Paper List

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Summary of Demystifying Functional Random Forests: Novel Explainability Tools For Model Transparency in High-dimensional Spaces, by Fabrizio Maturo et al.
Summary of Leveraging Unlabeled Data Sharing Through Kernel Function Approximation in Offline Reinforcement Learning, by Yen-ru Lai et al.
Summary of Tackling Data Heterogeneity in Federated Learning Via Loss Decomposition, by Shuang Zeng et al.
Summary of Neural Symbolic Logical Rule Learner For Interpretable Learning, by Bowen Wei and Ziwei Zhu
Summary of Two-timescale Gradient Descent Ascent Algorithms For Nonconvex Minimax Optimization, by Tianyi Lin et al.
Summary of An Asymptotically Optimal Coordinate Descent Algorithm For Learning Bayesian Networks From Gaussian Models, by Tong Xu et al.
Summary of Only Strict Saddles in the Energy Landscape Of Predictive Coding Networks?, by Francesco Innocenti et al.
Summary of Time Series Foundation Models and Deep Learning Architectures For Earthquake Temporal and Spatial Nowcasting, by Alireza Jafari et al.
Summary of Quack-tsf: Quantum-classical Kernelized Time Series Forecasting, by Abdallah Aaraba et al.
Summary of Cspi-mt: Calibrated Safe Policy Improvement with Multiple Testing For Threshold Policies, by Brian M Cho et al.
Summary of Limitations in Employing Natural Language Supervision For Sensor-based Human Activity Recognition — and Ways to Overcome Them, by Harish Haresamudram et al.
Summary of Reasoning and Tools For Human-level Forecasting, by Elvis Hsieh et al.
Summary of Aligning (medical) Llms For (counterfactual) Fairness, by Raphael Poulain et al.
Summary of A Deconfounding Approach to Climate Model Bias Correction, by Wentao Gao et al.
Summary of Multi-task Curriculum Graph Contrastive Learning with Clustering Entropy Guidance, by Chusheng Zeng et al.
Summary of Simplified Mamba with Disentangled Dependency Encoding For Long-term Time Series Forecasting, by Zixuan Weng et al.
Summary of Unsupervised Discovery Of the Shared and Private Geometry in Multi-view Data, by Sai Koukuntla et al.
Summary of Umedsum: a Unified Framework For Advancing Medical Abstractive Summarization, by Aishik Nagar et al.
Summary of Extraction Of Research Objectives, Machine Learning Model Names, and Dataset Names From Academic Papers and Analysis Of Their Interrelationships Using Llm and Network Analysis, by S. Nishio et al.
Summary of Integrating Audio, Visual, and Semantic Information For Enhanced Multimodal Speaker Diarization, by Luyao Cheng and Hui Wang and Siqi Zheng and Yafeng Chen and Rongjie Huang and Qinglin Zhang and Qian Chen and Xihao Li
Summary of Pareto Inverse Reinforcement Learning For Diverse Expert Policy Generation, by Woo Kyung Kim and Minjong Yoo and Honguk Woo
Summary of Pareto Merging: Multi-objective Optimization For Preference-aware Model Merging, by Weiyu Chen et al.
Summary of Balancing Act: Prioritization Strategies For Llm-designed Restless Bandit Rewards, by Shresth Verma et al.
Summary of Critique-out-loud Reward Models, by Zachary Ankner et al.
Summary of Approaching Deep Learning Through the Spectral Dynamics Of Weights, by David Yunis et al.
Summary of Llm Pruning and Distillation in Practice: the Minitron Approach, by Sharath Turuvekere Sreenivas et al.
Summary of Efficient Exploration and Discriminative World Model Learning with An Object-centric Abstraction, by Anthony Gx-chen et al.
Summary of Faker: Full-body Anonymization with Human Keypoint Extraction For Real-time Video Deidentification, by Byunghyun Ban and Hyoseok Lee
Summary of Fast Training Dataset Attribution Via In-context Learning, by Milad Fotouhi et al.
Summary of Microxercise: a Micro-level Comparative and Explainable System For Remote Physical Therapy, by Hanchen David Wang et al.
Summary of Adaptive Friction in Deep Learning: Enhancing Optimizers with Sigmoid and Tanh Function, by Hongye Zheng et al.
