Saved in:
| Main Authors: | Guo, Zhengnan, Tan, Fei |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.10556 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
HIVE: Hidden-Evidence Verification for Hallucination Detection in Diffusion Large Language Models
by: Zhao, Guoshenghui, et al.
Published: (2026)
by: Zhao, Guoshenghui, et al.
Published: (2026)
DiffuGuard: How Intrinsic Safety is Lost and Found in Diffusion Large Language Models
by: Li, Zherui, et al.
Published: (2025)
by: Li, Zherui, et al.
Published: (2025)
DynHD: Hallucination Detection for Diffusion Large Language Models via Denoising Dynamics Deviation Learning
by: Qian, Yanyu, et al.
Published: (2026)
by: Qian, Yanyu, et al.
Published: (2026)
Logical Closed Loop: Uncovering Object Hallucinations in Large Vision-Language Models
by: Wu, Junfei, et al.
Published: (2024)
by: Wu, Junfei, et al.
Published: (2024)
The Confidence Shortcut: A Reasoning Failure Mode of Masked Diffusion Models
by: Kim, Dueun, et al.
Published: (2026)
by: Kim, Dueun, et al.
Published: (2026)
TraceDet: Hallucination Detection from the Decoding Trace of Diffusion Large Language Models
by: Chang, Shenxu, et al.
Published: (2025)
by: Chang, Shenxu, et al.
Published: (2025)
TDGNet: Hallucination Detection in Diffusion Language Models via Temporal Dynamic Graphs
by: Hemmat, Arshia, et al.
Published: (2026)
by: Hemmat, Arshia, et al.
Published: (2026)
Lost in Translation and Noise: A Deep Dive into the Failure Modes of VLMs on Real-World Tables
by: Singh, Anshul, et al.
Published: (2025)
by: Singh, Anshul, et al.
Published: (2025)
Lost in Translation: Latent Concept Misalignment in Text-to-Image Diffusion Models
by: Zhao, Juntu, et al.
Published: (2024)
by: Zhao, Juntu, et al.
Published: (2024)
Lost in Transcription, Found in Distribution Shift: Demystifying Hallucination in Speech Foundation Models
by: Atwany, Hanin, et al.
Published: (2025)
by: Atwany, Hanin, et al.
Published: (2025)
Large Language Diffusion Models
by: Nie, Shen, et al.
Published: (2025)
by: Nie, Shen, et al.
Published: (2025)
Jailbreaking Large Language Diffusion Models: Revealing Hidden Safety Flaws in Diffusion-Based Text Generation
by: Zhang, Yuanhe, et al.
Published: (2025)
by: Zhang, Yuanhe, et al.
Published: (2025)
Patterns of Persistence and Diffusibility across the World's Languages
by: Chen, Yiyi, et al.
Published: (2024)
by: Chen, Yiyi, et al.
Published: (2024)
Reinforcing the Diffusion Chain of Lateral Thought with Diffusion Language Models
by: Huang, Zemin, et al.
Published: (2025)
by: Huang, Zemin, et al.
Published: (2025)
Uncovering Overfitting in Large Language Model Editing
by: Zhang, Mengqi, et al.
Published: (2024)
by: Zhang, Mengqi, et al.
Published: (2024)
Lost in Inference: Rediscovering the Role of Natural Language Inference for Large Language Models
by: Madaan, Lovish, et al.
Published: (2024)
by: Madaan, Lovish, et al.
Published: (2024)
The Hallucinations Leaderboard -- An Open Effort to Measure Hallucinations in Large Language Models
by: Hong, Giwon, et al.
Published: (2024)
by: Hong, Giwon, et al.
Published: (2024)
C$^2$DLM: Causal Concept-Guided Diffusion Large Language Models
by: Han, Kairong, et al.
Published: (2025)
by: Han, Kairong, et al.
Published: (2025)
Uncertainty Quantification for Large Language Diffusion Models
by: Vazhentsev, Artem, et al.
Published: (2026)
by: Vazhentsev, Artem, et al.
Published: (2026)
From Signal Degradation to Computation Collapse: Uncovering the Two Failure Modes of LLM Quantization
by: Zhou, Chenxi, et al.
Published: (2026)
by: Zhou, Chenxi, et al.
Published: (2026)
Alleviating Hallucinations of Large Language Models through Induced Hallucinations
by: Zhang, Yue, et al.
Published: (2023)
by: Zhang, Yue, et al.
Published: (2023)
Multilingual Hallucination Gaps in Large Language Models
by: Chataigner, Cléa, et al.
