Paper List

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Summary of Lora-drop: Efficient Lora Parameter Pruning Based on Output Evaluation, by Hongyun Zhou et al.
Summary of Generalization Bounds For Heavy-tailed Sdes Through the Fractional Fokker-planck Equation, by Benjamin Dupuis et al.
Summary of Universal Link Predictor by In-context Learning on Graphs, By Kaiwen Dong et al.
Summary of A Closer Look at the Robustness Of Contrastive Language-image Pre-training (clip), by Weijie Tu et al.
Summary of Potential-based Reward Shaping For Intrinsic Motivation, by Grant C. Forbes et al.
Summary of Context-aware Multi-model Object Detection For Diversely Heterogeneous Compute Systems, by Justin Davis and Mehmet E. Belviranli
Summary of Auxiliary Reward Generation with Transition Distance Representation Learning, by Siyuan Li and Shijie Han and Yingnan Zhao and By Liang and Peng Liu
Summary of An Empirical Study Into What Matters For Calibrating Vision-language Models, by Weijie Tu et al.
Summary of The I/o Complexity Of Attention, or How Optimal Is Flash Attention?, by Barna Saha et al.
Summary of Conditional Generative Models Are Sufficient to Sample From Any Causal Effect Estimand, by Md Musfiqur Rahman et al.
Summary of Araspider: Democratizing Arabic-to-sql, by Ahmed Heakl et al.
Summary of Triaug: Out-of-distribution Detection For Imbalanced Breast Lesion in Ultrasound, by Yinyu Ye et al.
Summary of Bandit-feedback Online Multiclass Classification: Variants and Tradeoffs, by Yuval Filmus et al.
Summary of On the Distance From Calibration in Sequential Prediction, by Mingda Qiao et al.
Summary of Score-based Physics-informed Neural Networks For High-dimensional Fokker-planck Equations, by Zheyuan Hu et al.
Summary of A Hormetic Approach to the Value-loading Problem: Preventing the Paperclip Apocalypse?, by Nathan I. N. Henry et al.
Summary of Topological Safeguard For Evasion Attack Interpreting the Neural Networks’ Behavior, by Xabier Echeberria-barrio et al.
Summary of Differentially Private Decentralized Learning with Random Walks, by Edwige Cyffers et al.
Summary of Score-based Diffusion Models Via Stochastic Differential Equations — a Technical Tutorial, by Wenpin Tang and Hanyang Zhao
Summary of Understanding Deep Learning Defenses Against Adversarial Examples Through Visualizations For Dynamic Risk Assessment, by Xabier Echeberria-barrio et al.
Summary of Accelerated Smoothing: a Scalable Approach to Randomized Smoothing, by Devansh Bhardwaj et al.
Summary of One Train For Two Tasks: An Encrypted Traffic Classification Framework Using Supervised Contrastive Learning, by Haozhen Zhang et al.
Summary of Clustertabnet: Supervised Clustering Method For Table Detection and Table Structure Recognition, by Marek Polewczyk and Marco Spinaci
Summary of Training Heterogeneous Client Models Using Knowledge Distillation in Serverless Federated Learning, by Mohak Chadha et al.
Summary of Power Transformer Fault Prediction Based on Knowledge Graphs, by Chao Wang et al.
Summary of Self-calibrating Conformal Prediction, by Lars Van Der Laan and Ahmed M. Alaa
Summary of Online Iterative Reinforcement Learning From Human Feedback with General Preference Model, by Chenlu Ye et al.
Summary of Bionerf: Biologically Plausible Neural Radiance Fields For View Synthesis, by Leandro A. Passos et al.
Summary of Odin: Disentangled Reward Mitigates Hacking in Rlhf, by Lichang Chen et al.
Summary of Towards Explainable, Safe Autonomous Driving with Language Embeddings For Novelty Identification and Active Learning: Framework and Experimental Analysis with Real-world Data Sets, by Ross Greer and Mohan Trivedi
Summary of Summing Up the Facts: Additive Mechanisms Behind Factual Recall in Llms, by Bilal Chughtai et al.
Summary of Perfect Recovery For Random Geometric Graph Matching with Shallow Graph Neural Networks, by Suqi Liu and Morgane Austern
Summary of Measurement Scheduling For Icu Patients with Offline Reinforcement Learning, by Zongliang Ji et al.
