Paper List

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Summary of On Mesa-optimization in Autoregressively Trained Transformers: Emergence and Capability, by Chenyu Zheng et al.
Summary of Em Distillation For One-step Diffusion Models, by Sirui Xie et al.
Summary of Transfer Learning For Diffusion Models, by Yidong Ouyang et al.
Summary of Unsupervised Generative Feature Transformation Via Graph Contrastive Pre-training and Multi-objective Fine-tuning, by Wangyang Ying et al.
Summary of Zamba: a Compact 7b Ssm Hybrid Model, by Paolo Glorioso et al.
Summary of Crafting Interpretable Embeddings by Asking Llms Questions, By Vinamra Benara et al.
Summary of Amortized Active Causal Induction with Deep Reinforcement Learning, by Yashas Annadani et al.
Summary of Exploring Edge Probability Graph Models Beyond Edge Independency: Concepts, Analyses, and Algorithms, by Fanchen Bu et al.
Summary of Disentangling and Integrating Relational and Sensory Information in Transformer Architectures, by Awni Altabaa and John Lafferty
Summary of Pretraining with Random Noise For Fast and Robust Learning Without Weight Transport, by Jeonghwan Cheon et al.
Summary of Latent Energy-based Odyssey: Black-box Optimization Via Expanded Exploration in the Energy-based Latent Space, by Peiyu Yu and Dinghuai Zhang and Hengzhi He and Xiaojian Ma and Ruiyao Miao and Yifan Lu and Yasi Zhang and Deqian Kong and Ruiqi Gao and Jianwen Xie and Guang Cheng and Ying Nian Wu
Summary of Towards Multi-task Multi-modal Models: a Video Generative Perspective, by Lijun Yu
Summary of The Collusion Of Memory and Nonlinearity in Stochastic Approximation with Constant Stepsize, by Dongyan Huo et al.
Summary of Oracle-efficient Reinforcement Learning For Max Value Ensembles, by Marcel Hussing et al.
Summary of Faster Sampling Via Stochastic Gradient Proximal Sampler, by Xunpeng Huang et al.
Summary of Understanding Linear Probing Then Fine-tuning Language Models From Ntk Perspective, by Akiyoshi Tomihari and Issei Sato
Summary of Dmplug: a Plug-in Method For Solving Inverse Problems with Diffusion Models, by Hengkang Wang et al.
Summary of Hypergraph Laplacian Eigenmaps and Face Recognition Problems, by Loc Hoang Tran
Summary of Model Ensembling For Constrained Optimization, by Ira Globus-harris et al.
Summary of Symmetry-informed Governing Equation Discovery, by Jianke Yang et al.
Summary of Chess: Contextual Harnessing For Efficient Sql Synthesis, by Shayan Talaei et al.
Summary of Greedy Growing Enables High-resolution Pixel-based Diffusion Models, by Cristina N. Vasconcelos et al.
Summary of Masked Face Recognition with Generative-to-discriminative Representations, by Shiming Ge et al.
Summary of Study Of Robust Direction Finding Based on Joint Sparse Representation, by Y. Li et al.
Summary of The Devil Is in Discretization Discrepancy. Robustifying Differentiable Nas with Single-stage Searching Protocol, by Konstanty Subbotko et al.
Summary of Dphgnn: a Dual Perspective Hypergraph Neural Networks, by Siddhant Saxena et al.
Summary of Graph Neural Networks with Configuration Cross-attention For Tensor Compilers, by Dmitrii Khizbullin et al.
Summary of Competing For Pixels: a Self-play Algorithm For Weakly-supervised Segmentation, by Shaheer U. Saeed et al.
Summary of A Unified Law Of Robustness For Bregman Divergence Losses, by Santanu Das et al.
Summary of Bayesian Inference with Deep Weakly Nonlinear Networks, by Boris Hanin and Alexander Zlokapa
Summary of Gaussian Approximation and Multiplier Bootstrap For Polyak-ruppert Averaged Linear Stochastic Approximation with Applications to Td Learning, by Sergey Samsonov et al.
Summary of Fast Trac: a Parameter-free Optimizer For Lifelong Reinforcement Learning, by Aneesh Muppidi et al.
