:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhan, Qishi, Hu, Minxuan, He, Liang, Wang, Guansu, Liu, Jiaxin
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2604.23114
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Unstable Rankings in Bayesian Deep Learning Evaluation
by: Zhan, Qishi, et al.
Published: (2026)

Disentangling Language Roles in Multilingual LLM Task Execution
by: Zhan, Qishi, et al.
Published: (2026)

Adaptive Signal Resuscitation: Channel-wise Post-Pruning Repair for Sparse Vision Networks
by: Zhan, Qishi, et al.
Published: (2026)

Research on Optimization of Natural Language Processing Model Based on Multimodal Deep Learning
by: Sun, Dan, et al.
Published: (2024)

BudgetDraft: Acceptance-Aware Multi-View Training for Sparse-KV Speculative Decoding
by: He, Liang, et al.
Published: (2026)

Two Tales of Single-Phase Contrastive Hebbian Learning
by: Høier, Rasmus Kjær, et al.
Published: (2024)

Beyond Explained Variance: A Cautionary Tale of PCA
by: Marchetti, Gionni
Published: (2026)

Deep Reinforcement Learning and The Tale of Two Temporal Difference Errors
by: Rojas, Juan Sebastian, et al.
Published: (2026)

Understanding the Generalization of Bilevel Programming in Hyperparameter Optimization: A Tale of Bias-Variance Decomposition
by: Zhou, Yubo, et al.
Published: (2026)

When Does Pairing Seeds Reduce Variance? Evidence from a Multi-Agent Economic Simulation
by: Sharma, Udit
Published: (2025)

Deep Temporal Graph Clustering: A Comprehensive Benchmark and Datasets
by: Liu, Meng, et al.
Published: (2026)

Real-World Benchmarks Make Membership Inference Attacks Fail on Diffusion Models
by: Liang, Chumeng, et al.
Published: (2024)

When Adaptation Fails: A Gradient-Based Diagnosis of Collapsed Gating in Vision-Language Prompt Learning
by: Fang, Yunxuan, et al.
Published: (2026)

On the Extreme Variance of Certified Local Robustness Across Model Seeds
by: Le, Minh, et al.
Published: (2026)

Incremental Sequence Labeling: A Tale of Two Shifts
by: Qiu, Shengjie, et al.
Published: (2024)

A Tale of Two Cities: Pessimism and Opportunism in Offline Dynamic Pricing
by: Bian, Zeyu, et al.
Published: (2024)

A Tale of Two Geometries: Adaptive Optimizers and Non-Euclidean Descent
by: Xie, Shuo, et al.
Published: (2025)

On the Reduction of Variance and Overestimation of Deep Q-Learning
by: Sabry, Mohammed, et al.
Published: (2019)

MARS-M: When Variance Reduction Meets Matrices
by: Liu, Yifeng, et al.
Published: (2025)

A Tale of Two Learning Algorithms: Multiple Stream Random Walk and Asynchronous Gossip
by: Gholami, Peyman, et al.
Published: (2025)

A Tale of Two Problems: Multi-Task Bilevel Learning Meets Equality Constrained Multi-Objective Optimization
by: Zhang, Zhiyao, et al.
Published: (2026)

A Confidence-Variance Theory for Pseudo-Label Selection in Semi-Supervised Learning
by: Liu, Jinshi, et al.
Published: (2026)

When LLM Reward Design Fails: Diagnostic-Driven Refinement for Sparse Structured RL
by: Wang, Youting, et al.
Published: (2026)

When Explanations Lie: Why Many Modified BP Attributions Fail
by: Sixt, Leon, et al.
Published: (2019)

Actor-Critic or Critic-Actor? A Tale of Two Time Scales
by: Bhatnagar, Shalabh, et al.
Published: (2022)

Quantifying Variance in Evaluation Benchmarks
by: Madaan, Lovish, et al.
Published: (2024)

When Active Learning Fails, Uncalibrated Out of Distribution Uncertainty Quantification Might Be the Problem
by: Dale, Ashley S., et al.
Published: (2025)

Learning Through Noise: Why Subliminal Learning Works and When It Fails
by: Brockers, Vincent C., et al.
Published: (2026)

When Counterfactual Reasoning Fails: Chaos and Real-World Complexity
by: Aalaila, Yahya, et al.
Published: (2025)

When Vision Fails: Text Attacks Against ViT and OCR
by: Boucher, Nicholas, et al.
Published: (2023)

AdaFlow: Imitation Learning with Variance-Adaptive Flow-Based Policies
by: Hu, Xixi, et al.
Published: (2024)

Reinforcement Learning for Option Hedging: Static Implied-Volatility Fit versus Shortfall-Aware Performance
by: Chen, Ziheng, et al.
Published: (2026)

Lecture Notes on Linear Neural Networks: A Tale of Optimization and Generalization in Deep Learning
by: Cohen, Nadav, et al.
Published: (2024)

A Tale of Two Temperatures: Simple, Efficient, and Diverse Sampling from Diffusion Language Models
by: Olausson, Theo X., et al.
Published: (2026)

Deep Kernel Posterior Learning under Infinite Variance Prior Weights
by: Loría, Jorge, et al.
Published: (2024)

Single-Position Intervention Fails: Distributed Output Templates Drive In-Context Learning
by: Cheng, Bryan, et al.
Published: (2026)

Reducing Variance Caused by Communication in Decentralized Multi-agent Deep Reinforcement Learning
by: Zhu, Changxi, et al.
Published: (2025)

When Will It Fail?: Anomaly to Prompt for Forecasting Future Anomalies in Time Series
by: Park, Min-Yeong, et al.
Published: (2025)

Improving Diversity in Language Models: When Temperature Fails, Change the Loss
by: Verine, Alexandre, et al.
Published: (2025)

A Tale of Two Symmetries: Exploring the Loss Landscape of Equivariant Models
by: Xie, YuQing, et al.
Published: (2025)