Paper List

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Summary of Exploiting Class Probabilities For Black-box Sentence-level Attacks, by Raha Moraffah and Huan Liu
Summary of Causal Feature Selection For Responsible Machine Learning, by Raha Moraffah et al.
Summary of Deep Equilibrium Models Are Almost Equivalent to Not-so-deep Explicit Models For High-dimensional Gaussian Mixtures, by Zenan Ling et al.
Summary of Are Large Language Models Table-based Fact-checkers?, by Hanwen Zhang et al.
Summary of Lhrs-bot: Empowering Remote Sensing with Vgi-enhanced Large Multimodal Language Model, by Dilxat Muhtar et al.
Summary of Classification Of Tennis Actions Using Deep Learning, by Emil Hovad (1 and 2) et al.
Summary of Desparsify: Adversarial Attack Against Token Sparsification Mechanisms in Vision Transformers, by Oryan Yehezkel et al.
Summary of Enhancing Robustness in Biomedical Nli Models: a Probing Approach For Clinical Trials, by Ata Mustafa
Summary of Foundation Model Makes Clustering a Better Initialization For Cold-start Active Learning, by Han Yuan and Chuan Hong
Summary of Synergy-of-thoughts: Eliciting Efficient Reasoning in Hybrid Language Models, by Yu Shang et al.
Summary of A Truly Joint Neural Architecture For Segmentation and Parsing, by Danit Yshaayahu Levi and Reut Tsarfaty
Summary of Spatio-temporal Prompting Network For Robust Video Feature Extraction, by Guanxiong Sun et al.
Summary of Diffeditor: Boosting Accuracy and Flexibility on Diffusion-based Image Editing, by Chong Mou et al.
Summary of Unified Training Of Universal Time Series Forecasting Transformers, by Gerald Woo et al.
Summary of Clipformer: Key-value Clipping Of Transformers on Memristive Crossbars For Write Noise Mitigation, by Abhiroop Bhattacharjee et al.
Summary of Leveraging Continuously Differentiable Activation Functions For Learning in Quantized Noisy Environments, by Vivswan Shah and Nathan Youngblood
Summary of Dual Interior Point Optimization Learning, by Michael Klamkin et al.
Summary of Accelerating Inverse Reinforcement Learning with Expert Bootstrapping, by David Wu and Sanjiban Choudhury
Summary of Fcorebench: Can Large Language Models Solve Challenging First-order Combinatorial Reasoning Problems?, by Chinmay Mittal et al.
Summary of The Virtues Of Pessimism in Inverse Reinforcement Learning, by David Wu and Gokul Swamy and J. Andrew Bagnell and Zhiwei Steven Wu and Sanjiban Choudhury
Summary of Enhancing Transformer Rnns with Multiple Temporal Perspectives, by Razvan-gabriel Dumitru et al.
Summary of Arithmetic in Transformers Explained, by Philip Quirke et al.
Summary of Denseformer: Enhancing Information Flow in Transformers Via Depth Weighted Averaging, by Matteo Pagliardini et al.
Summary of Beclr: Batch Enhanced Contrastive Few-shot Learning, by Stylianos Poulakakis-daktylidis and Hadi Jamali-rad
Summary of Lqer: Low-rank Quantization Error Reconstruction For Llms, by Cheng Zhang et al.
Summary of Breaking Mlperf Training: a Case Study on Optimizing Bert, by Yongdeok Kim et al.
Summary of Surfing the Modeling Of Pos Taggers in Low-resource Scenarios, by Manuel Vilares Ferro et al.
Summary of On the Role Of Initialization on the Implicit Bias in Deep Linear Networks, by Oria Gruber et al.
Summary of Tngps: Discovering Unknown Tensor Network Structure Search Algorithms Via Large Language Models (llms), by Junhua Zeng et al.
Summary of Review Of Multimodal Machine Learning Approaches in Healthcare, by Felix Krones et al.
Summary of On Minimum Trace Factor Analysis — An Old Song Sung to a New Tune, by C. Li et al.
Summary of A Fast Method For Lasso and Logistic Lasso, by Siu-wing Cheng et al.
Summary of Fast Peer Adaptation with Context-aware Exploration, by Long Ma et al.
