Paper List

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Summary of Adversarial Score Identity Distillation: Rapidly Surpassing the Teacher in One Step, by Mingyuan Zhou and Huangjie Zheng and Yi Gu and Zhendong Wang and Hai Huang
Summary of Hippo-kan: Efficient Kan Model For Time Series Analysis, by Sangjong Lee et al.
Summary of Baichuan Alignment Technical Report, by Mingan Lin et al.
Summary of Knowledge Graph Embeddings: a Comprehensive Survey on Capturing Relation Properties, by Guanglin Niu
Summary of Advancements in Heart Disease Prediction: a Machine Learning Approach For Early Detection and Risk Assessment, by Balaji Shesharao Ingole et al.
Summary of Harnessing Your Dram and Ssd For Sustainable and Accessible Llm Inference with Mixed-precision and Multi-level Caching, by Jie Peng et al.
Summary of Cakd: a Correlation-aware Knowledge Distillation Framework Based on Decoupling Kullback-leibler Divergence, by Zao Zhang et al.
Summary of Arrivalnet: Predicting City-wide Bus/tram Arrival Time with Two-dimensional Temporal Variation Modeling, by Zirui Li and Patrick Wolf and Meng Wang
Summary of Efficient Deep Learning Board: Training Feedback Is Not All You Need, by Lina Gong et al.
Summary of Cfts-gan: Continual Few-shot Teacher Student For Generative Adversarial Networks, by Munsif Ali et al.
Summary of Collaboratively Adding New Knowledge to An Llm, by Rhui Dih Lee and Laura Wynter
Summary of On the Sparsity Of the Strong Lottery Ticket Hypothesis, by Emanuele Natale (coati) et al.
Summary of Controllable Discovery Of Intents: Incremental Deep Clustering Using Semi-supervised Contrastive Learning, by Mrinal Rawat et al.
Summary of Mitigating Embedding Collapse in Diffusion Models For Categorical Data, by Bac Nguyen and and Chieh-hsin Lai and Yuhta Takida and Naoki Murata and Toshimitsu Uesaka and Stefano Ermon and Yuki Mitsufuji
Summary of Universal Approximation Results For Neural Networks with Non-polynomial Activation Function Over Non-compact Domains, by Ariel Neufeld et al.
Summary of Constrained Recurrent Bayesian Forecasting For Crack Propagation, by Sara Yasmine Ouerk et al.
Summary of Multifidelity Kolmogorov-arnold Networks, by Amanda A. Howard et al.
Summary of High-dimensional Tensor Discriminant Analysis with Incomplete Tensors, by Elynn Chen et al.
Summary of What’s New in My Data? Novelty Exploration Via Contrastive Generation, by Masaru Isonuma and Ivan Titov
Summary of Privacy For Free in the Over-parameterized Regime, by Simone Bombari and Marco Mondelli
Summary of Implicit Regularization Of Sharpness-aware Minimization For Scale-invariant Problems, by Bingcong Li et al.
Summary of Distrl: An Asynchronous Distributed Reinforcement Learning Framework For On-device Control Agents, by Taiyi Wang et al.
Summary of Effects Of Soft-domain Transfer and Named Entity Information on Deception Detection, by Steven Triplett et al.
Summary of Online Reinforcement Learning with Passive Memory, by Anay Pattanaik and Lav R. Varshney
Summary of Stochastic Gradient Descent Jittering For Inverse Problems: Alleviating the Accuracy-robustness Tradeoff, by Peimeng Guan et al.
Summary of Discograms: Enhancing Movie Screen-play Summarization Using Movie Character-aware Discourse Graph, by Maitreya Prafulla Chitale et al.
Summary of Decomposing the Dark Matter Of Sparse Autoencoders, by Joshua Engels et al.
Summary of Rethinking Vlms and Llms For Image Classification, by Avi Cooper et al.
Summary of Optimizing Parking Space Classification: Distilling Ensembles Into Lightweight Classifiers, by Paulo Luza Alves et al.
Summary of Deep Learning Enhanced Road Traffic Analysis: Scalable Vehicle Detection and Velocity Estimation Using Planetscope Imagery, by Maciej Adamiak et al.
Summary of G2d2: Gradient-guided Discrete Diffusion For Image Inverse Problem Solving, by Naoki Murata et al.