Summary of A Provably Effective Method For Pruning Experts in Fine-tuned Sparse Mixture-of-experts, by Mohammed Nowaz Rabbani Chowdhury et al.
Summary of Acceleration Of Grokking in Learning Arithmetic Operations Via Kolmogorov-arnold Representation, by Yeachan Park et al.
Summary of Comments on Friedman’s Method For Class Distribution Estimation, by Dirk Tasche
Summary of Rlsf: Reinforcement Learning Via Symbolic Feedback, by Piyush Jha et al.
Summary of Mixture Of Latent Experts Using Tensor Products, by Zhan Su et al.
Summary of Provably Efficient Off-policy Adversarial Imitation Learning with Convergence Guarantees, by Yilei Chen et al.
Summary of A Systematic Review Of Federated Generative Models, by Ashkan Vedadi Gargary et al.
Summary of Transfer Learning Under High-dimensional Graph Convolutional Regression Model For Node Classification, by Jiachen Chen et al.
Summary of Toward Digitalization: a Secure Approach to Find a Missing Person Using Facial Recognition Technology, by Abid Faisal Ayon et al.
Summary of Gzip Predicts Data-dependent Scaling Laws, by Rohan Pandey
Summary of Cnn Autoencoder Resizer: a Power-efficient Los/nlos Detector in Mimo-enabled Uav Networks, by Azim Akhtarshenas et al.
Summary of Implicit Multimodal Alignment: on the Generalization Of Frozen Llms to Multimodal Inputs, by Mustafa Shukor et al.
Summary of Planning with Multi-constraints Via Collaborative Language Agents, by Cong Zhang et al.
Summary of Anycbms: How to Turn Any Black Box Into a Concept Bottleneck Model, by Gabriele Dominici et al.
Summary of Fourier Sliced-wasserstein Embedding For Multisets and Measures, by Tal Amir et al.
Summary of Se3set: Harnessing Equivariant Hypergraph Neural Networks For Molecular Representation Learning, by Hongfei Wu et al.
Summary of Multi-state Td Target For Model-free Reinforcement Learning, by Wuhao Wang et al.
Summary of Loqt: Low-rank Adapters For Quantized Pretraining, by Sebastian Loeschcke et al.
Summary of Variance-reducing Couplings For Random Features, by Isaac Reid et al.
Summary of Scalable Numerical Embeddings For Multivariate Time Series: Enhancing Healthcare Data Representation Learning, by Chun-kai Huang et al.
Summary of Task Groupings Regularization: Data-free Meta-learning with Heterogeneous Pre-trained Models, by Yongxian Wei et al.
Summary of Contextual Linear Optimization with Bandit Feedback, by Yichun Hu et al.
Summary of Higher-order Transformer Derivative Estimates For Explicit Pathwise Learning Guarantees, by Yannick Limmer et al.
Summary of Reflected Flow Matching, by Tianyu Xie et al.
Summary of A Study on Unsupervised Anomaly Detection and Defect Localization Using Generative Model in Ultrasonic Non-destructive Testing, by Yusaku Ando and Miya Nakajima and Takahiro Saitoh and Tsuyoshi Kato
Summary of On Bits and Bandits: Quantifying the Regret-information Trade-off, by Itai Shufaro et al.
Summary of Cost-effective Online Multi-llm Selection with Versatile Reward Models, by Xiangxiang Dai et al.
Summary of Fair Federated Learning Under Domain Skew with Local Consistency and Domain Diversity, by Yuhang Chen et al.
Summary of Training-conditional Coverage Bounds Under Covariate Shift, by Mehrdad Pournaderi and Yu Xiang
Summary of Regularized Projection Matrix Approximation with Applications to Community Detection, by Zheng Zhai et al.
Summary of A Cmdp-within-online Framework For Meta-safe Reinforcement Learning, by Vanshaj Khattar et al.
Summary of Efficient Probabilistic Modeling Of Crystallization at Mesoscopic Scale, by Pol Timmer et al.
Summary of Node Identifiers: Compact, Discrete Representations For Efficient Graph Learning, by Yuankai Luo et al.
Summary of Provably Mitigating Overoptimization in Rlhf: Your Sft Loss Is Implicitly An Adversarial Regularizer, by Zhihan Liu et al.