Published: (2024)
by: Chataigner, Cléa, et al.
Published: (2024)
DiffER: Diffusion Entity-Relation Modeling for Reversal Curse in Diffusion Large Language Models
by: He, Shaokai, et al.
Published: (2026)
by: He, Shaokai, et al.
Published: (2026)
Mitigating Hallucinations in Large Vision-Language Models by Self-Injecting Hallucinations
by: Lu, Yifan, et al.
Published: (2025)
by: Lu, Yifan, et al.
Published: (2025)
Benchmarking Hallucination in Large Language Models based on Unanswerable Math Word Problem
by: Sun, Yuhong, et al.
Published: (2024)
by: Sun, Yuhong, et al.
Published: (2024)
The Energy of Falsehood: Detecting Hallucinations via Diffusion Model Likelihoods
by: Gautam, Arpit Singh, et al.
Published: (2026)
by: Gautam, Arpit Singh, et al.
Published: (2026)
Self Speculative Decoding for Diffusion Large Language Models
by: Gao, Yifeng, et al.
Published: (2025)
by: Gao, Yifeng, et al.
Published: (2025)
Dream 7B: Diffusion Large Language Models
by: Ye, Jiacheng, et al.
Published: (2025)
by: Ye, Jiacheng, et al.
Published: (2025)
Lost in Benchmarks? Rethinking Large Language Model Benchmarking with Item Response Theory
by: Zhou, Hongli, et al.
Published: (2025)
by: Zhou, Hongli, et al.
Published: (2025)
MeasHalu: Mitigation of Scientific Measurement Hallucinations for Large Language Models with Enhanced Reasoning
by: Huang, Ruijun, et al.
Published: (2026)
by: Huang, Ruijun, et al.
Published: (2026)
Mitigating Hallucinations in Large Vision-Language Models by Adaptively Constraining Information Flow
by: Bai, Jiaqi, et al.
Published: (2025)
by: Bai, Jiaqi, et al.
Published: (2025)
AR-MAP: Are Autoregressive Large Language Models Implicit Teachers for Diffusion Large Language Models?
by: Lin, Liang, et al.
Published: (2026)
by: Lin, Liang, et al.
Published: (2026)
Large Language Models to Diffusion Finetuning
by: Cetin, Edoardo, et al.
Published: (2025)
by: Cetin, Edoardo, et al.
Published: (2025)
Exploring and Mitigating Fawning Hallucinations in Large Language Models
by: Shangguan, Zixuan, et al.
Published: (2025)
by: Shangguan, Zixuan, et al.
Published: (2025)
Large Language Models Hallucination: A Comprehensive Survey
by: Alansari, Aisha, et al.
Published: (2025)
by: Alansari, Aisha, et al.
Published: (2025)
Mitigating Large Language Model Hallucination with Faithful Finetuning
by: Hu, Minda, et al.
Published: (2024)
by: Hu, Minda, et al.
Published: (2024)
"Lost-in-the-Later": Framework for Quantifying Contextual Grounding in Large Language Models
by: Tao, Yufei, et al.
Published: (2025)
by: Tao, Yufei, et al.
Published: (2025)
How Large Language Models are Designed to Hallucinate
by: Ackermann, Richard, et al.
Published: (2025)
by: Ackermann, Richard, et al.
Published: (2025)
DHI: Leveraging Diverse Hallucination Induction for Enhanced Contrastive Factuality Control in Large Language Models
by: Guo, Jiani, et al.
Published: (2026)
by: Guo, Jiani, et al.
Published: (2026)
Hallucination Detection and Evaluation of Large Language Model
by: Zhang, Chenggong, et al.
Published: (2025)
by: Zhang, Chenggong, et al.
Published: (2025)
Similar Items
-
HIVE: Hidden-Evidence Verification for Hallucination Detection in Diffusion Large Language Models
by: Zhao, Guoshenghui, et al.
Published: (2026) -
DiffuGuard: How Intrinsic Safety is Lost and Found in Diffusion Large Language Models
by: Li, Zherui, et al.
Published: (2025) -
DynHD: Hallucination Detection for Diffusion Large Language Models via Denoising Dynamics Deviation Learning
by: Qian, Yanyu, et al.
Published: (2026) -
Logical Closed Loop: Uncovering Object Hallucinations in Large Vision-Language Models
by: Wu, Junfei, et al.
Published: (2024) -
The Confidence Shortcut: A Reasoning Failure Mode of Masked Diffusion Models
by: Kim, Dueun, et al.
Published: (2026)