Summary of Timesiam: a Pre-training Framework For Siamese Time-series Modeling, by Jiaxiang Dong et al.
Summary of Why Are Hyperbolic Neural Networks Effective? a Study on Hierarchical Representation Capability, by Shicheng Tan et al.
Summary of Brain: Bayesian Reward-conditioned Amortized Inference For Natural Language Generation From Feedback, by Gaurav Pandey et al.
Summary of Weisfeiler Leman For Euclidean Equivariant Machine Learning, by Snir Hordan et al.
Summary of Early Stopping by Correlating Online Indicators in Neural Networks, By Manuel Vilares Ferro et al.
Summary of Modeling Of Learning Curves with Applications to Pos Tagging, by Manuel Vilares Ferro et al.
Summary of Adaptive Scheduling For Adaptive Sampling in Pos Taggers Construction, by Manuel Vilares Ferro et al.
Summary of Unifying Generation and Prediction on Graphs with Latent Graph Diffusion, by Cai Zhou et al.
Summary of Competesmoe — Effective Training Of Sparse Mixture Of Experts Via Competition, by Quang Pham et al.
Summary of Absolute Convergence and Error Thresholds in Non-active Adaptive Sampling, by Manuel Vilares Ferro et al.
Summary of Timer: Generative Pre-trained Transformers Are Large Time Series Models, by Yong Liu et al.
Summary of Autotimes: Autoregressive Time Series Forecasters Via Large Language Models, by Yong Liu et al.
Summary of Noah: Learning Pairwise Object Category Attentions For Image Classification, by Chao Li et al.
Summary of Revisiting the Power Of Prompt For Visual Tuning, by Yuzhu Wang et al.
Summary of Dellma: Decision Making Under Uncertainty with Large Language Models, by Ollie Liu et al.
Summary of Solution-oriented Agent-based Models Generation with Verifier-assisted Iterative In-context Learning, by Tong Niu et al.
Summary of Fredf: Learning to Forecast in Frequency Domain, by Hao Wang et al.
Summary of Defining Neural Network Architecture Through Polytope Structures Of Dataset, by Sangmin Lee et al.
Summary of Glape: Gold Label-agnostic Prompt Evaluation and Optimization For Large Language Model, by Xuanchang Zhang et al.
Summary of Aligner: Efficient Alignment by Learning to Correct, By Jiaming Ji et al.
Summary of Uni-rlhf: Universal Platform and Benchmark Suite For Reinforcement Learning with Diverse Human Feedback, by Yifu Yuan et al.
Summary of Deeplag: Discovering Deep Lagrangian Dynamics For Intuitive Fluid Prediction, by Qilong Ma et al.
Summary of Towards An Information Theoretic Framework Of Context-based Offline Meta-reinforcement Learning, by Lanqing Li et al.
Summary of Exploiting Low-level Representations For Ultra-fast Road Segmentation, by Huan Zhou et al.
Summary of Uncertainty-aware Perceiver, by Euiyul Song
Summary of Learning Mutual Excitation For Hand-to-hand and Human-to-human Interaction Recognition, by Mengyuan Liu et al.
Summary of Fast and Interpretable Support Vector Classification Based on the Truncated Anova Decomposition, by Kseniya Akhalaya et al.
Summary of Diffstitch: Boosting Offline Reinforcement Learning with Diffusion-based Trajectory Stitching, by Guanghe Li et al.
Summary of Topox: a Suite Of Python Packages For Machine Learning on Topological Domains, by Mustafa Hajij et al.
Summary of A Momentum Accelerated Algorithm For Relu-based Nonlinear Matrix Decomposition, by Qingsong Wang et al.
Summary of Invit: a Generalizable Routing Problem Solver with Invariant Nested View Transformer, by Han Fang et al.
Summary of Diversity Measurement and Subset Selection For Instruction Tuning Datasets, by Peiqi Wang et al.
Summary of Active Learning For Graphs with Noisy Structures, by Hongliang Chi et al.
Summary of Dynamic Incremental Optimization For Best Subset Selection, by Shaogang Ren et al.
Summary of Momentum Does Not Reduce Stochastic Noise in Stochastic Gradient Descent, by Naoki Sato and Hideaki Iiduka
Summary of Sample Complexity Of Algorithm Selection Using Neural Networks and Its Applications to Branch-and-cut, by Hongyu Cheng et al.
