Paper List

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Summary of Biasbuster: a Neural Approach For Accurate Estimation Of Population Statistics Using Biased Location Data, by Sepanta Zeighami et al.
Summary of Fair Classification with Partial Feedback: An Exploration-based Data Collection Approach, by Vijay Keswani et al.
Summary of Expressive Higher-order Link Prediction Through Hypergraph Symmetry Breaking, by Simon Zhang et al.
Summary of The Evolution Of Statistical Induction Heads: In-context Learning Markov Chains, by Benjamin L. Edelman et al.
Summary of Training Bayesian Neural Networks with Sparse Subspace Variational Inference, by Junbo Li et al.
Summary of Occlusion Resilient 3d Human Pose Estimation, by Soumava Kumar Roy et al.
Summary of Model Editing by Standard Fine-tuning, By Govind Gangadhar et al.
Summary of Robustness to Subpopulation Shift with Domain Label Noise Via Regularized Annotation Of Domains, by Nathan Stromberg and Rohan Ayyagari and Monica Welfert and Sanmi Koyejo and Richard Nock and Lalitha Sankar
Summary of Modular Graph Extraction For Handwritten Circuit Diagram Images, by Johannes Bayer et al.
Summary of Towards Financially Inclusive Credit Products Through Financial Time Series Clustering, by Tristan Bester et al.
Summary of Toward Learning Latent-variable Representations Of Microstructures by Optimizing in Spatial Statistics Space, By Sayed Sajad Hashemi et al.
Summary of Private Pac Learning May Be Harder Than Online Learning, by Mark Bun et al.
Summary of Dynamic Nowcast Of the New Zealand Greenhouse Gas Inventory, by Malcolm Jones et al.
Summary of Dart: a Principled Approach to Adversarially Robust Unsupervised Domain Adaptation, by Yunjuan Wang et al.
Summary of Optimizing Warfarin Dosing Using Contextual Bandit: An Offline Policy Learning and Evaluation Method, by Yong Huang et al.
Summary of Implicit Causal Representation Learning Via Switchable Mechanisms, by Shayan Shirahmad Gale Bagi and Zahra Gharaee and Oliver Schulte and Mark Crowley
Summary of Kolmogorov N-widths For Multitask Physics-informed Machine Learning (piml) Methods: Towards Robust Metrics, by Michael Penwarden et al.
Summary of Speculative Streaming: Fast Llm Inference Without Auxiliary Models, by Nikhil Bhendawade et al.
Summary of Tunetables: Context Optimization For Scalable Prior-data Fitted Networks, by Benjamin Feuer et al.
Summary of Contrastive Instruction Tuning, by Tianyi Lorena Yan et al.
Summary of Lignn: Graph Neural Networks at Linkedin, by Fedor Borisyuk et al.
Summary of Boosting Of Thoughts: Trial-and-error Problem Solving with Large Language Models, by Sijia Chen et al.
Summary of Knowledge Distillation Based on Transformed Teacher Matching, by Kaixiang Zheng and En-hui Yang
Summary of When Is Tree Search Useful For Llm Planning? It Depends on the Discriminator, by Ziru Chen et al.
Summary of Instruction Diversity Drives Generalization to Unseen Tasks, by Dylan Zhang et al.
Summary of Rlvf: Learning From Verbal Feedback Without Overgeneralization, by Moritz Stephan et al.
Summary of Fusion Of Diffusion Weighted Mri and Clinical Data For Predicting Functional Outcome After Acute Ischemic Stroke with Deep Contrastive Learning, by Chia-ling Tsai et al.
Summary of Neural Machine Translation Of Clinical Procedure Codes For Medical Diagnosis and Uncertainty Quantification, by Pei-hung Chung et al.
Summary of Text2data: Low-resource Data Generation with Textual Control, by Shiyu Wang et al.
Summary of Llm-assisted Crisis Management: Building Advanced Llm Platforms For Effective Emergency Response and Public Collaboration, by Hakan T. Otal and M. Abdullah Canbaz
Summary of Culturellm: Incorporating Cultural Differences Into Large Language Models, by Cheng Li et al.
