Cover Image

TrustLDM: Benchmarking Trustworthiness in Language Diffusion Models

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Mo, Yichuan, Jiang, Yukun, Shi, Yanbo, Li, Mingjie, Backes, Michael, Zhang, Yang, Wang, Yisen
Format:	Preprint
Published:	2026
Subjects:	Computation and Language Artificial Intelligence Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

TERD: A Unified Framework for Safeguarding Diffusion Models Against Backdoors
by: Mo, Yichuan, et al.
Published: (2024)

Jailbreak and Guard Aligned Language Models with Only Few In-Context Demonstrations
by: Wei, Zeming, et al.
Published: (2023)

Fight Back Against Jailbreaking via Prompt Adversarial Tuning
by: Mo, Yichuan, et al.
Published: (2024)

On the Adversarial Transferability of Generalized "Skip Connections"
by: Wang, Yisen, et al.
Published: (2024)

MultiTrust: A Comprehensive Benchmark Towards Trustworthy Multimodal Large Language Models
by: Zhang, Yichi, et al.
Published: (2024)

Sparse Models, Sparse Safety: Unsafe Routes in Mixture-of-Experts LLMs
by: Jiang, Yukun, et al.
Published: (2026)

Are Smarter LLMs Safer? Exploring Safety-Reasoning Trade-offs in Prompting and Fine-Tuning
by: Li, Ang, et al.
Published: (2025)

Decoding Large Language Diffusion Models with Foreseeing Movement
by: Mo, Yichuan, et al.
Published: (2025)

PID: Prompt-Independent Data Protection Against Latent Diffusion Models
by: Li, Ang, et al.
Published: (2024)

TrustAgent: Towards Safe and Trustworthy LLM-based Agents
by: Hua, Wenyue, et al.
Published: (2024)

Finding and Reactivating Post-Trained LLMs' Hidden Safety Mechanisms
by: Li, Mingjie, et al.
Published: (2026)

Generalist++: A Meta-learning Framework for Mitigating Trade-off in Adversarial Training
by: Wang, Yisen, et al.
Published: (2025)

TabDLM: Free-Form Tabular Data Generation via Joint Numerical-Language Diffusion
by: Cai, Donghong, et al.
Published: (2026)

Generalizing Trust: Weak-to-Strong Trustworthiness in Language Models
by: Pawelczyk, Martin, et al.
Published: (2024)

Reconstruct Your Previous Conversations! Comprehensively Investigating Privacy Leakage Risks in Conversations with GPT Models
by: Chu, Junjie, et al.
Published: (2024)

Diffusion of Thoughts: Chain-of-Thought Reasoning in Diffusion Language Models
by: Ye, Jiacheng, et al.
Published: (2024)

Unraveling Text Generation in LLMs: A Stochastic Differential Equation Approach
by: Zhang, Yukun
Published: (2024)

DivLogicEval: A Framework for Benchmarking Logical Reasoning Evaluation in Large Language Models
by: Chung, Tsz Ting, et al.
Published: (2025)

Trustworthy Summarization via Uncertainty Quantification and Risk Awareness in Large Language Models
by: Pan, Shuaidong, et al.
Published: (2025)

How Sparse Attention Approximates Exact Attention? Your Attention is Naturally $n^C$-Sparse
by: Deng, Yichuan, et al.
Published: (2024)

A Simple and Effective Pruning Approach for Large Language Models
by: Sun, Mingjie, et al.
Published: (2023)

Beyond Size: How Gradients Shape Pruning Decisions in Large Language Models
by: Das, Rocktim Jyoti, et al.
Published: (2023)

Soft-Masked Diffusion Language Models
by: Hersche, Michael, et al.
Published: (2025)

DLM-Scope: Mechanistic Interpretability of Diffusion Language Models via Sparse Autoencoders
by: Wang, Xu, et al.
Published: (2026)

Calibrating Long-form Generations from Large Language Models
by: Huang, Yukun, et al.
Published: (2024)

Benchmarking Benchmark Leakage in Large Language Models
by: Xu, Ruijie, et al.
Published: (2024)

Generalization or Memorization: Data Contamination and Trustworthy Evaluation for Large Language Models
by: Dong, Yihong, et al.
Published: (2024)

Cite Pretrain: Retrieval-Free Knowledge Attribution for Large Language Models
by: Huang, Yukun, et al.
Published: (2025)

Unveiling LLM Mechanisms Through Neural ODEs and Control Theory
by: Zhang, Yukun, et al.
Published: (2024)

Locally Coherent Parallel Decoding in Diffusion Language Models
by: Hersche, Michael, et al.
Published: (2026)

Fluid Language Model Benchmarking
by: Hofmann, Valentin, et al.
Published: (2025)

Training Optimal Large Diffusion Language Models
by: Ni, Jinjie, et al.
Published: (2025)

Enhancing Trust in Large Language Models via Uncertainty-Calibrated Fine-Tuning
by: Krishnan, Ranganath, et al.
Published: (2024)

dLLM-Cache: Accelerating Diffusion Large Language Models with Adaptive Caching
by: Liu, Zhiyuan, et al.
Published: (2025)

Learning to Trust the Crowd: A Multi-Model Consensus Reasoning Engine for Large Language Models
by: Kallem, Pranav
Published: (2026)

LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit
by: Gong, Ruihao, et al.
Published: (2024)

Non-Markovian Discrete Diffusion with Causal Language Models
by: Zhang, Yangtian, et al.
Published: (2025)

MANGO: A Benchmark for Evaluating Mapping and Navigation Abilities of Large Language Models
by: Ding, Peng, et al.
Published: (2024)

Context-Aware Initialization for Reducing Generative Path Length in Diffusion Language Models
by: Miao, Tongyuan, et al.
Published: (2025)

Prompt Optimization Via Diffusion Language Models
by: Wang, Shiyu, et al.
Published: (2026)