HIVE: Hidden-Evidence Verification for Hallucination Detection in Diffusion Large Language Models
cs.CL
Submitted: 2026-04-28
Updated: 2026-09-23
Comments: 5 figures, appendix included
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Lost in Diffusion: Uncovering Hallucination Patterns and Failure Modes in Diffusion Large Language Models
- TDGNet: Hallucination Detection in Diffusion Language Models via Temporal Dynamic Graphs
- Language Models (Mostly) Know What They Know
- Early Decisions Matter: Proximity Bias and Initial Trajectory Shaping in Non-Autoregressive Diffusion Language Models
- Semantic Entropy Probes: Robust and Cheap Hallucination Detection in LLMs
- Large Language Diffusion Models
- Steer LLM Latents for Hallucination Detection
- DynHD: Hallucination Detection for Diffusion Large Language Models via Denoising Dynamics Deviation Learning
- Qwen2.5 Technical Report
- Diffusion Language Models Are Natively Length-Aware
- HALT: Hallucination Assessment via Log-probs as Time series
- Scaling Behavior of Discrete Diffusion Language Models
- Dream 7B: Diffusion Large Language Models
Related papers
- Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
- Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
- Subliminal Steering: Stronger Encoding of Hidden Signals
- MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
- The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
- Untangling the Mechanisms of Misleading Context in Medical Question Answering