Saved in:
| Main Authors: | Luo, Jinyuan, Fang, Zhen, Li, Yixuan, Park, Seongheon, Chen, Ling |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2506.02696 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Steer LLM Latents for Hallucination Detection
by: Park, Seongheon, et al.
Published: (2025)
by: Park, Seongheon, et al.
Published: (2025)
GLSim: Detecting Object Hallucinations in LVLMs via Global-Local Similarity
by: Park, Seongheon, et al.
Published: (2025)
by: Park, Seongheon, et al.
Published: (2025)
Beyond In-Domain Detection: SpikeScore for Cross-Domain Hallucination Detection
by: Deng, Yongxin, et al.
Published: (2026)
by: Deng, Yongxin, et al.
Published: (2026)
Understanding Language Prior of LVLMs by Contrasting Chain-of-Embedding
by: Long, Lin, et al.
Published: (2025)
by: Long, Lin, et al.
Published: (2025)
ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection
by: Peng, Bo, et al.
Published: (2024)
by: Peng, Bo, et al.
Published: (2024)
HalluEntity: Benchmarking and Understanding Entity-Level Hallucination Detection
by: Yeh, Min-Hsuan, et al.
Published: (2025)
by: Yeh, Min-Hsuan, et al.
Published: (2025)
Whispers that Shake Foundations: Analyzing and Mitigating False Premise Hallucinations in Large Language Models
by: Yuan, Hongbang, et al.
Published: (2024)
by: Yuan, Hongbang, et al.
Published: (2024)
Beyond Functional Correctness: Exploring Hallucinations in LLM-Generated Code
by: Liu, Fang, et al.
Published: (2024)
by: Liu, Fang, et al.
Published: (2024)
Hallucination Detection and Hallucination Mitigation: An Investigation
by: Luo, Junliang, et al.
Published: (2024)
by: Luo, Junliang, et al.
Published: (2024)
Assessing and Mitigating Miscalibration in LLM-Based Social Science Measurement
by: Wang, Jinyuan, et al.
Published: (2026)
by: Wang, Jinyuan, et al.
Published: (2026)
Enhancing Hallucination Detection through Perturbation-Based Synthetic Data Generation in System Responses
by: Zhang, Dongxu, et al.
Published: (2024)
by: Zhang, Dongxu, et al.
Published: (2024)
Uncertainty Quantification in LLM Agents: Foundations, Emerging Challenges, and Opportunities
by: Oh, Changdae, et al.
Published: (2026)
by: Oh, Changdae, et al.
Published: (2026)
Probing LLM Hallucination from Within: Perturbation-Driven Approach via Internal Knowledge
by: Lee, Seongmin, et al.
Published: (2024)
by: Lee, Seongmin, et al.
Published: (2024)
On the Structural Memory of LLM Agents
by: Zeng, Ruihong, et al.
Published: (2024)
by: Zeng, Ruihong, et al.
Published: (2024)
LLM-CAS: Dynamic Neuron Perturbation for Real-Time Hallucination Correction
by: Zhang, Jensen, et al.
Published: (2025)
by: Zhang, Jensen, et al.
Published: (2025)
Toxic HallucinAItions: Perturbing Prompts and Tracing LLM Circuits
by: Shimgekar, Soorya Ram, et al.
Published: (2026)
by: Shimgekar, Soorya Ram, et al.
Published: (2026)
Shaking the Fake: Detecting Deepfake Videos in Real Time via Active Probes
by: Xie, Zhixin, et al.
Published: (2024)
by: Xie, Zhixin, et al.
Published: (2024)
Zero-resource Hallucination Detection for Text Generation via Graph-based Contextual Knowledge Triples Modeling
by: Fang, Xinyue, et al.
Published: (2024)
by: Fang, Xinyue, et al.
Published: (2024)
Hide-and-Seek in Trajectories: Discovering Failure Signals for VLA Runtime Monitoring
by: Park, Seongheon, et al.
Published: (2026)
by: Park, Seongheon, et al.
Published: (2026)
The MedPerturb Dataset: What Non-Content Perturbations Reveal About Human and Clinical LLM Decision Making
by: Gourabathina, Abinitha, et al.
Published: (2025)
by: Gourabathina, Abinitha, et al.
Published: (2025)
Enhancing Mathematical Reasoning in Large Language Models with Self-Consistency-Based Hallucination Detection
by: Liu, MingShan, et al.
Published: (2025)
by: Liu, MingShan, et al.
Published: (2025)
VAUQ: Vision-Aware Uncertainty Quantification for LVLM Self-Evaluation
by: Park, Seongheon, et al.