Summary of When Raw Data Prevails: Are Large Language Model Embeddings Effective in Numerical Data Representation For Medical Machine Learning Applications?, by Yanjun Gao et al.
Summary of Factorllm: Factorizing Knowledge Via Mixture Of Experts For Large Language Models, by Zhongyu Zhao et al.
Summary of Speaking the Same Language: Leveraging Llms in Standardizing Clinical Data For Ai, by Arindam Sett et al.
Summary of Unraveling Text Generation in Llms: a Stochastic Differential Equation Approach, by Yukun Zhang
Summary of How Susceptible Are Llms to Influence in Prompts?, by Sotiris Anagnostidis et al.
Summary of Crossing New Frontiers: Knowledge-augmented Large Language Model Prompting For Zero-shot Text-based De Novo Molecule Design, by Sakhinana Sagar Srinivas et al.
Summary of Improving Embedding with Contrastive Fine-tuning on Small Datasets with Expert-augmented Scores, by Jun Lu et al.
Summary of Elder: Enhancing Lifelong Model Editing with Mixture-of-lora, by Jiaang Li et al.
Summary of Beyond Labels: Aligning Large Language Models with Human-like Reasoning, by Muhammad Rafsan Kabir et al.
Summary of Explainable Anomaly Detection: Counterfactual Driven What-if Analysis, by Logan Cummins et al.
Summary of Matmul or No Matmul in the Era Of 1-bit Llms, by Jinendra Malekar et al.
Summary of Valuing An Engagement Surface Using a Large Scale Dynamic Causal Model, by Abhimanyu Mukerji et al.
Summary of A Benchmark For Ai-based Weather Data Assimilation, by Wuxin Wang et al.
Summary of Using Part-based Representations For Explainable Deep Reinforcement Learning, by Manos Kirtas et al.
Summary of Learning Deep Dissipative Dynamics, by Yuji Okamoto and Ryosuke Kojima
Summary of Lakd-activation Mapping Distillation Based on Local Learning, by Yaoze Zhang and Yuming Zhang and Yu Zhao and Yue Zhang and Feiyu Zhu
Summary of Last-iterate Convergence Of General Parameterized Policies in Constrained Mdps, by Washim Uddin Mondal and Vaneet Aggarwal
Summary of Slicing Input Features to Accelerate Deep Learning: a Case Study with Graph Neural Networks, by Zhengjia Xu et al.
Summary of The Vizier Gaussian Process Bandit Algorithm, by Xingyou Song et al.
Summary of Memorization in In-context Learning, by Shahriar Golchin et al.
Summary of Self-supervised Iterative Refinement For Anomaly Detection in Industrial Quality Control, by Muhammad Aqeel et al.
Summary of Improving Calibration by Relating Focal Loss, Temperature Scaling, and Properness, By Viacheslav Komisarenko and Meelis Kull
Summary of A Markovian Model For Learning-to-optimize, by Michael Sucker and Peter Ochs
Summary of Macformer: Transformer with Random Maclaurin Feature Attention, by Yuhan Guo et al.
Summary of Optimizing Federated Graph Learning with Inherent Structural Knowledge and Dual-densely Connected Gnns, by Longwen Wang and Jianchun Liu and Zhi Liu and Jinyang Huang
Summary of First Line Of Defense: a Robust First Layer Mitigates Adversarial Attacks, by Janani Suresh et al.
Summary of Iterative Object Count Optimization For Text-to-image Diffusion Models, by Oz Zafar and Lior Wolf and Idan Schwartz
Summary of On Learnable Parameters Of Optimal and Suboptimal Deep Learning Models, by Ziwei Zheng et al.
Summary of Marlin: Mixed-precision Auto-regressive Parallel Inference on Large Language Models, by Elias Frantar et al.
Summary of Embedding Ordinality to Binary Loss Function For Improving Solar Flare Forecasting, by Chetraj Pandey et al.
Summary of Sum Of Squares Circuits, by Lorenzo Loconte et al.
Summary of Rfid Based Health Adherence Medicine Case Using Fair Federated Learning, by Ali Kamrani Khodaei et al.
Summary of Koopman Autoencoder Via Singular Value Decomposition For Data-driven Long-term Prediction, by Jinho Choi and Sivaram Krishnan and Jihong Park
Summary of Fedmoe: Personalized Federated Learning Via Heterogeneous Mixture Of Experts, by Hanzi Mei et al.
