Paper List

We recommend you use the search box as this list is very long.

Summary of Molfusion: Multimodal Fusion Learning For Molecular Representations Via Multi-granularity Views, by Muzhen Cai et al.
Summary of Boosting Soft Q-learning by Bounding, By Jacob Adamczyk et al.
Summary of Local Linear Recovery Guarantee Of Deep Neural Networks at Overparameterization, by Yaoyu Zhang et al.
Summary of Mt2st: Adaptive Multi-task to Single-task Learning, by Dong Liu et al.
Summary of Calmqa: Exploring Culturally Specific Long-form Question Answering Across 23 Languages, by Shane Arora et al.
Summary of Deep Learning Approaches For Detecting Adversarial Cyberbullying and Hate Speech in Social Networks, by Sylvia Worlali Azumah et al.
Summary of Training-free Exponential Context Extension Via Cascading Kv Cache, by Jeffrey Willette et al.
Summary of Mossbench: Is Your Multimodal Language Model Oversensitive to Safe Queries?, by Xirui Li et al.
Summary of Scalable Artificial Intelligence For Science: Perspectives, Methods and Exemplars, by Wesley Brewer et al.
Summary of Unsupervised Concept Drift Detection From Deep Learning Representations in Real-time, by Salvatore Greco et al.
Summary of Temporal Prototype-aware Learning For Active Voltage Control on Power Distribution Networks, by Feiyang Xu et al.
Summary of Distribution Learnability and Robustness, by Shai Ben-david et al.
Summary of Automatically Adaptive Conformal Risk Control, by Vincent Blot (lisn et al.
Summary of Ai For the Prediction Of Early Stages Of Alzheimer’s Disease From Neuroimaging Biomarkers — a Narrative Review Of a Growing Field, by Thorsten Rudroff et al.
Summary of European Space Agency Benchmark For Anomaly Detection in Satellite Telemetry, by Krzysztof Kotowski et al.
Summary of Treatment Of Statistical Estimation Problems in Randomized Smoothing For Adversarial Robustness, by Vaclav Voracek
Summary of Empirical Bayes For Dynamic Bayesian Networks Using Generalized Variational Inference, by Vyacheslav Kungurtsev et al.
Summary of Univariate Skeleton Prediction in Multivariate Systems Using Transformers, by Giorgio Morales et al.
Summary of The Use Of Ai-robotic Systems For Scientific Discovery, by Alexander H. Gower et al.
Summary of Transformer Normalisation Layers and the Independence Of Semantic Subspaces, by Stephen Menary et al.
Summary of Inficond: Interactive No-code Fine-tuning with Concept-based Knowledge Distillation, by Jinbin Huang et al.
Summary of Et Tu, Clip? Addressing Common Object Errors For Unseen Environments, by Ye Won Byun et al.
Summary of Enabling Regional Explainability by Automatic and Model-agnostic Rule Extraction, By Yu Chen et al.
Summary of Ctbench: a Comprehensive Benchmark For Evaluating Language Model Capabilities in Clinical Trial Design, by Nafis Neehal et al.
Summary of Learning Dynamic Bayesian Networks From Data: Foundations, First Principles and Numerical Comparisons, by Vyacheslav Kungurtsev et al.
Summary of Distributed Training Of Large Graph Neural Networks with Variable Communication Rates, by Juan Cervino et al.
Summary of Knowledge Distillation in Automated Annotation: Supervised Text Classification with Llm-generated Training Labels, by Nicholas Pangakis and Samuel Wolken
Summary of Mitigate the Gap: Investigating Approaches For Improving Cross-modal Alignment in Clip, by Sedigheh Eslami and Gerard De Melo
Summary of Baytta: Uncertainty-aware Medical Image Classification with Optimized Test-time Augmentation Using Bayesian Model Averaging, by Zeinab Sherkatghanad et al.
Summary of Privacy Preserving Reinforcement Learning For Population Processes, by Samuel Yang-zhao et al.
Summary of Grass: Compute Efficient Low-memory Llm Training with Structured Sparse Gradients, by Aashiq Muhamed et al.
Summary of Latable: Towards Large Tabular Models, by Boris Van Breugel et al.
Summary of From Distributional to Overton Pluralism: Investigating Large Language Model Alignment, by Thom Lake et al.