Summary of Quailora: Quantization-aware Initialization For Lora, by Neal Lawton et al.
Summary of Sglp: a Similarity Guided Fast Layer Partition Pruning For Compressing Large Deep Models, by Yuqi Li et al.
Summary of A Systematic Survey on Large Language Models For Algorithm Design, by Fei Liu et al.
Summary of The Representation Of Meaningful Precision, and Accuracy, by a Mani
Summary of A Phenomenological Ai Foundation Model For Physical Signals, by Jaime Lien et al.
Summary of Incorporating Long-term Data in Training Short-term Traffic Prediction Model, by Xiannan Huang et al.
Summary of Rethinking Token Reduction For State Space Models, by Zheng Zhan et al.
Summary of Is Less More? Exploring Token Condensation As Training-free Test-time Adaptation, by Zixin Wang et al.
Summary of Leveraging Intra-period and Inter-period Features For Enhanced Passenger Flow Prediction Of Subway Stations, by Xiannan Huang et al.
Summary of On the Relation Between Linear Diffusion and Power Iteration, by Dana Weitzner et al.
Summary of Matryoshkakv: Adaptive Kv Compression Via Trainable Orthogonal Projection, by Bokai Lin et al.
Summary of Sifm: a Foundation Model For Multi-granularity Arctic Sea Ice Forecasting, by Jingyi Xu et al.
Summary of Building Trust in Black-box Optimization: a Comprehensive Framework For Explainability, by Nazanin Nezami et al.
Summary of Large Language Models Are Overparameterized Text Encoders, by Thennal D K et al.
Summary of Optimizing Attention with Mirror Descent: Generalized Max-margin Token Selection, by Addison Kristanto Julistiono et al.
Summary of Neural Combinatorial Clustered Bandits For Recommendation Systems, by Baran Atalar et al.
Summary of Towards Unsupervised Validation Of Anomaly-detection Models, by Lihi Idan
Summary of Neuro-symbolic Traders: Assessing the Wisdom Of Ai Crowds in Markets, by Namid R. Stillman and Rory Baggott
Summary of How Does Data Diversity Shape the Weight Landscape Of Neural Networks?, by Yang Ba et al.
Summary of Learning with Multi-group Guarantees For Clusterable Subpopulations, by Jessica Dai et al.
Summary of Learning to Control the Smoothness Of Graph Convolutional Network Features, by Shih-hsin Wang et al.
Summary of Streaming Deep Reinforcement Learning Finally Works, by Mohamed Elsayed et al.
Summary of Asymptotically Optimal Change Detection For Unnormalized Pre- and Post-change Distributions, by Arman Adibi et al.
Summary of Simformer: Single-layer Vanilla Transformer Can Learn Free-space Trajectory Similarity, by Chuang Yang et al.
Summary of On the Regularization Of Learnable Embeddings For Time Series Forecasting, by Luca Butera et al.
Summary of Convergence Of Manifold Filter-combine Networks, by David R. Johnson et al.
Summary of Parallel Backpropagation For Inverse Of a Convolution with Application to Normalizing Flows, by Sandeep Nagar et al.
Summary of Hr-bandit: Human-ai Collaborated Linear Recourse Bandit, by Junyu Cao et al.
Summary of Evopress: Towards Optimal Dynamic Model Compression Via Evolutionary Search, by Oliver Sieberling et al.
Summary of Harnessing Causality in Reinforcement Learning with Bagged Decision Times, by Daiqi Gao et al.
Summary of Bridging the Training-inference Gap in Llms by Leveraging Self-generated Tokens, By Zhepeng Cen and Yao Liu and Siliang Zeng and Pratik Chaudhari and Huzefa Rangwala and George Karypis and Rasool Fakoor
Summary of A Large Language Model-driven Reward Design Framework Via Dynamic Feedback For Reinforcement Learning, by Shengjie Sun et al.
Summary of Surgeryv2: Bridging the Gap Between Model Merging and Multi-task Learning with Deep Representation Surgery, by Enneng Yang et al.
Summary of Predicting Time-varying Flux and Balance in Metabolic Systems Using Structured Neural-ode Processes, by Santanu Rathod et al.
Summary of Fashionr2r: Texture-preserving Rendered-to-real Image Translation with Diffusion Models, by Rui Hu et al.
Summary of The Propensity For Density in Feed-forward Models, by Nandi Schoots et al.