Summary of Mambats: Improved Selective State Space Models For Long-term Time Series Forecasting, by Xiuding Cai et al.
Summary of Categorical Flow Matching on Statistical Manifolds, by Chaoran Cheng et al.
Summary of Cacheblend: Fast Large Language Model Serving For Rag with Cached Knowledge Fusion, by Jiayi Yao et al.
Summary of Fast Asymmetric Factorization For Large Scale Multiple Kernel Clustering, by Yan Chen et al.
Summary of Reinforcement Learning For Jump-diffusions, with Financial Applications, by Xuefeng Gao et al.
Summary of A Slices Perspective For Incremental Nonparametric Inference in High Dimensional State Spaces, by Moshe Shienman et al.
Summary of Synthesizing Programmatic Reinforcement Learning Policies with Large Language Model Guided Search, by Max Liu et al.
Summary of On the Algorithmic Bias Of Aligning Large Language Models with Rlhf: Preference Collapse and Matching Regularization, by Jiancong Xiao et al.
Summary of Dominant Shuffle: a Simple Yet Powerful Data Augmentation For Time-series Prediction, by Kai Zhao et al.
Summary of Probabilistic Contrastive Learning with Explicit Concentration on the Hypersphere, by Hongwei Bran Li et al.
Summary of Multi-level Additive Modeling For Structured Non-iid Federated Learning, by Shutong Chen et al.
Summary of Inaccurate Label Distribution Learning with Dependency Noise, by Zhiqiang Kou et al.
Summary of Looks Too Good to Be True: An Information-theoretic Analysis Of Hallucinations in Generative Restoration Models, by Regev Cohen et al.
Summary of Causal-aware Graph Neural Architecture Search Under Distribution Shifts, by Peiwen Li et al.
Summary of Exploring a Multimodal Fusion-based Deep Learning Network For Detecting Facial Palsy, by Heng Yim Nicole Oo et al.
Summary of Grag: Graph Retrieval-augmented Generation, by Yuntong Hu et al.
Summary of Explaining Modern Gated-linear Rnns Via a Unified Implicit Attention Formulation, by Itamar Zimerman et al.
Summary of Causal Concept Graph Models: Beyond Causal Opacity in Deep Learning, by Gabriele Dominici et al.
Summary of Dynamic Inhomogeneous Quantum Resource Scheduling with Reinforcement Learning, by Linsen Li et al.
Summary of Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups, by Yuchen Zhu et al.
Summary of Variational Offline Multi-agent Skill Discovery, by Jiayu Chen et al.
Summary of Reverse Transition Kernel: a Flexible Framework to Accelerate Diffusion Inference, by Xunpeng Huang et al.
Summary of Rewarded Region Replay (r3) For Policy Learning with Discrete Action Space, by Bangzheng Li et al.
Summary of Multi-reference Preference Optimization For Large Language Models, by Hung Le et al.
Summary of Safe and Balanced: a Framework For Constrained Multi-objective Reinforcement Learning, by Shangding Gu et al.
Summary of When Does Compositional Structure Yield Compositional Generalization? a Kernel Theory, by Samuel Lippl et al.
Summary of Daily Physical Activity Monitoring — Adaptive Learning From Multi-source Motion Sensor Data, by Haoting Zhang et al.
Summary of Machine Learning in Business Process Management: a Systematic Literature Review, by Sven Weinzierl et al.
Summary of Adafisher: Adaptive Second Order Optimization Via Fisher Information, by Damien Martins Gomes and Yanlei Zhang and Eugene Belilovsky and Guy Wolf and Mahdi S. Hosseini
Summary of Intruding with Words: Towards Understanding Graph Injection Attacks at the Text Level, by Runlin Lei et al.
Summary of Understanding the Effect Of Using Semantically Meaningful Tokens For Visual Representation Learning, by Neha Kalibhat et al.
Summary of Spinquant: Llm Quantization with Learned Rotations, by Zechun Liu et al.
Summary of Network Interdiction Goes Neural, by Lei Zhang et al.
Summary of Tensor Attention Training: Provably Efficient Learning Of Higher-order Transformers, by Yingyu Liang et al.