Paper List

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Summary of Optimizing Cnn-bigru Performance: Mish Activation and Comparative Analysis with Relu, by Asmaa Benchama and Khalid Zebbara
Summary of How Multilingual Are Large Language Models Fine-tuned For Translation?, by Aquia Richburg and Marine Carpuat
Summary of Spot: Text Source Prediction From Originality Score Thresholding, by Edouard Yvinec et al.
Summary of Large Language Models Can Self-improve at Web Agent Tasks, by Ajay Patel et al.
Summary of Group Robust Preference Optimization in Reward-free Rlhf, by Shyam Sundhar Ramesh et al.
Summary of Sequence-augmented Se(3)-flow Matching For Conditional Protein Backbone Generation, by Guillaume Huguet et al.
Summary of Quriosity: Analyzing Human Questioning Behavior and Causal Inquiry Through Curiosity-driven Queries, by Roberto Ceraolo et al.
Summary of Improving the Training Of Rectified Flows, by Sangyun Lee et al.
Summary of Don’t Drop Your Samples! Coherence-aware Training Benefits Conditional Diffusion, by Nicolas Dufour et al.
Summary of Cosy: Evaluating Textual Explanations Of Neurons, by Laura Kopf et al.
Summary of From Zero to Hero: Cold-start Anomaly Detection, by Tal Reiss et al.
Summary of Unique3d: High-quality and Efficient 3d Mesh Generation From a Single Image, by Kailu Wu et al.
Summary of Small Language Models For Application Interactions: a Case Study, by Beibin Li et al.
Summary of Linear Function Approximation As a Computationally Efficient Method to Solve Classical Reinforcement Learning Challenges, by Hari Srikanth
Summary of Imitating From Auxiliary Imperfect Demonstrations Via Adversarial Density Weighted Regression, by Ziqi Zhang et al.
Summary of Medication Recommendation Via Dual Molecular Modalities and Multi-step Enhancement, by Shi Mu et al.
Summary of Explainable Data-driven Modeling Of Adsorption Energy in Heterogeneous Catalysis, by Tirtha Vinchurkar et al.
Summary of Quantitative Convergences Of Lie Group Momentum Optimizers, by Lingkai Kong et al.
Summary of Xprompt:explaining Large Language Model’s Generation Via Joint Prompt Attribution, by Yurui Chang et al.
Summary of Enhancing Antibiotic Stewardship Using a Natural Language Approach For Better Feature Representation, by Simon A. Lee et al.
Summary of The Impact Of Ontology on the Prediction Of Cardiovascular Disease Compared to Machine Learning Algorithms, by Hakim El Massari et al.
Summary of Enhancing Performance For Highly Imbalanced Medical Data Via Data Regularization in a Federated Learning Setting, by Georgios Tsoumplekas et al.
Summary of Back to the Basics on Predicting Transfer Performance, by Levy Chaves et al.
Summary of Towards Faster Decentralized Stochastic Optimization with Communication Compression, by Rustem Islamov et al.
Summary of Language Models Need Inductive Biases to Count Inductively, by Yingshan Chang and Yonatan Bisk
Summary of A Geometric Unification Of Distributionally Robust Covariance Estimators: Shrinking the Spectrum by Inflating the Ambiguity Set, By Man-chung Yue et al.
Summary of Gnn-rag: Graph Neural Retrieval For Large Language Model Reasoning, by Costas Mavromatis et al.
Summary of Randomized Exploration For Reinforcement Learning with Multinomial Logistic Function Approximation, by Wooseong Cho et al.
Summary of Tropical Expressivity Of Neural Networks, by Paul Lezeau et al.
Summary of Occam Gradient Descent, by B.n. Kausik
Summary of Unified Explanations in Machine Learning Models: a Perturbation Approach, by Jacob Dineen et al.
Summary of Transformers and Slot Encoding For Sample Efficient Physical World Modelling, by Francesco Petri et al.
Summary of Postdoc: Generating Poster From a Long Multimodal Document Using Deep Submodular Optimization, by Vijay Jaisankar et al.
