Saved in:
| Main Authors: | Zhang, Jiawei, Estornell, Andrew, Baek, David D., Li, Bo, Xu, Xiaojun |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.18081 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Reasoned Safety Alignment: Ensuring Jailbreak Defense via Answer-Then-Check
by: Cao, Chentao, et al.
Published: (2025)
by: Cao, Chentao, et al.
Published: (2025)
Symbolic Representation for Any-to-Any Generative Tasks
by: Chen, Jiaqi, et al.
Published: (2025)
by: Chen, Jiaqi, et al.
Published: (2025)
MixEval-X: Any-to-Any Evaluations from Real-World Data Mixtures
by: Ni, Jinjie, et al.
Published: (2024)
by: Ni, Jinjie, et al.
Published: (2024)
Self-Evaluation Unlocks Any-Step Text-to-Image Generation
by: Yu, Xin, et al.
Published: (2025)
by: Yu, Xin, et al.
Published: (2025)
AR-Omni: A Unified Autoregressive Model for Any-to-Any Generation
by: Cheng, Dongjie, et al.
Published: (2026)
by: Cheng, Dongjie, et al.
Published: (2026)
NExT-GPT: Any-to-Any Multimodal LLM
by: Wu, Shengqiong, et al.
Published: (2023)
by: Wu, Shengqiong, et al.
Published: (2023)
AnyFit: Controllable Virtual Try-on for Any Combination of Attire Across Any Scenario
by: Li, Yuhan, et al.
Published: (2024)
by: Li, Yuhan, et al.
Published: (2024)
Multimodal Crystal Flow: Any-to-Any Modality Generation for Unified Crystal Modeling
by: Seong, Kiyoung, et al.
Published: (2026)
by: Seong, Kiyoung, et al.
Published: (2026)
How to Train a Leader: Hierarchical Reasoning in Multi-Agent LLMs
by: Estornell, Andrew, et al.
Published: (2025)
by: Estornell, Andrew, et al.
Published: (2025)
Any-Way Meta Learning
by: Lee, Junhoo, et al.
Published: (2024)
by: Lee, Junhoo, et al.
Published: (2024)
Why Deep Jacobian Spectra Separate: Depth-Induced Scaling and Singular-Vector Alignment
by: Haas, Nathanaël, et al.
Published: (2026)
by: Haas, Nathanaël, et al.
Published: (2026)
4M-21: An Any-to-Any Vision Model for Tens of Tasks and Modalities
by: Bachmann, Roman, et al.
Published: (2024)
by: Bachmann, Roman, et al.
Published: (2024)
Forgetting Any Data at Any Time: A Theoretically Certified Unlearning Framework for Vertical Federated Learning
by: Wang, Linian, et al.
Published: (2025)
by: Wang, Linian, et al.
Published: (2025)
ChatScene: Knowledge-Enabled Safety-Critical Scenario Generation for Autonomous Vehicles
by: Zhang, Jiawei, et al.
Published: (2024)
by: Zhang, Jiawei, et al.
Published: (2024)
Unifying Sequences, Structures, and Descriptions for Any-to-Any Protein Generation with the Large Multimodal Model HelixProtX
by: Chen, Zhiyuan, et al.
Published: (2024)
by: Chen, Zhiyuan, et al.
Published: (2024)
Depth Any Camera: Zero-Shot Metric Depth Estimation from Any Camera
by: Guo, Yuliang, et al.
Published: (2025)
by: Guo, Yuliang, et al.
Published: (2025)
AnyBCQ: Hardware Efficient Flexible Binary-Coded Quantization for Multi-Precision LLMs
by: Park, Gunho, et al.
Published: (2025)
by: Park, Gunho, et al.
Published: (2025)
Picky LLMs and Unreliable RMs: An Empirical Study on Safety Alignment after Instruction Tuning
by: Li, Guanlin, et al.
Published: (2025)
by: Li, Guanlin, et al.
Published: (2025)
Depth Anything at Any Condition
by: Sun, Boyuan, et al.
Published: (2025)
by: Sun, Boyuan, et al.
Published: (2025)
Curriculum Learning for Safety Alignment
by: Kumar, Sandeep, et al.
Published: (2026)
by: Kumar, Sandeep, et al.
Published: (2026)
Time Matters: Scaling Laws for Any Budget
by: Inbar, Itay, et al.
Published: (2024)
by: Inbar, Itay, et al.