Summary of Accuracy Of Textfooler Black Box Adversarial Attacks on 01 Loss Sign Activation Neural Network Ensemble, by Yunzhe Xue and Usman Roshan
Summary of Noise-adaptive Confidence Sets For Linear Bandits and Application to Bayesian Optimization, by Kwang-sung Jun et al.
Summary of Data Distribution-based Curriculum Learning, by Shonal Chaudhry and Anuraganand Sharma
Summary of Regression Trees For Fast and Adaptive Prediction Intervals, by Luben M. C. Cabezas et al.
Summary of A Novel Gaussian Min-max Theorem and Its Applications, by Danil Akhtiamov et al.
Summary of Bayesian Deep Learning Via Expectation Maximization and Turbo Deep Approximate Message Passing, by Wei Xu et al.
Summary of Assessing Generalization For Subpopulation Representative Modeling Via In-context Learning, by Gabriel Simmons and Vladislav Savinov
Summary of Diff-rntraj: a Structure-aware Diffusion Model For Road Network-constrained Trajectory Generation, by Tonglong Wei et al.
Summary of Exploring Perceptual Limitation Of Multimodal Large Language Models, by Jiarui Zhang et al.
Summary of Replicability Is Asymptotically Free in Multi-armed Bandits, by Junpei Komiyama et al.
Summary of Pasoa- Particle Based Bayesian Optimal Adaptive Design, by Jacopo Iollo et al.
Summary of Geoformer: a Vision and Sequence Transformer-based Approach For Greenhouse Gas Monitoring, by Madhav Khirwar and Ankur Narang
Summary of Improving Lsh Via Tensorized Random Projection, by Bhisham Dev Verma and Rameshwar Pratap
Summary of Magneto: Edge Ai For Human Activity Recognition — Privacy and Personalization, by Jingwei Zuo et al.
Summary of Gsina: Improving Subgraph Extraction For Graph Invariant Learning Via Graph Sinkhorn Attention, by Fangyu Ding et al.
Summary of Parameter Symmetry and Noise Equilibrium Of Stochastic Gradient Descent, by Liu Ziyin et al.
Summary of More Benefits Of Being Distributional: Second-order Bounds For Reinforcement Learning, by Kaiwen Wang et al.
Summary of Outlier-aware Training For Low-bit Quantization Of Structural Re-parameterized Networks, by Muqun Niu et al.
Summary of Itinera: Integrating Spatial Optimization with Large Language Models For Open-domain Urban Itinerary Planning, by Yihong Tang et al.
Summary of Towards Fast Stochastic Sampling in Diffusion Generative Models, by Kushagra Pandey et al.
Summary of Rethinking Graph Masked Autoencoders Through Alignment and Uniformity, by Liang Wang et al.
Summary of Towards Generalized Inverse Reinforcement Learning, by Chaosheng Dong et al.
Summary of Uvtm: Universal Vehicle Trajectory Modeling with St Feature Domain Generation, by Yan Lin et al.
Summary of Impact Of Domain Knowledge and Multi-modality on Intelligent Molecular Property Prediction: a Systematic Survey, by Taojie Kuang et al.
Summary of Depth Separations in Neural Networks: Separating the Dimension From the Accuracy, by Itay Safran et al.
Summary of Dimon: Learning Solution Operators Of Partial Differential Equations on a Diffeomorphic Family Of Domains, by Minglang Yin et al.
Summary of Physics-informed Neural Networks with Hard Linear Equality Constraints, by Hao Chen et al.
Summary of Can Tree Based Approaches Surpass Deep Learning in Anomaly Detection? a Benchmarking Study, by Santonu Sarkar et al.
Summary of Open-ended Vqa Benchmarking Of Vision-language Models by Exploiting Classification Datasets and Their Semantic Hierarchy, By Simon Ging et al.
Summary of How Do Large Language Models Navigate Conflicts Between Honesty and Helpfulness?, by Ryan Liu et al.
Summary of Generalization Error Of Graph Neural Networks in the Mean-field Regime, by Gholamali Aminian et al.
Summary of Fiddler: Cpu-gpu Orchestration For Fast Inference Of Mixture-of-experts Models, by Keisuke Kamahori et al.