Summary of Boost Your Own Human Image Generation Model Via Direct Preference Optimization with Ai Feedback, by Sanghyeon Na et al.
Summary of Feature Fusion For Improved Classification: Combining Dempster-shafer Theory and Multiple Cnn Architectures, by Ayyub Alzahem and Wadii Boulila and Maha Driss and Anis Koubaa
Summary of The Empirical Impact Of Neural Parameter Symmetries, or Lack Thereof, by Derek Lim et al.
Summary of Disentangling and Mitigating the Impact Of Task Similarity For Continual Learning, by Naoki Hiratani
Summary of Grokfast: Accelerated Grokking by Amplifying Slow Gradients, By Jaerin Lee et al.
Summary of Retrieval Augmented Structured Generation: Business Document Information Extraction As Tool Use, by Franz Louis Cesista et al.
Summary of Kerascv and Kerasnlp: Vision and Language Power-ups, by Matthew Watson et al.
Summary of Reconstruction Attacks on Machine Unlearning: Simple Models Are Vulnerable, by Martin Bertran et al.
Summary of Ether: Efficient Finetuning Of Large-scale Models with Hyperplane Reflections, by Massimo Bini et al.
Summary of Roast: Review-level Opinion Aspect Sentiment Target Joint Detection For Absa, by Siva Uday Sampreeth Chebolu and Franck Dernoncourt and Nedim Lipka and Thamar Solorio
Summary of Learning Latent Graph Structures and Their Uncertainty, by Alessandro Manenti et al.
Summary of Ban: Detecting Backdoors Activated by Adversarial Neuron Noise, By Xiaoyun Xu et al.
Summary of Exploring Diffusion Models’ Corruption Stage in Few-shot Fine-tuning and Mitigating with Bayesian Neural Networks, by Xiaoyu Wu et al.
Summary of Transition Path Sampling with Improved Off-policy Training Of Diffusion Path Samplers, by Kiyoung Seong et al.
Summary of Domain Adaptation with Cauchy-schwarz Divergence, by Wenzhe Yin et al.
Summary of Improved Out-of-scope Intent Classification with Dual Encoding and Threshold-based Re-classification, by Hossam M. Zawbaa et al.
Summary of Mm-lego: Modular Biomedical Multimodal Models with Minimal Fine-tuning, by Konstantin Hemker et al.
Summary of Symmetries in Overparametrized Neural Networks: a Mean-field View, by Javier Maass and Joaquin Fontbona
Summary of Kernel Language Entropy: Fine-grained Uncertainty Quantification For Llms From Semantic Similarities, by Alexander Nikitin et al.
Summary of Flexidrop: Theoretical Insights and Practical Advances in Random Dropout Method on Gnns, by Zhiheng Zhou et al.
Summary of Submfl: Compatiple Submodel Generation For Federated Learning in Device Heterogenous Environment, by Zeyneddin Oz et al.
Summary of A Random Forest-based Prediction Model For Turning Points in Antagonistic Event-group Competitions, by Zishuo Zhu
Summary of Task-agnostic Machine-learning-assisted Inference, by Jiacheng Miao and Qiongshi Lu
Summary of Cycleformer : Tsp Solver Based on Language Modeling, by Jieun Yook et al.
Summary of Iterative Learning Control Of Fast, Nonlinear, Oscillatory Dynamics (preprint), by John W. Brooks et al.
Summary of Would I Lie to You? Inference Time Alignment Of Language Models Using Direct Preference Heads, by Avelina Asada Hadji-kyriacou and Ognjen Arandjelovic
Summary of Threshold-independent Fair Matching Through Score Calibration, by Mohammad Hossein Moslemi et al.
Summary of Student Answer Forecasting: Transformer-driven Answer Choice Prediction For Language Learning, by Elena Grazia Gado et al.
Summary of Segment, Shuffle, and Stitch: a Simple Layer For Improving Time-series Representations, by Shivam Grover et al.
Summary of Vaad: Visual Attention Analysis Dashboard Applied to E-learning, by Miriam Navarro et al.
Summary of Estimating Before Debiasing: a Bayesian Approach to Detaching Prior Bias in Federated Semi-supervised Learning, by Guogang Zhu et al.