Published: (2024)
AnyGraph: Graph Foundation Model in the Wild
by: Xia, Lianghao, et al.
Published: (2024)
by: Xia, Lianghao, et al.
Published: (2024)
Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration
by: Yang, Zhicheng, et al.
Published: (2025)
by: Yang, Zhicheng, et al.
Published: (2025)
Distribution-Based Feature Attribution for Explaining the Predictions of Any Classifier
by: Li, Xinpeng, et al.
Published: (2025)
by: Li, Xinpeng, et al.
Published: (2025)
A2D: Any-Order, Any-Step Safety Alignment for Diffusion Language Models
by: Jeung, Wonje, et al.
Published: (2025)
by: Jeung, Wonje, et al.
Published: (2025)
SoSBench: Benchmarking Safety Alignment on Six Scientific Domains
by: Jiang, Fengqing, et al.
Published: (2025)
by: Jiang, Fengqing, et al.
Published: (2025)
Safe Transformer: An Explicit Safety Bit For Interpretable And Controllable Alignment
by: Feng, Jingyuan, et al.
Published: (2026)
by: Feng, Jingyuan, et al.
Published: (2026)
The Blessing and Curse of Dimensionality in Safety Alignment
by: Teo, Rachel S. Y., et al.
Published: (2025)
by: Teo, Rachel S. Y., et al.
Published: (2025)
NeuronTune: Fine-Grained Neuron Modulation for Balanced Safety-Utility Alignment in LLMs
by: Pan, Birong, et al.
Published: (2025)
by: Pan, Birong, et al.
Published: (2025)
Course-Correction: Safety Alignment Using Synthetic Preferences
by: Xu, Rongwu, et al.
Published: (2024)
by: Xu, Rongwu, et al.
Published: (2024)
Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges
by: Lu, Haoran, et al.
Published: (2025)
by: Lu, Haoran, et al.
Published: (2025)
Unaligning Everything: Or Aligning Any Text to Any Image in Multimodal Models
by: Salman, Shaeke, et al.
Published: (2024)
by: Salman, Shaeke, et al.
Published: (2024)
PSPO*: An Effective Process-supervised Policy Optimization for Reasoning Alignment
by: Li, Jiawei, et al.
Published: (2024)
by: Li, Jiawei, et al.
Published: (2024)
Efficiency vs. Alignment: Investigating Safety and Fairness Risks in Parameter-Efficient Fine-Tuning of LLMs
by: Taraghi, Mina, et al.
Published: (2025)
by: Taraghi, Mina, et al.
Published: (2025)
Safe Pruning LoRA: Robust Distance-Guided Pruning for Safety Alignment in Adaptation of LLMs
by: Ao, Shuang, et al.
Published: (2025)
by: Ao, Shuang, et al.
Published: (2025)
BSO: Safety Alignment Is Density Ratio Matching
by: Nguyen, Tien-Phat, et al.
Published: (2026)
by: Nguyen, Tien-Phat, et al.
Published: (2026)
Test-Time Safety Alignment
by: Saglam, Baturay, et al.
Published: (2026)
by: Saglam, Baturay, et al.
Published: (2026)
CAP: Controllable Alignment Prompting for Unlearning in LLMs
by: Wang, Zhaokun, et al.
Published: (2026)
by: Wang, Zhaokun, et al.
Published: (2026)
Multi-Value Alignment for LLMs via Value Decorrelation and Extrapolation
by: Xu, Hefei, et al.
Published: (2025)
by: Xu, Hefei, et al.
Published: (2025)
AnyRotate: Gravity-Invariant In-Hand Object Rotation with Sim-to-Real Touch
by: Yang, Max, et al.
Published: (2024)
by: Yang, Max, et al.
Published: (2024)
Similar Items
-
Reasoned Safety Alignment: Ensuring Jailbreak Defense via Answer-Then-Check
by: Cao, Chentao, et al.
Published: (2025) -
Symbolic Representation for Any-to-Any Generative Tasks
by: Chen, Jiaqi, et al.
Published: (2025) -
MixEval-X: Any-to-Any Evaluations from Real-World Data Mixtures
by: Ni, Jinjie, et al.
Published: (2024) -
Self-Evaluation Unlocks Any-Step Text-to-Image Generation
by: Yu, Xin, et al.
Published: (2025) -
AR-Omni: A Unified Autoregressive Model for Any-to-Any Generation
by: Cheng, Dongjie, et al.
Published: (2026)