu Zhao et al.
Summary of Optimized Gradient Clipping For Noisy Label Learning, by Xichen Ye et al.
Summary of Turboattention: Efficient Attention Approximation For High Throughputs Llms, by Hao Kang et al.
Summary of Flowedit: Inversion-free Text-based Editing Using Pre-trained Flow Models, by Vladimir Kulikov and Matan Kleiner and Inbar Huberman-spiegelglas and Tomer Michaeli
Summary of Mnist-fraction: Enhancing Math Education with Ai-driven Fraction Detection and Analysis, by Pegah Ahadian et al.
Summary of Multimodal Latent Language Modeling with Next-token Diffusion, by Yutao Sun et al.
Summary of Dmin: Scalable Training Data Influence Estimation For Diffusion Models, by Huawei Lin et al.
Summary of Gpd-1: Generative Pre-training For Driving, by Zixun Xie et al.
Summary of Geoconformal Prediction: a Model-agnostic Framework Of Measuring the Uncertainty Of Spatial Prediction, by Xiayin Lou et al.
Summary of A Feature Refinement Module For Light-weight Semantic Segmentation Network, by Zhiyan Wang et al.
Summary of A Deep Semantic Segmentation Network with Semantic and Contextual Refinements, by Zhiyan Wang et al.
Summary of Latentqa: Teaching Llms to Decode Activations Into Natural Language, by Alexander Pan and Lijie Chen and Jacob Steinhardt
Summary of Learning Physics Informed Neural Odes with Partial Measurements, by Paul Ghanem et al.
Summary of From Mlp to Neomlp: Leveraging Self-attention For Neural Fields, by Miltiadis Kofinas et al.
Summary of Docvlm: Make Your Vlm An Efficient Reader, by Mor Shpigel Nacson et al.
Summary of Deepnose: An Equivariant Convolutional Neural Network Predictive Of Human Olfactory Percepts, by Sergey Shuvaev et al.
Summary of Proactive Adversarial Defense: Harnessing Prompt Tuning in Vision-language Models to Detect Unseen Backdoored Images, by Kyle Stein et al.
Summary of Integrating Optimization Theory with Deep Learning For Wireless Network Design, by Sinem Coleri et al.
Summary of Beyond Knowledge Silos: Task Fingerprinting For Democratization Of Medical Imaging Ai, by Patrick Godau and Akriti Srivastava and Tim Adler and Lena Maier-hein
Summary of Llava-zip: Adaptive Visual Token Compression with Intrinsic Image Information, by Ke Wang et al.
Summary of Bayesian Optimized Deep Ensemble For Uncertainty Quantification Of Deep Neural Networks: a System Safety Case Study on Sodium Fast Reactor Thermal Stratification Modeling, by Zaid Abulawi et al.
Summary of Gmem: a Modular Approach For Ultra-efficient Generative Models, by Yi Tang et al.
Summary of Adversarial Purification by Consistency-aware Latent Space Optimization on Data Manifolds, By Shuhai Zhang et al.
Summary of Robustness Of Graph Classification: Failure Modes, Causes, and Noise-resistant Loss in Graph Neural Networks, by Farooq Ahmad Wani et al.
Summary of From Logistic Regression to the Perceptron Algorithm: Exploring Gradient Descent with Large Step Sizes, by Alexander Tyurin
Summary of Proactive Model Adaptation Against Concept Drift For Online Time Series Forecasting, by Lifan Zhao et al.
Summary of From Multimodal Llms to Generalist Embodied Agents: Methods and Lessons, by Andrew Szot et al.
Summary of Efficient Rectification Of Neuro-symbolic Reasoning Inconsistencies by Abductive Reflection, By Wen-chao Hu et al.
Summary of Federated Learning For Traffic Flow Prediction with Synthetic Data Augmentation, by Fermin Orozco et al.
Summary of Irl For Restless Multi-armed Bandits with Applications in Maternal and Child Health, by Gauri Jain et al.
Summary of Invdiff: Invariant Guidance For Bias Mitigation in Diffusion Models, by Min Hou et al.
Summary of Gradstop: Exploring Training Dynamics in Unsupervised Outlier Detection Through Gradient Cohesion, by Yuang Zhang et al.
Summary of Enhancing Interpretability Through Loss-defined Classification Objective in Structured Latent Spaces, by Daniel Geissler et al.
Summary of Spend More to Save More (sm2): An Energy-aware Implementation Of Successive Halving For Sustainable Hyperparameter Optimization, by Daniel Geissler et al.
Summary of Maestromotif: Skill Design From Artificial Intelligence Feedback, by Martin Klissarov et al.