Summary of Minusformer: Improving Time Series Forecasting by Progressively Learning Residuals, By Daojun Liang et al.
Summary of Uncertainty-aware Testing-time Optimization For 3d Human Pose Estimation, by Ti Wang et al.
Summary of Arithmetic Feature Interaction Is Necessary For Deep Tabular Learning, by Yi Cheng et al.
Summary of Metaoptimize: a Framework For Optimizing Step Sizes and Other Meta-parameters, by Arsalan Sharifnassab et al.
Summary of Learning Semantic Proxies From Visual Prompts For Parameter-efficient Fine-tuning in Deep Metric Learning, by Li Ren et al.
Summary of Stereographic Spherical Sliced Wasserstein Distances, by Huy Tran et al.
Summary of Riemannian Preconditioned Lora For Fine-tuning Foundation Models, by Fangzhao Zhang et al.
Summary of A Paradigm For Potential Model Performance Improvement in Classification and Regression Problems. a Proof Of Concept, by Francisco Javier Lobo-cabrera
Summary of Symbol: Generating Flexible Black-box Optimizers Through Symbolic Equation Learning, by Jiacheng Chen et al.
Summary of Multi-modal Causal Structure Learning and Root Cause Analysis, by Lecheng Zheng et al.
Summary of Pruner: a Speculative Exploration Mechanism to Accelerate Tensor Program Tuning, by Liang Qiao et al.
Summary of Unification Of Symmetries Inside Neural Networks: Transformer, Feedforward and Neural Ode, by Koji Hashimoto et al.
Summary of Loss Landscape Degeneracy Drives Stagewise Development in Transformers, by Jesse Hoogland et al.
Summary of Transolver: a Fast Transformer Solver For Pdes on General Geometries, by Haixu Wu et al.
Summary of Vanilla Bayesian Optimization Performs Great in High Dimensions, by Carl Hvarfner and Erik Orm Hellsten and Luigi Nardi
Summary of Federated Learning with Differential Privacy, by Adrien Banse et al.
Summary of Distributional Reduction: Unifying Dimensionality Reduction and Clustering with Gromov-wasserstein, by Hugues Van Assel et al.
Summary of Beyond the Limits: a Survey Of Techniques to Extend the Context Length in Large Language Models, by Xindi Wang et al.
Summary of Parameter-efficient Fine-tuning For Pre-trained Vision Models: a Survey, by Yi Xin et al.
Summary of Revisiting Generative Adversarial Networks For Binary Semantic Segmentation on Imbalanced Datasets, by Lei Xu and Moncef Gabbouj
Summary of Teacher-student Learning Based Low Complexity Relay Selection in Wireless Powered Communications, by Aysun Gurur Onalan et al.
Summary of Frequency Explains the Inverse Correlation Of Large Language Models’ Size, Training Data Amount, and Surprisal’s Fit to Reading Times, by Byung-doh Oh et al.
Summary of Don’t Label Twice: Quantity Beats Quality When Comparing Binary Classifiers on a Budget, by Florian E. Dorner and Moritz Hardt
Summary of Mixednuts: Training-free Accuracy-robustness Balance Via Nonlinearly Mixed Classifiers, by Yatong Bai et al.
Summary of Xtsformer: Cross-temporal-scale Transformer For Irregular-time Event Prediction in Clinical Applications, by Tingsong Xiao et al.
Summary of Federated Learning with New Knowledge: Fundamentals, Advances, and Futures, by Lixu Wang et al.
Summary of Sudokusens: Enhancing Deep Learning Robustness For Iot Sensing Applications Using a Generative Approach, by Tianshi Wang et al.
Summary of Causal Bayesian Optimization Via Exogenous Distribution Learning, by Shaogang Ren et al.
Summary of Synthdst: Synthetic Data Is All You Need For Few-shot Dialog State Tracking, by Atharva Kulkarni et al.
Summary of Multi-level Aggregation and Recursive Alignment Architecture For Efficient Parallel Inference Segmentation Network, by Yanhua Zhang et al.
Summary of Jailbreaking Attack Against Multimodal Large Language Model, by Zhenxing Niu and Haodong Ren and Xinbo Gao and Gang Hua and Rong Jin