Summary of Preference Alignment with Flow Matching, by Minu Kim et al.
Summary of Metacurl: Non-stationary Concave Utility Reinforcement Learning, by Bianca Marin Moreno (uga et al.
Summary of Approximate Global Convergence Of Independent Learning in Multi-agent Systems, by Ruiyang Jin et al.
Summary of Efficient Stimuli Generation Using Reinforcement Learning in Design Verification, by Deepak Narayan Gadde et al.
Summary of Joint Selective State Space Model and Detrending For Robust Time Series Anomaly Detection, by Junqi Chen et al.
Summary of Out-of-distribution Reject Option Method For Dataset Shift Problem in Early Disease Onset Prediction, by Taisei Tosaki et al.
Summary of The Merit Of River Network Topology For Neural Flood Forecasting, by Nikolas Kirschstein et al.
Summary of On Vessel Location Forecasting and the Effect Of Federated Learning, by Andreas Tritsarolis et al.
Summary of Learning From Random Demonstrations: Offline Reinforcement Learning with Importance-sampled Diffusion Models, by Zeyu Fang et al.
Summary of Is In-context Learning Sufficient For Instruction Following in Llms?, by Hao Zhao et al.
Summary of From Words to Actions: Unveiling the Theoretical Underpinnings Of Llm-driven Autonomous Systems, by Jianliang He et al.
Summary of Fourier Controller Networks For Real-time Decision-making in Embodied Learning, by Hengkai Tan et al.
Summary of Parrot: Efficient Serving Of Llm-based Applications with Semantic Variable, by Chaofan Lin et al.
Summary of Similarity Is Not All You Need: Endowing Retrieval Augmented Generation with Multi Layered Thoughts, by Chunjing Gan et al.
Summary of Urban Air Pollution Forecasting: a Machine Learning Approach Leveraging Satellite Observations and Meteorological Forecasts, by Giacomo Blanco et al.
Summary of Learning Discriminative Dynamics with Label Corruption For Noisy Label Detection, by Suyeon Kim et al.
Summary of Robust Kernel Hypothesis Testing Under Data Corruption, by Antonin Schrab et al.
Summary of Adaptive Advantage-guided Policy Regularization For Offline Reinforcement Learning, by Tenglong Liu et al.
Summary of Unraveling the Impact Of Heterophilic Structures on Graph Positive-unlabeled Learning, by Yuhao Wu et al.
Summary of Few For Many: Tchebycheff Set Scalarization For Many-objective Optimization, by Xi Lin et al.
Summary of Syscaps: Language Interfaces For Simulation Surrogates Of Complex Systems, by Patrick Emami et al.
Summary of Mgcp: a Multi-grained Correlation Based Prediction Network For Multivariate Time Series, by Zhicheng Chen et al.
Summary of Reconciling Model Multiplicity For Downstream Decision Making, by Ally Yalei Du et al.
Summary of Bridging Model-based Optimization and Generative Modeling Via Conservative Fine-tuning Of Diffusion Models, by Masatoshi Uehara et al.
Summary of Bayesian Online Natural Gradient (bong), by Matt Jones et al.
Summary of Efficient Trajectory Inference in Wasserstein Space Using Consecutive Averaging, by Amartya Banerjee et al.
Summary of Diffusion Policies Creating a Trust Region For Offline Reinforcement Learning, by Tianyu Chen et al.
Summary of Towards a Better Evaluation Of Out-of-domain Generalization, by Duhun Hwang et al.
Summary of Enhancing Sufficient Dimension Reduction Via Hellinger Correlation, by Seungbeom Hong et al.
Summary of Specdec++: Boosting Speculative Decoding Via Adaptive Candidate Lengths, by Kaixuan Huang et al.
Summary of Dynamic Feature Selection in Medical Predictive Monitoring by Reinforcement Learning, By Yutong Chen et al.
Summary of Research on the Spatial Data Intelligent Foundation Model, by Shaohua Wang (1) et al.
Summary of Llm As a Complementary Optimizer to Gradient Descent: a Case Study in Prompt Tuning, by Zixian Guo et al.
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