Summary of Hgtdp-dta: Hybrid Graph-transformer with Dynamic Prompt For Drug-target Binding Affinity Prediction, by Xi Xiao and Wentao Wang and Jiacheng Xie and Lijing Zhu and Gaofei Chen and Zhengji Li and Tianyang Wang and Min Xu
Summary of Identifying Nonstationary Causal Structures with High-order Markov Switching Models, by Carles Balsells-rodas et al.
Summary of Fedbiot: Llm Local Fine-tuning in Federated Learning Without Full Model, by Feijie Wu et al.
Summary of Data Curation Via Joint Example Selection Further Accelerates Multimodal Learning, by Talfan Evans et al.
Summary of Compositional Models For Estimating Causal Effects, by Purva Pruthi and David Jensen
Summary of When Does Self-prediction Help? Understanding Auxiliary Tasks in Reinforcement Learning, by Claas Voelcker et al.
Summary of Llm Targeted Underperformance Disproportionately Impacts Vulnerable Users, by Elinor Poole-dayan et al.
Summary of Structured Unrestricted-rank Matrices For Parameter Efficient Fine-tuning, by Arijit Sehanobish et al.
Summary of A New Perspective on Shampoo’s Preconditioner, by Depen Morwani et al.
Summary of Interpreting Attention Layer Outputs with Sparse Autoencoders, by Connor Kissane et al.
Summary of Diffusionpde: Generative Pde-solving Under Partial Observation, by Jiahe Huang et al.
Summary of Generative Modelling Of Structurally Constrained Graphs, by Manuel Madeira et al.
Summary of Xami — a Benchmark Dataset For Artefact Detection in Xmm-newton Optical Images, by Elisabeta-iulia Dima et al.
Summary of Stacked Confusion Reject Plots (score), by Stephan Hasler and Lydia Fischer
Summary of Generalizability Of Experimental Studies, by Federico Matteucci et al.
Summary of Forget but Recall: Incremental Latent Rectification in Continual Learning, by Nghia D. Nguyen et al.
Summary of Gradcheck: Analyzing Classifier Guidance Gradients For Conditional Diffusion Sampling, by Philipp Vaeth et al.
Summary of Layer-wise Quantization: a Pragmatic and Effective Method For Quantizing Llms Beyond Integer Bit-levels, by Razvan-gabriel Dumitru et al.
Summary of Make Some Noise: Unlocking Language Model Parallel Inference Capability Through Noisy Training, by Yixuan Wang et al.
Summary of Se-vgae: Unsupervised Disentangled Representation Learning For Interpretable Architectural Layout Design Graph Generation, by Jielin Chen and Rudi Stouffs
Summary of Cuda2: An Approach For Incorporating Traitor Agents Into Cooperative Multi-agent Systems, by Zhen Chen and Yong Liao and Youpeng Zhao and Zipeng Dai and Jian Zhao
Summary of A Critical Analysis Of the Theoretical Framework Of the Extreme Learning Machine, by Irina Perfilievaa et al.
Summary of Mind the Graph When Balancing Data For Fairness or Robustness, by Jessica Schrouff et al.
Summary of Early Learning Of the Optimal Constant Solution in Neural Networks and Humans, by Jirko Rubruck et al.
Summary of Dynamic Scheduling For Vehicle-to-vehicle Communications Enhanced Federated Learning, by Jintao Yan et al.
Summary of Wave: Weight Templates For Adaptive Initialization Of Variable-sized Models, by Fu Feng et al.
Summary of Preserving Node Distinctness in Graph Autoencoders Via Similarity Distillation, by Ge Chen et al.
Summary of On the Consistency Of Hyper-parameter Selection in Value-based Deep Reinforcement Learning, by Johan Obando-ceron et al.
Summary of Cdquant: Greedy Coordinate Descent For Accurate Llm Quantization, by Pranav Ajit Nair and Arun Sai Suggala
Summary of Multi-property Steering Of Large Language Models with Dynamic Activation Composition, by Daniel Scalena et al.
Summary of Towards Compositional Interpretability For Xai, by Sean Tull et al.
Summary of Peirce in the Machine: How Mixture Of Experts Models Perform Hypothesis Construction, by Bruce Rushing
Summary of Virtual Mines — Component-level Recycling Of Printed Circuit Boards Using Deep Learning, by Muhammad Mohsin et al.
Summary of Paraphrase and Aggregate with Large Language Models For Minimizing Intent Classification Errors, by Vikas Yadav and Zheng Tang and Vijay Srinivasan
Summary of Learning on Transformers Is Provable Low-rank and Sparse: a One-layer Analysis, by Hongkang Li et al.
