Paper List

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Summary of Decompose-and-compose: a Compositional Approach to Mitigating Spurious Correlation, by Fahimeh Hosseini Noohdani et al.
Summary of Improving Group Connectivity For Generalization Of Federated Deep Learning, by Zexi Li et al.
Summary of Real-time Adaptive Safety-critical Control with Gaussian Processes in High-order Uncertain Models, by Yu Zhang et al.
Summary of Ice-search: a Language Model-driven Feature Selection Approach, by Tianze Yang et al.
Summary of Simple Linear Attention Language Models Balance the Recall-throughput Tradeoff, by Simran Arora et al.
Summary of Gnss Positioning Using Cost Function Regulated Multilateration and Graph Neural Networks, by Amir Jalalirad et al.
Summary of Quantifying Human Priors Over Social and Navigation Networks, by Gecia Bravo-hermsdorff
Summary of Data Interpreter: An Llm Agent For Data Science, by Sirui Hong et al.
Summary of The Voros: Lifting Roc Curves to 3d, by Christopher Ratigan and Lenore Cowen
Summary of Inferring Dynamic Networks From Marginals with Iterative Proportional Fitting, by Serina Chang et al.
Summary of Learning to Compress Prompt in Natural Language Formats, by Yu-neng Chuang et al.
Summary of Learning Associative Memories with Gradient Descent, by Vivien Cabannes et al.
Summary of Unveiling Privacy, Memorization, and Input Curvature Links, by Deepak Ravikumar et al.
Summary of Gaia: Categorical Foundations Of Generative Ai, by Sridhar Mahadevan
Summary of Priority Sampling Of Large Language Models For Compilers, by Dejan Grubisic et al.
Summary of Multi-sensor and Multi-temporal High-throughput Phenotyping For Monitoring and Early Detection Of Water-limiting Stress in Soybean, by Sarah E. Jones et al.
Summary of Pre-training Differentially Private Models with Limited Public Data, by Zhiqi Bu et al.
Summary of Disentangling the Causes Of Plasticity Loss in Neural Networks, by Clare Lyle et al.
Summary of Enhancing the “immunity” Of Mixture-of-experts Networks For Adversarial Defense, by Qiao Han et al.
Summary of Mpat: Building Robust Deep Neural Networks Against Textual Adversarial Attacks, by Fangyuan Zhang et al.
Summary of Blockecho: Retaining Long-range Dependencies For Imputing Block-wise Missing Data, by Qiao Han et al.
Summary of To Pool or Not to Pool: Analyzing the Regularizing Effects Of Group-fair Training on Shared Models, by Cyrus Cousins et al.
Summary of Dual Operating Modes Of In-context Learning, by Ziqian Lin et al.
Summary of Signature Kernel Conditional Independence Tests in Causal Discovery For Stochastic Processes, by Georg Manten et al.
Summary of Dynamical Regimes Of Diffusion Models, by Giulio Biroli et al.
Summary of Orchid: Flexible and Data-dependent Convolution For Sequence Modeling, by Mahdi Karami and Ali Ghodsi
Summary of Rnns Are Not Transformers (yet): the Key Bottleneck on In-context Retrieval, by Kaiyue Wen et al.
Summary of Log Neural Controlled Differential Equations: the Lie Brackets Make a Difference, by Benjamin Walker et al.
Summary of Defect Detection in Tire X-ray Images: Conventional Methods Meet Deep Structures, by Andrei Cozma et al.
Summary of Implicit Optimization Bias Of Next-token Prediction in Linear Models, by Christos Thrampoulidis
Summary of Keeping Llms Aligned After Fine-tuning: the Crucial Role Of Prompt Templates, by Kaifeng Lyu et al.
Summary of Generalizability Under Sensor Failure: Tokenization + Transformers Enable More Robust Latent Spaces, by Geeling Chau et al.
Summary of Diffusion Language Models Are Versatile Protein Learners, by Xinyou Wang et al.
Summary of Approaching Human-level Forecasting with Language Models, by Danny Halawi et al.
Summary of Arithmetic Control Of Llms For Diverse User Preferences: Directional Preference Alignment with Multi-objective Rewards, by Haoxiang Wang et al.