Summary of Electrocardiogram-language Model For Few-shot Question Answering with Meta Learning, by Jialu Tang et al.
Summary of Enhancing Cryptocurrency Market Forecasting: Advanced Machine Learning Techniques and Industrial Engineering Contributions, by Jannatun Nayeem Pinky and Ramya Akula
Summary of How Do Training Methods Influence the Utilization Of Vision Models?, by Paul Gavrikov et al.
Summary of Laplace Transform Based Low-complexity Learning Of Continuous Markov Semigroups, by Vladimir R. Kostic et al.
Summary of Spectral Representations For Accurate Causal Uncertainty Quantification with Gaussian Processes, by Hugh Dance et al.
Summary of Transfer Reinforcement Learning in Heterogeneous Action Spaces Using Subgoal Mapping, by Kavinayan P. Sivakumar et al.
Summary of Ant: Adaptive Noise Schedule For Time Series Diffusion Models, by Seunghan Lee et al.
Summary of Cats and Dags: Integrating Directed Acyclic Graphs with Transformers and Fully-connected Neural Networks For Causally Constrained Predictions, by Matthew J. Vowels and Mathieu Rochat and Sina Akbari
Summary of Efficient Annotator Reliability Assessment and Sample Weighting For Knowledge-based Misinformation Detection on Social Media, by Owen Cook et al.
Summary of Using Sentiment and Technical Analysis to Predict Bitcoin with Machine Learning, by Arthur Emanuel De Oliveira Carosia
Summary of Rethinking Distance Metrics For Counterfactual Explainability, by Joshua Nathaniel Williams et al.
Summary of Diffusion-based Semi-supervised Spectral Algorithm For Regression on Manifolds, by Weichun Xia et al.
Summary of Boosting K-means For Big Data by Fusing Data Streaming with Global Optimization, By Ravil Mussabayev et al.
Summary of Understanding the Difficulty Of Low-precision Post-training Quantization Of Large Language Models, by Zifei Xu et al.
Summary of Measuring Diversity: Axioms and Challenges, by Mikhail Mironov and Liudmila Prokhorenkova
Summary of Momentumsmoe: Integrating Momentum Into Sparse Mixture Of Experts, by Rachel S.y. Teo et al.
Summary of Almost-linear Rnns Yield Highly Interpretable Symbolic Codes in Dynamical Systems Reconstruction, by Manuel Brenner et al.
Summary of G-neurodavis: a Neural Network Model For Generalized Embedding, Data Visualization and Sample Generation, by Chayan Maitra and Rajat K. De
Summary of Formal Explanations For Neuro-symbolic Ai, by Sushmita Paul et al.
Summary of Unified Convergence Analysis For Score-based Diffusion Models with Deterministic Samplers, by Runjia Li and Qiwei Di and Quanquan Gu
Summary of Pseudo-label Refinement For Improving Self-supervised Learning Systems, by Zia-ur-rehman et al.
Summary of Razor: Refining Accuracy by Zeroing Out Redundancies, By Daniel Riccio et al.
Summary of Modification: Mixture Of Depths Made Easy, by Chen Zhang et al.
Summary of On Time Series Clustering with K-means, by Christopher Holder et al.
Summary of Revisiting Slo and Goodput Metrics in Llm Serving, by Zhibin Wang et al.
Summary of Finder: Stochastic Mirroring Of Noisy Quasi-newton Search and Deep Network Training, by Uttam Suman et al.
Summary of Plmtrajrec: a Scalable and Generalizable Trajectory Recovery Method with Pre-trained Language Models, by Tonglong Wei et al.
Summary of Optimizing Importance Weighting in the Presence Of Sub-population Shifts, by Floris Holstege et al.
Summary of Debiasing Mini-batch Quadratics For Applications in Deep Learning, by Lukas Tatzel et al.
Summary of Evaluating the Evaluators: Towards Human-aligned Metrics For Missing Markers Reconstruction, by Taras Kucherenko et al.
Summary of Fine-tuning Pre-trained Language Models For Robust Causal Representation Learning, by Jialin Yu et al.
Summary of A Scientific Machine Learning Approach For Predicting and Forecasting Battery Degradation in Electric Vehicles, by Sharv Murgai et al.
Summary of Dual-label Learning with Irregularly Present Labels, by Mingqian Li et al.