Saved in:
| Main Authors: | Zhang, Songming, Luo, Yuxiao, Wang, Qizhou, Chi, Haoang, Chen, Xiaofeng, Han, Bo, Li, Jinyan |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2312.16243 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
ShiftKD: Benchmarking Knowledge Distillation under Distribution Shift
by: Zhang, Songming, et al.
Published: (2023)
by: Zhang, Songming, et al.
Published: (2023)
Causal Representation Learning with Optimal Compression under Complex Treatments
by: Liang, Wanting, et al.
Published: (2026)
by: Liang, Wanting, et al.
Published: (2026)
M-STAR: Multi-Scale Spatiotemporal Autoregression for Human Mobility Modeling
by: Luo, Yuxiao, et al.
Published: (2025)
by: Luo, Yuxiao, et al.
Published: (2025)
AEGIS: Adversarial Target-Guided Retention-Data-Free Robust Concept Erasure from Diffusion Models
by: Li, Fengpeng, et al.
Published: (2026)
by: Li, Fengpeng, et al.
Published: (2026)
Adaptive-Boundary-Clipping GRPO: Ensuring Bounded Ratios for Stable and Generalizable Training
by: Liu, Chi, et al.
Published: (2026)
by: Liu, Chi, et al.
Published: (2026)
Towards Understanding Valuable Preference Data for Large Language Model Alignment
by: Zhang, Zizhuo, et al.
Published: (2025)
by: Zhang, Zizhuo, et al.
Published: (2025)
On the Learnability of Out-of-distribution Detection
by: Fang, Zhen, et al.
Published: (2024)
by: Fang, Zhen, et al.
Published: (2024)
Membership Inference Attacks Cannot Prove that a Model Was Trained On Your Data
by: Zhang, Jie, et al.
Published: (2024)
by: Zhang, Jie, et al.
Published: (2024)
What Is Preference Optimization Doing, and Why?
by: Wang, Yue, et al.
Published: (2025)
by: Wang, Yue, et al.
Published: (2025)
Concept Matching with Agent for Out-of-Distribution Detection
by: Lee, Yuxiao, et al.
Published: (2024)
by: Lee, Yuxiao, et al.
Published: (2024)
BOOD: Boundary-based Out-Of-Distribution Data Generation
by: Liao, Qilin, et al.
Published: (2025)
by: Liao, Qilin, et al.
Published: (2025)
Reasoned Safety Alignment: Ensuring Jailbreak Defense via Answer-Then-Check
by: Cao, Chentao, et al.
Published: (2025)
by: Cao, Chentao, et al.
Published: (2025)
Understanding the Impact of Differentially Private Training on Memorization of Long-Tailed Data
by: Zhang, Jiaming, et al.
Published: (2026)
by: Zhang, Jiaming, et al.
Published: (2026)
A Sober Look at the Robustness of CLIPs to Spurious Features
by: Wang, Qizhou, et al.
Published: (2024)
by: Wang, Qizhou, et al.
Published: (2024)
Mixture of Link Predictors on Graphs
by: Ma, Li, et al.
Published: (2024)
by: Ma, Li, et al.
Published: (2024)
Dual Test-time Training for Out-of-distribution Recommender System
by: Yang, Xihong, et al.
Published: (2024)
by: Yang, Xihong, et al.
Published: (2024)
Unveiling Causal Reasoning in Large Language Models: Reality or Mirage?
by: Chi, Haoang, et al.
Published: (2025)
by: Chi, Haoang, et al.
Published: (2025)
Distinguishable Deletion: Unifying Knowledge Erasure and Refusal for Large Language Model Unlearning
by: Yang, Puning, et al.
Published: (2026)
by: Yang, Puning, et al.
Published: (2026)
SMILE: Zero-Shot Sparse Mixture of Low-Rank Experts Construction From Pre-Trained Foundation Models
by: Tang, Anke, et al.
Published: (2024)
by: Tang, Anke, et al.
Published: (2024)
Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning
by: Yang, Puning, et al.
Published: (2025)
by: Yang, Puning, et al.
Published: (2025)
Improving Graph Out-of-distribution Generalization Beyond Causality
by: Xu, Can, et al.
Published: (2024)
by: Xu, Can, et al.
Published: (2024)
Towards Effective Evaluations and Comparisons for LLM Unlearning Methods
by: Wang, Qizhou, et al.
Published: (2024)
by: Wang, Qizhou, et al.