Summary of The Unreasonable Effectiveness Of Eccentric Automatic Prompts, by Rick Battle and Teja Gollapudi
Summary of Daedra: a Language Model For Predicting Outcomes in Passive Pharmacovigilance Reporting, by Chris Von Csefalvay
Summary of Relative Preference Optimization: Enhancing Llm Alignment Through Contrasting Responses Across Identical and Diverse Prompts, by Yueqin Yin et al.
Summary of Glore: When, Where, and How to Improve Llm Reasoning Via Global and Local Refinements, by Alex Havrilla et al.
Summary of Generalization in Healthcare Ai: Evaluation Of a Clinical Large Language Model, by Salman Rahman et al.
Summary of Measuring and Controlling Instruction (in)stability in Language Model Dialogs, by Kenneth Li et al.
Summary of Generative Ai and Process Systems Engineering: the Next Frontier, by Benjamin Decardi-nelson et al.
Summary of Quantum-inspired Analysis Of Neural Network Vulnerabilities: the Role Of Conjugate Variables in System Attacks, by Jun-jie Zhang et al.
Summary of Language Models with Conformal Factuality Guarantees, by Christopher Mohri et al.
Summary of Mshw, a Forecasting Library to Predict Short-term Electricity Demand Based on Multiple Seasonal Holt-winters, by Oscar Trull et al.
Summary of Enhancing Convergence in Federated Learning: a Contribution-aware Asynchronous Approach, by Changxin Xu et al.
Summary of Analysis and Mortality Prediction Using Multiclass Classification For Older Adults with Type 2 Diabetes, by Ruchika Desure et al.
Summary of Towards Cohesion-fairness Harmony: Contrastive Regularization in Individual Fair Graph Clustering, by Siamak Ghodsi et al.
Summary of Conformalized Credal Set Predictors, by Alireza Javanmardi et al.
Summary of Stochastic Localization Via Iterative Posterior Sampling, by Louis Grenioux et al.
Summary of Policy Learning For Off-dynamics Rl with Deficient Support, by Linh Le Pham Van and Hung the Tran and Sunil Gupta
Summary of Edgeqat: Entropy and Distribution Guided Quantization-aware Training For the Acceleration Of Lightweight Llms on the Edge, by Xuan Shen et al.
Summary of In Search Of Needles in a 11m Haystack: Recurrent Memory Finds What Llms Miss, by Yuri Kuratov et al.
Summary of An End-to-end Attention-based Approach For Learning on Graphs, by David Buterez et al.
Summary of Timeseriesbench: An Industrial-grade Benchmark For Time Series Anomaly Detection Models, by Haotian Si et al.
Summary of Diversified Ensembling: An Experiment in Crowdsourced Machine Learning, by Ira Globus-harris et al.
Summary of Double Duality: Variational Primal-dual Policy Optimization For Constrained Reinforcement Learning, by Zihao Li et al.
Summary of Associative Memories in the Feature Space, by Tommaso Salvatori et al.
Summary of Trading Off Consistency and Dimensionality Of Convex Surrogates For the Mode, by Enrique Nueve et al.
Summary of Ternaryvote: Differentially Private, Communication Efficient, and Byzantine Resilient Distributed Optimization on Heterogeneous Data, by Richeng Jin et al.
Summary of Learning Goal-conditioned Policies From Sub-optimal Offline Data Via Metric Learning, by Alfredo Reichlin et al.
Summary of Fedd2s: Personalized Data-free Federated Knowledge Distillation, by Kawa Atapour et al.
Summary of Differential Private Federated Transfer Learning For Mental Health Monitoring in Everyday Settings: a Case Study on Stress Detection, by Ziyu Wang et al.
Summary of Best Of Three Worlds: Adaptive Experimentation For Digital Marketing in Practice, by Tanner Fiez et al.
Summary of Robust Agents Learn Causal World Models, by Jonathan Richens et al.
Summary of Explainability For Machine Learning Models: From Data Adaptability to User Perception, by Julien Delaunay
Summary of Multi-modal Preference Alignment Remedies Degradation Of Visual Instruction Tuning on Language Models, by Shengzhi Li et al.
Summary of Active Preference Optimization For Sample Efficient Rlhf, by Nirjhar Das et al.
Summary of Can Transformers Predict Vibrations?, by Fusataka Kuniyoshi et al.
Summary of Any-precision Llm: Low-cost Deployment Of Multiple, Different-sized Llms, by Yeonhong Park et al.
