Paper List

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Summary of Understanding and Mitigating Difficulties in Posterior Predictive Evaluation, by Abhinav Agrawal and Justin Domke
Summary of Improving Smote Via Fusing Conditional Vae For Data-adaptive Noise Filtering, by Sungchul Hong et al.
Summary of Identifiability Of a Statistical Model with Two Latent Vectors: Importance Of the Dimensionality Relation and Application to Graph Embedding, by Hiroaki Sasaki
Summary of Instruction-guided Visual Masking, by Jinliang Zheng et al.
Summary of Crowdsourcing with Difficulty: a Bayesian Rating Model For Heterogeneous Items, by Seong Woo Han et al.
Summary of Contrasting Multiple Representations with the Multi-marginal Matching Gap, by Zoe Piran et al.
Summary of Preference Learning Algorithms Do Not Learn Preference Rankings, by Angelica Chen et al.
Summary of Chexpert Plus: Augmenting a Large Chest X-ray Dataset with Text Radiology Reports, Patient Demographics and Additional Image Formats, by Pierre Chambon et al.
Summary of One-shot Safety Alignment For Large Language Models Via Optimal Dualization, by Xinmeng Huang et al.
Summary of Cliploss and Norm-based Data Selection Methods For Multimodal Contrastive Learning, by Yiping Wang et al.
Summary of Rlexplore: Accelerating Research in Intrinsically-motivated Reinforcement Learning, by Mingqi Yuan et al.
Summary of Stress-testing Capability Elicitation with Password-locked Models, by Ryan Greenblatt et al.
Summary of Clustering Mixtures Of Discrete Distributions: a Note on Mitra’s Algorithm, by Mohamed Seif et al.
Summary of Sam-e: Leveraging Visual Foundation Model with Sequence Imitation For Embodied Manipulation, by Junjie Zhang et al.
Summary of Dr-llava: Visual Instruction Tuning with Symbolic Clinical Grounding, by Shenghuan Sun et al.
Summary of Weights Augmentation: It Has Never Ever Ever Ever Let Her Model Down, by Junbin Zhuang et al.
Summary of Why Larger Language Models Do In-context Learning Differently?, by Zhenmei Shi et al.
Summary of Svft: Parameter-efficient Fine-tuning with Singular Vectors, by Vijay Lingam et al.
Summary of Rethinking Spectral Augmentation For Contrast-based Graph Self-supervised Learning, by Xiangru Jian et al.
Summary of Easy Problems That Llms Get Wrong, by Sean Williams et al.
Summary of Factor Augmented Tensor-on-tensor Neural Networks, by Guanhao Zhou et al.
Summary of Egosurgery-phase: a Dataset Of Surgical Phase Recognition From Egocentric Open Surgery Videos, by Ryo Fujii and Masashi Hatano and Hideo Saito and Hiroki Kajita
Summary of Detecting Hallucinations in Large Language Model Generation: a Token Probability Approach, by Ernesto Quevedo et al.
Summary of Fts: a Framework to Find a Faithful Timesieve, by Songning Lai et al.
Summary of Robust Preference Optimization Through Reward Model Distillation, by Adam Fisch et al.
Summary of Generalized Neyman Allocation For Locally Minimax Optimal Best-arm Identification, by Masahiro Kato
Summary of Value-incentivized Preference Optimization: a Unified Approach to Online and Offline Rlhf, by Shicong Cen et al.
Summary of Map-neo: Highly Capable and Transparent Bilingual Large Language Model Series, by Ge Zhang et al.
Summary of Are Large Language Models Chameleons? An Attempt to Simulate Social Surveys, by Mingmeng Geng et al.
Summary of Self-exploring Language Models: Active Preference Elicitation For Online Alignment, by Shenao Zhang et al.
Summary of X-vila: Cross-modality Alignment For Large Language Model, by Hanrong Ye et al.
Summary of Optimal Multiclass U-calibration Error and Beyond, by Haipeng Luo et al.
Summary of Safety Through Permissibility: Shield Construction For Fast and Safe Reinforcement Learning, by Alexander Politowicz et al.