Summary of Stochastic Contextual Bandits with Graph Feedback: From Independence Number to Mas Number, by Yuxiao Wen et al.
Summary of Meta-task: a Method-agnostic Framework For Learning to Regularize in Few-shot Learning, by Mohammad Rostami et al.
Summary of Mmsr: Symbolic Regression Is a Multi-modal Information Fusion Task, by Yanjie Li et al.
Summary of Impact Of Network Topology on the Performance Of Decentralized Federated Learning, by Luigi Palmieri and Chiara Boldrini and Lorenzo Valerio and Andrea Passarella and Marco Conti
Summary of Forml: a Riemannian Hessian-free Method For Meta-learning on Stiefel Manifolds, by Hadi Tabealhojeh et al.
Summary of Exploring Privacy and Fairness Risks in Sharing Diffusion Models: An Adversarial Perspective, by Xinjian Luo et al.
Summary of Why Attention Graphs Are All We Need: Pioneering Hierarchical Classification Of Hematologic Cell Populations with Leukograph, by Fatemeh Nassajian Mojarrad et al.
Summary of Deep Neural Network Models Trained with a Fixed Random Classifier Transfer Better Across Domains, by Hafiz Tiomoko Ali et al.
Summary of Catastrophic Overfitting: a Potential Blessing in Disguise, by Mengnan Zhao et al.
Summary of Automated Machine Learning For Multi-label Classification, by Marcel Wever
Summary of Multi-objective Differentiable Neural Architecture Search, by Rhea Sanjay Sukthanker et al.
Summary of Self-supervised Learning with Generative Adversarial Networks For Electron Microscopy, by Bashir Kazimi and Karina Ruzaeva and Stefan Sandfeld
Summary of Cogbench: a Large Language Model Walks Into a Psychology Lab, by Julian Coda-forno et al.
Summary of Comparative Analysis Of Xgboost and Minirocket Algortihms For Human Activity Recognition, by Celal Alagoz
Summary of Fsl-rectifier: Rectify Outliers in Few-shot Learning Via Test-time Augmentation, by Yunwei Bai et al.
Summary of Escaping Local Optima in Global Placement, by Ke Xue et al.
Summary of How to Think Step-by-step: a Mechanistic Understanding Of Chain-of-thought Reasoning, by Subhabrata Dutta et al.
Summary of Probabilistic Bayesian Optimal Experimental Design Using Conditional Normalizing Flows, by Rafael Orozco et al.
Summary of Learning to Generate Instruction Tuning Datasets For Zero-shot Task Adaptation, by Nihal V. Nayak et al.
Summary of Feduv: Uniformity and Variance For Heterogeneous Federated Learning, by Ha Min Son et al.
Summary of Large Language Models As Evolution Strategies, by Robert Tjarko Lange et al.
Summary of Unveiling the Potential Of Robustness in Selecting Conditional Average Treatment Effect Estimators, by Yiyan Huang et al.
Summary of Can Gpt Improve the State Of Prior Authorization Via Guideline Based Automated Question Answering?, by Shubham Vatsal et al.
Summary of Emotion Classification in Low and Moderate Resource Languages, by Shabnam Tafreshi et al.
Summary of A Relational Inductive Bias For Dimensional Abstraction in Neural Networks, by Declan Campbell et al.
Summary of Graph Regularized Encoder Training For Extreme Classification, by Anshul Mittal et al.
Summary of Hop to the Next Tasks and Domains For Continual Learning in Nlp, by Umberto Michieli et al.
Summary of Lemo-nade: Multi-parameter Neural Architecture Discovery with Llms, by Md Hafizur Rahman and Prabuddha Chakraborty
Summary of Sample-efficient Preference-based Reinforcement Learning with Dynamics Aware Rewards, by Katherine Metcalf et al.
Summary of Flattenquant: Breaking Through the Inference Compute-bound For Large Language Models with Per-tensor Quantization, by Yi Zhang et al.
Summary of Imagine, Initialize, and Explore: An Effective Exploration Method in Multi-agent Reinforcement Learning, by Zeyang Liu et al.
Summary of Mixer Is More Than Just a Model, by Qingfeng Ji et al.