Published: (2024)
Is Gradient Ascent Really Necessary? Memorize to Forget for Machine Unlearning
by: Huang, Zhuo, et al.
Published: (2026)
by: Huang, Zhuo, et al.
Published: (2026)
FOOGD: Federated Collaboration for Both Out-of-distribution Generalization and Detection
by: Liao, Xinting, et al.
Published: (2024)
by: Liao, Xinting, et al.
Published: (2024)
ManiBox: Enhancing Embodied Spatial Generalization via Scalable Simulation Data Generations
by: Tan, Hengkai, et al.
Published: (2024)
by: Tan, Hengkai, et al.
Published: (2024)
Neuron Activation Coverage: Rethinking Out-of-distribution Detection and Generalization
by: Liu, Yibing, et al.
Published: (2023)
by: Liu, Yibing, et al.
Published: (2023)
LLM Unlearning with LLM Beliefs
by: Li, Kemou, et al.
Published: (2025)
by: Li, Kemou, et al.
Published: (2025)
Spurious Feature Diversification Improves Out-of-distribution Generalization
by: Lin, Yong, et al.
Published: (2023)
by: Lin, Yong, et al.
Published: (2023)
An Out-Of-Distribution Membership Inference Attack Approach for Cross-Domain Graph Attacks
by: Wang, Jinyan, et al.
Published: (2025)
by: Wang, Jinyan, et al.
Published: (2025)
Feature Protection For Out-of-distribution Generalization
by: Tan, Lu, et al.
Published: (2024)
by: Tan, Lu, et al.
Published: (2024)
Towards High Supervised Learning Utility Training Data Generation: Data Pruning and Column Reordering
by: Kwok, Tung Sum Thomas, et al.
Published: (2025)
by: Kwok, Tung Sum Thomas, et al.
Published: (2025)
$ϕ$-Balancing for Mixture-of-Experts Training
by: Chen, Lizhang, et al.
Published: (2026)
by: Chen, Lizhang, et al.
Published: (2026)
Learning from Streaming Data when Users Choose
by: Su, Jinyan, et al.
Published: (2024)
by: Su, Jinyan, et al.
Published: (2024)
Optimizing Pre-Training Data Mixtures with Mixtures of Data Expert Models
by: Belenki, Lior, et al.
Published: (2025)
by: Belenki, Lior, et al.
Published: (2025)
Principled Out-of-Distribution Generalization via Simplicity
by: Ge, Jiawei, et al.
Published: (2025)
by: Ge, Jiawei, et al.
Published: (2025)
FSMoE: A Flexible and Scalable Training System for Sparse Mixture-of-Experts Models
by: Pan, Xinglin, et al.
Published: (2025)
by: Pan, Xinglin, et al.
Published: (2025)
Forgetting: A New Mechanism Towards Better Large Language Model Fine-tuning
by: Taheri, Ali, et al.
Published: (2025)
by: Taheri, Ali, et al.
Published: (2025)
Rethinking LLM Unlearning Objectives: A Gradient Perspective and Go Beyond
by: Wang, Qizhou, et al.
Published: (2025)
by: Wang, Qizhou, et al.
Published: (2025)
The Illusion of Specialization: Unveiling the Domain-Invariant "Standing Committee" in Mixture-of-Experts Models
by: Wang, Yan, et al.
Published: (2026)
by: Wang, Yan, et al.
Published: (2026)
MixNet: A Runtime Reconfigurable Optical-Electrical Fabric for Distributed Mixture-of-Experts Training
by: Liao, Xudong, et al.
Published: (2025)
by: Liao, Xudong, et al.
Published: (2025)
Similar Items
-
ShiftKD: Benchmarking Knowledge Distillation under Distribution Shift
by: Zhang, Songming, et al.
Published: (2023) -
Causal Representation Learning with Optimal Compression under Complex Treatments
by: Liang, Wanting, et al.
Published: (2026) -
M-STAR: Multi-Scale Spatiotemporal Autoregression for Human Mobility Modeling
by: Luo, Yuxiao, et al.
Published: (2025) -
AEGIS: Adversarial Target-Guided Retention-Data-Free Robust Concept Erasure from Diffusion Models
by: Li, Fengpeng, et al.
Published: (2026) -
Adaptive-Boundary-Clipping GRPO: Ensuring Bounded Ratios for Stable and Generalizable Training
by: Liu, Chi, et al.
Published: (2026)