Support is All You Need for Certified VAE Training
Fuente:
arXiv
Saved in:
| Main Authors: | Xu, Changming, Banerjee, Debangshu, Vasisht, Deepak, Singh, Gagandeep |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Compression Aware Certified Training
by: Xu, Changming, et al.
Published: (2025)
by: Xu, Changming, et al.
Published: (2025)
Cross-Input Certified Training for Universal Perturbations
by: Xu, Changming, et al.
Published: (2024)
by: Xu, Changming, et al.
Published: (2024)
Relational DNN Verification With Cross Executional Bound Refinement
by: Banerjee, Debangshu, et al.
Published: (2024)
by: Banerjee, Debangshu, et al.
Published: (2024)
Data Shifts Hurt CoT: A Theoretical Study
by: Yin, Lang, et al.
Published: (2025)
by: Yin, Lang, et al.
Published: (2025)
SEVerA: Verified Synthesis of Self-Evolving Agents
by: Banerjee, Debangshu, et al.
Published: (2026)
by: Banerjee, Debangshu, et al.
Published: (2026)
CRANE: Reasoning with constrained LLM generation
by: Banerjee, Debangshu, et al.
Published: (2025)
by: Banerjee, Debangshu, et al.
Published: (2025)
Towards Generalized Certified Robustness with Multi-Norm Training
by: Jiang, Enyi, et al.
Published: (2024)
by: Jiang, Enyi, et al.
Published: (2024)
Bypassing the Safety Training of Open-Source LLMs with Priming Attacks
by: Vega, Jason, et al.
Published: (2023)
by: Vega, Jason, et al.
Published: (2023)
DINGO: Constrained Inference for Diffusion LLMs
by: Suresh, Tarun, et al.
Published: (2025)
by: Suresh, Tarun, et al.
Published: (2025)
Incremental Randomized Smoothing Certification
by: Ugare, Shubham, et al.
Published: (2023)
by: Ugare, Shubham, et al.
Published: (2023)
Certifying Knowledge Comprehension in LLMs
by: Chaudhary, Isha, et al.
Published: (2024)
by: Chaudhary, Isha, et al.
Published: (2024)
Towards Reliable Alignment: Uncertainty-aware RLHF
by: Banerjee, Debangshu, et al.
Published: (2024)
by: Banerjee, Debangshu, et al.
Published: (2024)
Bad Values but Good Behavior: Learning Highly Misspecified Bandits and MDPs
by: Banerjee, Debangshu, et al.
Published: (2023)
by: Banerjee, Debangshu, et al.
Published: (2023)
Formal Synthesis of Certifiably Robust Neural Lyapunov-Barrier Certificates
by: Wang, Chengxiao, et al.
Published: (2026)
by: Wang, Chengxiao, et al.
Published: (2026)
Probabilistic Trust Intervals for Out of Distribution Detection
by: Singh, Gagandeep, et al.
Published: (2021)
by: Singh, Gagandeep, et al.
Published: (2021)
Top-$nσ$: Not All Logits Are You Need
by: Tang, Chenxia, et al.
Published: (2024)
by: Tang, Chenxia, et al.
Published: (2024)
Accuracy is Not All You Need
by: Dutta, Abhinav, et al.
Published: (2024)
by: Dutta, Abhinav, et al.
Published: (2024)
Certifying Counterfactual Bias in LLMs
by: Chaudhary, Isha, et al.
Published: (2024)
by: Chaudhary, Isha, et al.
Published: (2024)
Attention is All You Need Until You Need Retention
by: Yaslioglu, M. Murat
Published: (2025)
by: Yaslioglu, M. Murat
Published: (2025)
Context is All You Need
by: Delanois, Jean Erik, et al.
Published: (2026)
by: Delanois, Jean Erik, et al.
Published: (2026)
Why DPO is a Misspecified Estimator and How to Fix It
by: Gopalan, Aditya, et al.
Published: (2025)
by: Gopalan, Aditya, et al.