Summary of Pureebm: Universal Poison Purification Via Mid-run Dynamics Of Energy-based Models, by Omead Pooladzandi et al.
Summary of Learning Human-aligned Representations with Contrastive Learning and Generative Similarity, by Raja Marjieh et al.
Summary of Mgda Converges Under Generalized Smoothness, Provably, by Qi Zhang et al.
Summary of Deep Grokking: Would Deep Neural Networks Generalize Better?, by Simin Fan et al.
Summary of Clustering-based Validation Splits For Model Selection Under Domain Shift, by Andrea Napoli et al.
Summary of Stochastic Optimization Algorithms For Instrumental Variable Regression with Streaming Data, by Xuxing Chen et al.
Summary of Active Exploration Via Autoregressive Generation Of Missing Data, by Tiffany Tianhui Cai et al.
Summary of Online Nonparametric Supervised Learning For Massive Data, by Mohamed Chaouch et al.
Summary of The Data Minimization Principle in Machine Learning, by Prakhar Ganesh et al.
Summary of Momentum For the Win: Collaborative Federated Reinforcement Learning Across Heterogeneous Environments, by Han Wang et al.
Summary of Decentralized Optimization in Time-varying Networks with Arbitrary Delays, by Tomas Ortega et al.
Summary of Vulnerable Road User Detection and Safety Enhancement: a Comprehensive Survey, by Renato M. Silva et al.
Summary of Gone but Not Forgotten: Improved Benchmarks For Machine Unlearning, by Keltin Grimes et al.
Summary of Gradient Guided Hypotheses: a Unified Solution to Enable Machine Learning Models on Scarce and Noisy Data Regimes, by Paulo Neves et al.
Summary of Synthetic Potential Outcomes and Causal Mixture Identifiability, by Bijan Mazaheri and Chandler Squires and Caroline Uhler
Summary of Partial Information Decomposition For Data Interpretability and Feature Selection, by Charles Westphal et al.
Summary of Valid Conformal Prediction For Dynamic Gnns, by Ed Davis et al.
Summary of Exploring the Impact Of Traffic Signal Control and Connected and Automated Vehicles on Intersections Safety: a Deep Reinforcement Learning Approach, by Amir Hossein Karbasi et al.
Summary of Forward-backward Knowledge Distillation For Continual Clustering, by Mohammadreza Sadeghi et al.
Summary of Comparative Study Of Neighbor-based Methods For Local Outlier Detection, by Zhuang Qi et al.
Summary of Conceptprune: Concept Editing in Diffusion Models Via Skilled Neuron Pruning, by Ruchika Chavhan and Da Li and Timothy Hospedales
Summary of Weak Generative Sampler to Efficiently Sample Invariant Distribution Of Stochastic Differential Equation, by Zhiqiang Cai et al.
Summary of Weak-to-strong Search: Align Large Language Models Via Searching Over Small Language Models, by Zhanhui Zhou et al.
Summary of Faster Cascades Via Speculative Decoding, by Harikrishna Narasimhan et al.
Summary of Rich-observation Reinforcement Learning with Continuous Latent Dynamics, by Yuda Song et al.
Summary of Differentially Private Clustered Federated Learning, by Saber Malekmohammadi et al.
Summary of Deep Latent Variable Modeling Of Physiological Signals, by Khuong Vo
Summary of Neural Isometries: Taming Transformations For Equivariant Ml, by Thomas W. Mitchel et al.
Summary of Understanding and Minimising Outlier Features in Neural Network Training, by Bobby He et al.
Summary of Measuring and Mitigating Bias For Tabular Datasets with Multiple Protected Attributes, by Manh Khoi Duong et al.
Summary of Matryoshka Query Transformer For Large Vision-language Models, by Wenbo Hu et al.
Summary of Statistical Context Detection For Deep Lifelong Reinforcement Learning, by Jeffery Dick et al.
Summary of Robust Entropy Search For Safe Efficient Bayesian Optimization, by Dorina Weichert et al.
Summary of Sig: Efficient Self-interpretable Graph Neural Network For Continuous-time Dynamic Graphs, by Lanting Fang et al.
Summary of Relevance-aware Algorithmic Recourse, by Dongwhi Kim et al.