Summary of Are Kans Effective For Multivariate Time Series Forecasting?, by Xiao Han et al.
Summary of Improving Out-of-distribution Data Handling and Corruption Resistance Via Modern Hopfield Networks, by Saleh Sargolzaei and Luis Rueda
Summary of Design Principle Transfer in Neural Architecture Search Via Large Language Models, by Xun Zhou et al.
Summary of Automatic Dataset Construction (adc): Sample Collection, Data Curation, and Beyond, by Minghao Liu et al.
Summary of Fate: Focal-modulated Attention Encoder For Temperature Prediction, by Tajamul Ashraf et al.
Summary of Clinical Context-aware Radiology Report Generation From Medical Images Using Transformers, by Sonit Singh
Summary of Vision Hgnn: An Electron-micrograph Is Worth Hypergraph Of Hypernodes, by Sakhinana Sagar Srinivas et al.
Summary of One-step Structure Prediction and Screening For Protein-ligand Complexes Using Multi-task Geometric Deep Learning, by Kelei He et al.
Summary of Proteingpt: Multimodal Llm For Protein Property Prediction and Structure Understanding, by Yijia Xiao et al.
Summary of Hypergraph Learning Based Recommender System For Anomaly Detection, Control and Optimization, by Sakhinana Sagar Srinivas et al.
Summary of Georeasoner: Reasoning on Geospatially Grounded Context For Natural Language Understanding, by Yibo Yan et al.
Summary of Towards Probabilistic Inductive Logic Programming with Neurosymbolic Inference and Relaxation, by Fieke Hillerstrom et al.
Summary of Graph Classification Via Reference Distribution Learning: Theory and Practice, by Zixiao Wang and Jicong Fan
Summary of A Unified Framework For Continual Learning and Unlearning, by Romit Chatterjee et al.
Summary of Data-centric Machine Learning For Earth Observation: Necessary and Sufficient Features, by Hiba Najjar et al.
Summary of First Activations Matter: Training-free Methods For Dynamic Activation in Large Language Models, by Chi Ma et al.
Summary of Towards Aligned Data Removal Via Twin Machine Unlearning, by Yuyao Sun et al.
Summary of Linear-time One-class Classification with Repeated Element-wise Folding, by Jenni Raitoharju
Summary of Subgoalxl: Subgoal-based Expert Learning For Theorem Proving, by Xueliang Zhao et al.
Summary of A Full Dag Score-based Algorithm For Learning Causal Bayesian Networks with Latent Confounders, by Christophe Gonzales and Amir-hosein Valizadeh
Summary of Active Learning Of Molecular Data For Task-specific Objectives, by Kunal Ghosh et al.
Summary of Cracks: Crowdsourcing Resources For Analysis and Categorization Of Key Subsurface Faults, by Mohit Prabhushankar et al.
Summary of Reading with Intent, by Benjamin Reichman et al.
Summary of Ukan: Unbound Kolmogorov-arnold Network Accompanied with Accelerated Library, by Alireza Moradzadeh et al.
Summary of Effective Off-policy Evaluation and Learning in Contextual Combinatorial Bandits, by Tatsuhiro Shimizu et al.
Summary of Poodle: Pooled and Dense Self-supervised Learning From Naturalistic Videos, by Alex N. Wang et al.
Summary of Revisiting Min-max Optimization Problem in Adversarial Training, by Sina Hajer Ahmadi et al.
Summary of Asymmetric Graph Error Control with Low Complexity in Causal Bandits, by Chen Peng et al.
Summary of Unified Deep Learning Model For Global Prediction Of Aboveground Biomass, Canopy Height and Cover From High-resolution, Multi-sensor Satellite Imagery, by Manuel Weber et al.
Summary of A Little Confidence Goes a Long Way, by John Scoville et al.
Summary of Out-of-distribution Detection with Attention Head Masking For Multimodal Document Classification, by Christos Constantinou et al.
Summary of Do Neural Scaling Laws Exist on Graph Self-supervised Learning?, by Qian Ma et al.
Summary of Correlation Analysis Of Adversarial Attack in Time Series Classification, by Zhengyang Li et al.
Summary of Practical Aspects on Solving Differential Equations Using Deep Learning: a Primer, by Georgios Is. Detorakis
Summary of Inverting the Leverage Score Gradient: An Efficient Approximate Newton Method, by Chenyang Li et al.