Published: (2026)
by: Park, Seongheon, et al.
Published: (2026)
Microsaccade-Inspired Probing: Positional Encoding Perturbations Reveal LLM Misbehaviours
by: Melo, Rui, et al.
Published: (2025)
by: Melo, Rui, et al.
Published: (2025)
Enhancing Hallucination Detection via Future Context
by: Lee, Joosung, et al.
Published: (2025)
by: Lee, Joosung, et al.
Published: (2025)
LLM Lies: Hallucinations are not Bugs, but Features as Adversarial Examples
by: Yao, Jia-Yu, et al.
Published: (2023)
by: Yao, Jia-Yu, et al.
Published: (2023)
Respecting Modality Gap in Post-hoc Out-of-distribution Detection with Pre-trained Vision-Language Models
by: Hu, Yuanwei, et al.
Published: (2026)
by: Hu, Yuanwei, et al.
Published: (2026)
Revealing Multi-View Hallucination in Large Vision-Language Models
by: Park, Wooje, et al.
Published: (2026)
by: Park, Wooje, et al.
Published: (2026)
EF-LLM: Energy Forecasting LLM with AI-assisted Automation, Enhanced Sparse Prediction, Hallucination Detection
by: Qiu, Zihang, et al.
Published: (2024)
by: Qiu, Zihang, et al.
Published: (2024)
Nonsense Helps: Prompt Space Perturbation Broadens Reasoning Exploration
by: Huang, Langlin, et al.
Published: (2026)
by: Huang, Langlin, et al.
Published: (2026)
FaithLens: Detecting and Explaining Faithfulness Hallucination
by: Si, Shuzheng, et al.
Published: (2025)
by: Si, Shuzheng, et al.
Published: (2025)
Explainable LLM Unlearning Through Reasoning
by: Liao, Junfeng, et al.
Published: (2026)
by: Liao, Junfeng, et al.
Published: (2026)
RepreGuard: Detecting LLM-Generated Text by Revealing Hidden Representation Patterns
by: Chen, Xin, et al.
Published: (2025)
by: Chen, Xin, et al.
Published: (2025)
Asynchronous Voice Anonymization Using Adversarial Perturbation On Speaker Embedding
by: Wang, Rui, et al.
Published: (2024)
by: Wang, Rui, et al.
Published: (2024)
NoiseBoost: Alleviating Hallucination with Noise Perturbation for Multimodal Large Language Models
by: Wu, Kai, et al.
Published: (2024)
by: Wu, Kai, et al.
Published: (2024)
AutoPBO: LLM-powered Optimization for Local Search PBO Solvers
by: Li, Jinyuan, et al.
Published: (2025)
by: Li, Jinyuan, et al.
Published: (2025)
PerturboLLaVA: Reducing Multimodal Hallucinations with Perturbative Visual Training
by: Chen, Cong, et al.
Published: (2025)
by: Chen, Cong, et al.
Published: (2025)
Is LLMs Hallucination Usable? LLM-based Negative Reasoning for Fake News Detection
by: Zhang, Chaowei, et al.
Published: (2025)
by: Zhang, Chaowei, et al.
Published: (2025)
Two Pathways to Truthfulness: On the Intrinsic Encoding of LLM Hallucinations
by: Luo, Wen, et al.
Published: (2026)
by: Luo, Wen, et al.
Published: (2026)
TRACE the Evidence: Constructing Knowledge-Grounded Reasoning Chains for Retrieval-Augmented Generation
by: Fang, Jinyuan, et al.
Published: (2024)
by: Fang, Jinyuan, et al.
Published: (2024)
Failure Ontology: A Lifelong Learning Framework for Blind Spot Detection and Resilience Design
by: Sun, Yuan, et al.
Published: (2026)
by: Sun, Yuan, et al.
Published: (2026)
Similar Items
-
Steer LLM Latents for Hallucination Detection
by: Park, Seongheon, et al.
Published: (2025) -
GLSim: Detecting Object Hallucinations in LVLMs via Global-Local Similarity
by: Park, Seongheon, et al.
Published: (2025) -
Beyond In-Domain Detection: SpikeScore for Cross-Domain Hallucination Detection
by: Deng, Yongxin, et al.
Published: (2026) -
Understanding Language Prior of LVLMs by Contrasting Chain-of-Embedding
by: Long, Lin, et al.
Published: (2025) -
ConjNorm: Tractable Density Estimation for Out-of-Distribution Detection
by: Peng, Bo, et al.
Published: (2024)