Published: (2025)
Attention Is All You Need But You Don't Need All Of It For Inference of Large Language Models
by: Tyukin, Georgy, et al.
Published: (2024)
by: Tyukin, Georgy, et al.
Published: (2024)
Efficient Deep Learning Board: Training Feedback Is Not All You Need
by: Gong, Lina, et al.
Published: (2024)
by: Gong, Lina, et al.
Published: (2024)
Towards Reliable, Uncertainty-Aware Alignment
by: Banerjee, Debangshu, et al.
Published: (2025)
by: Banerjee, Debangshu, et al.
Published: (2025)
Evolving Abstract Transformers for Gradient-Guided, Adaptable Abstract Interpretation
by: Gomber, Shaurya, et al.
Published: (2025)
by: Gomber, Shaurya, et al.
Published: (2025)
Some Attention is All You Need for Retrieval
by: Michalak, Felix, et al.
Published: (2025)
by: Michalak, Felix, et al.
Published: (2025)
Half Search Space is All You Need
by: Rumiantsev, Pavel, et al.
Published: (2025)
by: Rumiantsev, Pavel, et al.
Published: (2025)
Exploitation Is All You Need... for Exploration
by: Rentschler, Micah, et al.
Published: (2025)
by: Rentschler, Micah, et al.
Published: (2025)
Multistep Inverse Is Not All You Need
by: Levine, Alexander, et al.
Published: (2024)
by: Levine, Alexander, et al.
Published: (2024)
Revisiting End-To-End Sparse Autoencoder Training: A Short Finetune Is All You Need
by: Karvonen, Adam
Published: (2025)
by: Karvonen, Adam
Published: (2025)
No More Adam: Learning Rate Scaling at Initialization is All You Need
by: Xu, Minghao, et al.
Published: (2024)
by: Xu, Minghao, et al.
Published: (2024)
Fusion or Confusion? Multimodal Complexity Is Not All You Need
by: Rheude, Tillmann, et al.
Published: (2025)
by: Rheude, Tillmann, et al.
Published: (2025)
MoE Lens -- An Expert Is All You Need
by: Chaudhari, Marmik, et al.
Published: (2026)
by: Chaudhari, Marmik, et al.
Published: (2026)
Realizable Learning is All You Need
by: Hopkins, Max, et al.
Published: (2021)
by: Hopkins, Max, et al.
Published: (2021)
Cooperation Is All You Need
by: Adeel, Ahsan, et al.
Published: (2023)
by: Adeel, Ahsan, et al.
Published: (2023)
How Catastrophic is Your LLM? Certifying Risk in Conversation
by: Wang, Chengxiao, et al.
Published: (2025)
by: Wang, Chengxiao, et al.
Published: (2025)
Standard Gaussian Process is All You Need for High-Dimensional Bayesian Optimization
by: Xu, Zhitong, et al.
Published: (2024)
by: Xu, Zhitong, et al.
Published: (2024)
Block Rotation is All You Need for MXFP4 Quantization
by: Shao, Yuantian, et al.
Published: (2025)
by: Shao, Yuantian, et al.
Published: (2025)
All You Need Is Synthetic Task Augmentation
by: Godin, Guillaume
Published: (2025)
by: Godin, Guillaume
Published: (2025)
Element-wise Attention Is All You Need
by: Feng, Guoxin
Published: (2025)
by: Feng, Guoxin
Published: (2025)
Similar Items
-
Compression Aware Certified Training
by: Xu, Changming, et al.
Published: (2025) -
Cross-Input Certified Training for Universal Perturbations
by: Xu, Changming, et al.
Published: (2024) -
Relational DNN Verification With Cross Executional Bound Refinement
by: Banerjee, Debangshu, et al.
Published: (2024) -
Data Shifts Hurt CoT: A Theoretical Study
by: Yin, Lang, et al.
Published: (2025) -
SEVerA: Verified Synthesis of Self-Evolving Agents
by: Banerjee, Debangshu, et al.
Published: (2026)