Summary of Properties and Challenges Of Llm-generated Explanations, by Jenny Kunz et al.
Summary of Personalised Drug Identifier For Cancer Treatment with Transformers Using Auxiliary Information, by Aishwarya Jayagopal et al.
Summary of Direct Preference Optimization with An Offset, by Afra Amini et al.
Summary of Optimizing Adaptive Experiments: a Unified Approach to Regret Minimization and Best-arm Identification, by Chao Qin et al.
Summary of Symbolic Autoencoding For Self-supervised Sequence Learning, by Mohammad Hossein Amani et al.
Summary of Can Llms Speak For Diverse People? Tuning Llms Via Debate to Generate Controllable Controversial Statements, by Ming Li et al.
Summary of Efficient Multi-task Uncertainties For Joint Semantic Segmentation and Monocular Depth Estimation, by Steven Landgraf et al.
Summary of Multitask Kernel-based Learning with Logic Constraints, by Michelangelo Diligenti et al.
Summary of Graph-based Forecasting with Missing Data Through Spatiotemporal Downsampling, by Ivan Marisca et al.
Summary of Contiformer: Continuous-time Transformer For Irregular Time Series Modeling, by Yuqi Chen et al.
Summary of Linear Transformers with Learnable Kernel Functions Are Better In-context Models, by Yaroslav Aksenov et al.
Summary of Selective Prediction For Semantic Segmentation Using Post-hoc Confidence Estimation and Its Performance Under Distribution Shift, by Bruno Laboissiere Camargos Borges et al.
Summary of Exploring Precision and Recall to Assess the Quality and Diversity Of Llms, by Florian Le Bronnec et al.
Summary of Performance Gaps in Multi-view Clustering Under the Nested Matrix-tensor Model, by Hugo Lebeau et al.
Summary of Unlink to Unlearn: Simplifying Edge Unlearning in Gnns, by Jiajun Tan et al.
Summary of Machine Learning Based Prediction Of Ditching Loads, by Henning Schwarz et al.
Summary of From Risk to Uncertainty: Generating Predictive Uncertainty Measures Via Bayesian Estimation, by Nikita Kotelevskii et al.
Summary of Polyhedral Complex Derivation From Piecewise Trilinear Networks, by Jin-hwa Kim
Summary of Parametric Augmentation For Time Series Contrastive Learning, by Xu Zheng et al.
Summary of Understanding Survey Paper Taxonomy About Large Language Models Via Graph Representation Learning, by Jun Zhuang et al.
Summary of Measuring and Reducing Llm Hallucination Without Gold-standard Answers, by Jiaheng Wei et al.
Summary of Fixed Confidence Best Arm Identification in the Bayesian Setting, by Kyoungseok Jang et al.
Summary of Collaborative Learning with Different Labeling Functions, by Yuyang Deng et al.
Summary of Incremental Sequence Labeling: a Tale Of Two Shifts, by Shengjie Qiu et al.
Summary of Prise: Llm-style Sequence Compression For Learning Temporal Action Abstractions in Control, by Ruijie Zheng et al.
Summary of Efficient Generative Modeling Via Penalized Optimal Transport Network, by Wenhui Sophia Lu et al.
Summary of Qdylora: Quantized Dynamic Low-rank Adaptation For Efficient Large Language Model Tuning, by Hossein Rajabzadeh et al.
Summary of Fedkit: Enabling Cross-platform Federated Learning For Android and Ios, by Sichang He et al.
Summary of Theoretical Understanding Of Learning From Adversarial Perturbations, by Soichiro Kumano et al.
Summary of Adversarial Curriculum Graph Contrastive Learning with Pair-wise Augmentation, by Xinjian Zhao et al.
Summary of One-bit Quantization and Sparsification For Multiclass Linear Classification with Strong Regularization, by Reza Ghane et al.
Summary of Privacy For Fairness: Information Obfuscation For Fair Representation Learning with Local Differential Privacy, by Songjie Xie et al.
Summary of Understanding Likelihood Of Normalizing Flow and Image Complexity Through the Lens Of Out-of-distribution Detection, by Genki Osada et al.
Summary of Codamal: Contrastive Domain Adaptation For Malaria Detection in Low-cost Microscopes, by Ishan Rajendrakumar Dave et al.