Summary of Reinforcement Learning Via Auxiliary Task Distillation, by Abhinav Narayan Harish et al.
Summary of Minimax Optimality in Contextual Dynamic Pricing with General Valuation Models, by Xueping Gong and Jiheng Zhang
Summary of Machine Unlearning Fails to Remove Data Poisoning Attacks, by Martin Pawelczyk et al.
Summary of Contrastive General Graph Matching with Adaptive Augmentation Sampling, by Jianyuan Bo et al.
Summary of Geometric Median (gm) Matching For Robust Data Pruning, by Anish Acharya et al.
Summary of Large Language Models Are Interpretable Learners, by Ruochen Wang and Si Si and Felix Yu and Dorothea Wiesmann and Cho-jui Hsieh and Inderjit Dhillon
Summary of Greedy Equivalence Search For Nonparametric Graphical Models, by Bryon Aragam
Summary of Generative Expansion Of Small Datasets: An Expansive Graph Approach, by Vahid Jebraeeli et al.
Summary of Unlocking Continual Learning Abilities in Language Models, by Wenyu Du et al.
Summary of Topogcl: Topological Graph Contrastive Learning, by Yuzhou Chen and Jose Frias and Yulia R. Gel
Summary of Efficient, Multimodal, and Derivative-free Bayesian Inference with Fisher-rao Gradient Flows, by Yifan Chen and Daniel Zhengyu Huang and Jiaoyang Huang and Sebastian Reich and Andrew M. Stuart
Summary of A Comprehensive Solution to Connect Speech Encoder and Large Language Model For Asr, by Van Tung Pham et al.
Summary of Can We Trust the Performance Evaluation Of Uncertainty Estimation Methods in Text Summarization?, by Jianfeng He et al.
Summary of Adaptive Topology Reconstruction For Robust Graph Representation Learning, by Dong Liu et al.
Summary of Blockllm: Memory-efficient Adaptation Of Llms by Selecting and Optimizing the Right Coordinate Blocks, By Amrutha Varshini Ramesh et al.
Summary of Towards Efficient and Scalable Training Of Differentially Private Deep Learning, by Sebastian Rodriguez Beltran et al.
Summary of Metafollower: Adaptable Personalized Autonomous Car Following, by Xianda Chen et al.
Summary of Research on Disease Prediction Model Construction Based on Computer Ai Deep Learning Technology, by Yang Lin et al.
Summary of Machine Unlearning with Minimal Gradient Dependence For High Unlearning Ratios, by Tao Huang et al.
Summary of Unveiling Llm Mechanisms Through Neural Odes and Control Theory, by Yukun Zhang et al.
Summary of Md Tree: a Model-diagnostic Tree Grown on Loss Landscape, by Yefan Zhou et al.
Summary of Make Graph Neural Networks Great Again: a Generic Integration Paradigm Of Topology-free Patterns For Traffic Speed Prediction, by Yicheng Zhou et al.
Summary of Retrieval-augmented Mixture Of Lora Experts For Uploadable Machine Learning, by Ziyu Zhao et al.
Summary of Gate Recurrent Unit For Efficient Industrial Gas Identification, by Ding Wang
Summary of Identifying Easy Instances to Improve Efficiency Of Ml Pipelines For Algorithm-selection, by Quentin Renau and Emma Hart
Summary of Deep Learning For Prediction and Classifying the Dynamical Behaviour Of Piecewise Smooth Maps, by Vismaya V S et al.
Summary of Meta-gcn: a Dynamically Weighted Loss Minimization Method For Dealing with the Data Imbalance in Graph Neural Networks, by Mahdi Mohammadizadeh et al.
Summary of Large Language Models Assume People Are More Rational Than We Really Are, by Ryan Liu et al.
Summary of Learning Temporal Distances: Contrastive Successor Features Can Provide a Metric Structure For Decision-making, by Vivek Myers et al.
Summary of Model-free Robust Reinforcement Learning with Sample Complexity Analysis, by Yudan Wang et al.
Summary of Achieving Fairness Across Local and Global Models in Federated Learning, by Disha Makhija et al.
Summary of Integrating Generative Ai with Network Digital Twins For Enhanced Network Operations, by Kassi Muhammad and Teef David and Giulia Nassisid and Tina Farus