Summary of Cephalo: Multi-modal Vision-language Models For Bio-inspired Materials Analysis and Design, by Markus J. Buehler
Summary of Ompo: a Unified Framework For Rl Under Policy and Dynamics Shifts, by Yu Luo et al.
Summary of Efficient Black-box Adversarial Attacks Via Bayesian Optimization Guided by a Function Prior, By Shuyu Cheng et al.
Summary of Poseidon: Efficient Foundation Models For Pdes, by Maximilian Herde et al.
Summary of Offline Regularised Reinforcement Learning For Large Language Models Alignment, by Pierre Harvey Richemond et al.
Summary of Spatio-spectral Graph Neural Networks, by Simon Geisler et al.
Summary of Can Graph Learning Improve Planning in Llm-based Agents?, by Xixi Wu et al.
Summary of A Study Of Plasticity Loss in On-policy Deep Reinforcement Learning, by Arthur Juliani et al.
Summary of I Bet You Did Not Mean That: Testing Semantic Importance Via Betting, by Jacopo Teneggi et al.
Summary of Beyond Discrepancy: a Closer Look at the Theory Of Distribution Shift, by Robi Bhattacharjee et al.
Summary of Does Learning the Right Latent Variables Necessarily Improve In-context Learning?, by Sarthak Mittal et al.
Summary of Transformers As Neural Operators For Solutions Of Differential Equations with Finite Regularity, by Benjamin Shih et al.
Summary of Metatoken: Detecting Hallucination in Image Descriptions by Meta Classification, By Laura Fieback (1 et al.
Summary of Online Linear Regression in Dynamic Environments Via Discounting, by Andrew Jacobsen and Ashok Cutkosky
Summary of Long-horizon Rollout Via Dynamics Diffusion For Offline Reinforcement Learning, by Hanye Zhao et al.
Summary of Matrix Manifold Neural Networks++, by Xuan Son Nguyen and Shuo Yang and Aymeric Histace
Summary of Lspi: Heterogeneous Graph Neural Network Classification Aggregation Algorithm Based on Size Neighbor Path Identification, by Yufei Zhao et al.
Summary of Wttfnet: a Weather-time-trajectory Fusion Network For Pedestrian Trajectory Prediction in Urban Complex, by Ho Chun Wu et al.
Summary of Are You Sure? Rank Them Again: Repeated Ranking For Better Preference Datasets, by Peter Devine
Summary of Magic: Modular Auto-encoder For Generalisable Model Inversion with Bias Corrections, by Yihang She et al.
Summary of Uniif: Unified Molecule Inverse Folding, by Zhangyang Gao et al.
Summary of Federated Learning with Bilateral Curation For Partially Class-disjoint Data, by Ziqing Fan et al.
Summary of Hierarchical Classification Auxiliary Network For Time Series Forecasting, by Yanru Sun et al.
Summary of Mano: Exploiting Matrix Norm For Unsupervised Accuracy Estimation Under Distribution Shifts, by Renchunzi Xie et al.
Summary of Federated Learning Under Partially Class-disjoint Data Via Manifold Reshaping, by Ziqing Fan et al.
Summary of Optimizing Vehicular Networks with Variational Quantum Circuits-based Reinforcement Learning, by Zijiang Yan et al.
Summary of Robust Optimization in Protein Fitness Landscapes Using Reinforcement Learning in Latent Space, by Minji Lee et al.
Summary of Kernel Semi-implicit Variational Inference, by Ziheng Cheng et al.
Summary of Efficient Exploration in Average-reward Constrained Reinforcement Learning: Achieving Near-optimal Regret with Posterior Sampling, by Danil Provodin et al.
Summary of Trust the Model Where It Trusts Itself — Model-based Actor-critic with Uncertainty-aware Rollout Adaption, by Bernd Frauenknecht et al.
Summary of Fedmap: Unlocking Potential in Personalized Federated Learning Through Bi-level Map Optimization, by Fan Zhang et al.
Summary of Physics-aware Neural Implicit Solvers For Multiscale, Parametric Pdes with Applications in Heterogeneous Media, by Matthaios Chatzopoulos et al.