Summary of Semi-supervised Learning For Bilingual Lexicon Induction, by Paul Garnier and Gauthier Guinet
Summary of Distilling Symbolic Priors For Concept Learning Into Neural Networks, by Ioana Marinescu et al.
Summary of A Tale Of Tails: Model Collapse As a Change Of Scaling Laws, by Elvis Dohmatob et al.
Summary of Understanding the Training Speedup From Sampling with Approximate Losses, by Rudrajit Das et al.
Summary of Using Large Language Models to Automate and Expedite Reinforcement Learning with Reward Machine, by Shayan Meshkat Alsadat et al.
Summary of Fast Ucb-type Algorithms For Stochastic Bandits with Heavy and Super Heavy Symmetric Noise, by Yuriy Dorn et al.
Summary of Refined Sample Complexity For Markov Games with Independent Linear Function Approximation, by Yan Dai et al.
Summary of Rethinking the Capacity Of Graph Neural Networks For Branching Strategy, by Ziang Chen et al.
Summary of The Relevance Feature and Vector Machine For Health Applications, by Albert Belenguer-llorens et al.
Summary of Self-correcting Self-consuming Loops For Generative Model Training, by Nate Gillman et al.
Summary of An Empirical Study on the Power Of Future Prediction in Partially Observable Environments, by Jeongyeol Kwon et al.
Summary of Towards Quantifying the Preconditioning Effect Of Adam, by Rudrajit Das et al.
Summary of Echoes Of Socratic Doubt: Embracing Uncertainty in Calibrated Evidential Reinforcement Learning, by Alex Christopher Stutts et al.
Summary of An Attempt to Generate New Bridge Types From Latent Space Of Denoising Diffusion Implicit Model, by Hongjun Zhang
Summary of Resampling Methods For Private Statistical Inference, by Karan Chadha et al.
Summary of Towards Robust Car Following Dynamics Modeling Via Blackbox Models: Methodology, Analysis, and Recommendations, by Muhammad Bilal Shahid et al.
Summary of Explainable Global Wildfire Prediction Models Using Graph Neural Networks, by Dayou Chen and Sibo Cheng and Jinwei Hu and Matthew Kasoar and Rossella Arcucci
Summary of Natural Language Reinforcement Learning, by Xidong Feng et al.
Summary of Solving Deep Reinforcement Learning Tasks with Evolution Strategies and Linear Policy Networks, by Annie Wong et al.
Summary of Topological Neural Networks: Mitigating the Bottlenecks Of Graph Neural Networks Via Higher-order Interactions, by Lorenzo Giusti
Summary of Generating Chain-of-thoughts with a Pairwise-comparison Approach to Searching For the Most Promising Intermediate Thought, by Zhen-yu Zhang et al.
Summary of Learning Attributed Graphlets: Predictive Graph Mining by Graphlets with Trainable Attribute, By Tajima Shinji et al.
Summary of Assessing Uncertainty Estimation Methods For 3d Image Segmentation Under Distribution Shifts, by Masoumeh Javanbakhat et al.
Summary of Openfedllm: Training Large Language Models on Decentralized Private Data Via Federated Learning, by Rui Ye et al.
Summary of Efficient Incremental Belief Updates Using Weighted Virtual Observations, by David Tolpin
Summary of Feature Mapping in Physics-informed Neural Networks (pinns), by Chengxi Zeng et al.
Summary of Deepcover: Advancing Rnn Test Coverage and Online Error Prediction Using State Machine Extraction, by Pouria Golshanrad and Fathiyeh Faghih
Summary of Contextual Stochastic Vehicle Routing with Time Windows, by Breno Serrano et al.
Summary of Event-keyed Summarization, by William Gantt and Alexander Martin and Pavlo Kuchmiichuk and Aaron Steven White
Summary of In-context Data Distillation with Tabpfn, by Junwei Ma et al.
Summary of Hypernetwork-driven Model Fusion For Federated Domain Generalization, by Marc Bartholet et al.
Summary of Guided Sketch-based Program Induction by Search Gradients, By Ahmad Ayaz Amin
Summary of Clients Collaborate: Flexible Differentially Private Federated Learning with Guaranteed Improvement Of Utility-privacy Trade-off, by Yuecheng Li et al.
Summary of A Change Detection Reality Check, by Isaac Corley et al.
Summary of Informativeness Of Reward Functions in Reinforcement Learning, by Rati Devidze et al.