SingProbe Technical Report

arXiv:2608.30703 · cs.CR, cs.AI, cs.CL, cs.LG · Submitted 2026-08-31 · Read on arXiv

cs.CR, cs.AI, cs.CL, cs.LG

Submitted: 2026-08-31

Updated: 2026-09-21

Code: https://github.com/inclusionAI/SingProbehttps:

Terminology

• Hallucination — 59× in this paper · explained in 3 episodes
• AUC — 55× in this paper · explained in 2 episodes
• Benchmark — 31× in this paper · explained in 2 episodes
• Hallucination Detection — 19× in this paper · explained in 2 episodes
• Pruning — 10× in this paper · explained in 4 episodes
• Accuracy — 7× in this paper · explained in 1 episode
• Decode — 5× in this paper · explained in 2 episodes
• F1 Score — 5× in this paper · explained in 3 episodes
• Adaptation — 4× in this paper · explained in 1 episode
• Alignment — 4× in this paper · explained in 1 episode
• Robustness — 4× in this paper · explained in 5 episodes
• Steering — 4× in this paper · explained in 2 episodes
• Ablation — 3× in this paper · explained in 1 episode
• Ablation study — 3× in this paper · explained in 1 episode
• Benchmarking — 3× in this paper · explained in 3 episodes
• Verification — 3× in this paper · explained in 2 episodes
• Consistency — 2× in this paper · explained in 3 episodes
• Core — 2× in this paper · explained in 2 episodes
• Unified Framework — 2× in this paper · explained in 5 episodes
• Agentic Task — 1× in this paper · explained in 1 episode
• Agentic Tasks — 1× in this paper · explained in 1 episode
• Aggregation — 1× in this paper · explained in 1 episode
• Average Precision — 1× in this paper
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• Hallucination Mitigation — 1× in this paper · explained in 2 episodes
• LLM judge — 1× in this paper · explained in 2 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Positional Bias — 1× in this paper · explained in 2 episodes
• Self-consistency — 1× in this paper · explained in 2 episodes
• Verifier — 1× in this paper · explained in 2 episodes

Sources

• gpt-oss-120b & gpt-oss-20b Model Card
• HealthBench: Evaluating Large Language Models Towards Improved Human Health
• Program Synthesis with Large Language Models
• DRIFT: Detecting Representational Inconsistencies for Factual Truthfulness
• FactCHD: Benchmarking Fact-Conflicting Hallucination Detection
• Training Verifiers to Solve Math Word Problems
• Constitutional Classifiers++: Efficient Production-Grade Defenses against Universal Jailbreaks
• SingGuard: A Policy-Adaptive Multimodal LLM Guardrail with Dynamic Reasoning
• Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations
• AA-Omniscience: Evaluating Cross-Domain Knowledge Reliability in Large Language Models
• PKU-SafeRLHF: Towards Multi-Level Safety Alignment for LLMs with Human Preference
• YuFeng-XGuard: A Reasoning-Centric, Interpretable, and Flexible Guardrail Model for Large Language Models
• Hallucination Detection and Hallucination Mitigation: An Investigation
• Large Language Model Agent: A Survey on Methodology, Applications and Challenges
• Fine-grained Hallucination Detection and Editing for Language Models
• DARWIN: Evolving Jailbreak Adversary and Guardrail for LLM Safety Evaluation and Protection
• XSTest: A Test Suite for Identifying Exaggerated Safety Behaviours in Large Language Models
• Constitutional Classifiers: Defending against Universal Jailbreaks across Thousands of Hours of Red Teaming
• Qwen3 Technical Report
• Ensuring Safety and Trust: Analyzing the Risks of Large Language Models in Medicine

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