Summary of Diffusion Models As Constrained Samplers For Optimization with Unknown Constraints, by Lingkai Kong et al.
Summary of Communication Efficient Confederated Learning: An Event-triggered Saga Approach, by Bin Wang and Jun Fang and Hongbin Li and Yonina C. Eldar
Summary of Automated Discovery Of Integral with Deep Learning, by Xiaoxin Yin
Summary of Token-specific Watermarking with Enhanced Detectability and Semantic Coherence For Large Language Models, by Mingjia Huo et al.
Summary of Data Augmentation Method For Modeling Health Records with Applications to Clopidogrel Treatment Failure Detection, by Sunwoong Choi and Samuel Kim
Summary of No Token Left Behind: Reliable Kv Cache Compression Via Importance-aware Mixed Precision Quantization, by June Yong Yang et al.
Summary of Prcl: Probabilistic Representation Contrastive Learning For Semi-supervised Semantic Segmentation, by Haoyu Xie et al.
Summary of Hierarchical Multi-relational Graph Representation Learning For Large-scale Prediction Of Drug-drug Interactions, by Mengying Jiang et al.
Summary of Downstream Task Guided Masking Learning in Masked Autoencoders Using Multi-level Optimization, by Han Guo et al.
Summary of Classes Are Not Equal: An Empirical Study on Image Recognition Fairness, by Jiequan Cui et al.
Summary of On the Inductive Biases Of Demographic Parity-based Fair Learning Algorithms, by Haoyu Lei et al.
Summary of Provably Efficient Partially Observable Risk-sensitive Reinforcement Learning with Hindsight Observation, by Tonghe Zhang et al.
Summary of Diffusion-based Neural Network Weights Generation, by Bedionita Soro et al.
Summary of Provable Risk-sensitive Distributional Reinforcement Learning with General Function Approximation, by Yu Chen et al.
Summary of Autoencoder-based General Purpose Representation Learning For Customer Embedding, by Jan Henrik Bertrand et al.
Summary of Decentralised Traffic Incident Detection Via Network Lasso, by Qiyuan Zhu et al.
Summary of Graph Neural Networks and Arithmetic Circuits, by Timon Barlag et al.
Summary of Material Microstructure Design Using Vae-regression with Multimodal Prior, by Avadhut Sardeshmukh et al.
Summary of Truthx: Alleviating Hallucinations by Editing Large Language Models in Truthful Space, By Shaolei Zhang et al.
Summary of Dropbp: Accelerating Fine-tuning Of Large Language Models by Dropping Backward Propagation, By Sunghyeon Woo et al.
Summary of Follow My Instruction and Spill the Beans: Scalable Data Extraction From Retrieval-augmented Generation Systems, by Zhenting Qi et al.
Summary of Latent Neural Pde Solver: a Reduced-order Modelling Framework For Partial Differential Equations, by Zijie Li et al.
Summary of Prediction-powered Ranking Of Large Language Models, by Ivi Chatzi et al.
Summary of Automated Statistical Model Discovery with Language Models, by Michael Y. Li et al.
Summary of Independent Learning in Constrained Markov Potential Games, by Philip Jordan et al.
Summary of Zeroth-order Sampling Methods For Non-log-concave Distributions: Alleviating Metastability by Denoising Diffusion, By Ye He et al.
Summary of From Inverse Optimization to Feasibility to Erm, by Saurabh Mishra et al.
Summary of Conjnorm: Tractable Density Estimation For Out-of-distribution Detection, by Bo Peng et al.
Summary of Sequentialattention++ For Block Sparsification: Differentiable Pruning Meets Combinatorial Optimization, by Taisuke Yasuda et al.
Summary of Using Graph Neural Networks to Predict Local Culture, by Thiago H Silva and Daniel Silver
Summary of Representation Learning in Multiplex Graphs: Where and How to Fuse Information?, by Piotr Bielak et al.
Summary of Certain and Approximately Certain Models For Statistical Learning, by Cheng Zhen et al.
Summary of Collaborative Learning Of Common Latent Representations in Routinely Collected Multivariate Icu Physiological Signals, by Hollan Haule et al.