Traceable LLM Reasoning for Fake-Order Fraud Detection

arXiv:2607.23075 · cs.CR, cs.AI, cs.LG · Submitted 2026-07-25 · Read on arXiv

Siqi You, Bingsong Xu, Zhixian Zheng, Xinjian Peng, Yang Xie, Ying Wang, Jiarong Xu

cs.CR, cs.AI, cs.LG

Submitted: 2026-07-25

Comments: 15 pages, 3 figures

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 29× in this paper · explained in 1 episode
• Reinforcement Learning — 21× in this paper · explained in 4 episodes
• Verification — 15× in this paper · explained in 2 episodes
• Adaptation — 9× in this paper · explained in 1 episode
• Domain Adaptation — 8× in this paper · explained in 5 episodes
• Trace — 8× in this paper · explained in 2 episodes
• Consistency — 6× in this paper · explained in 3 episodes
• Alignment — 4× in this paper · explained in 1 episode
• Core — 4× in this paper · explained in 2 episodes
• Data Augmentation — 4× in this paper · explained in 7 episodes
• Interpretability — 4× in this paper · explained in 15 episodes
• Representation Learning — 4× in this paper · explained in 2 episodes
• Large Language Models (LLMs) — 3× in this paper · explained in 6 episodes
• Reward Function — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Embeddings — 2× in this paper · explained in 2 episodes
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• GRPO — 2× in this paper · explained in 6 episodes
• Perplexity — 2× in this paper · explained in 3 episodes
• Reasoning Traces — 2× in this paper · explained in 3 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Chain-of-Thought (CoT) — 1× in this paper · explained in 4 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• Downstream Tasks — 1× in this paper · explained in 2 episodes
• F1 Score — 1× in this paper · explained in 3 episodes
• GRPO Objective — 1× in this paper · explained in 2 episodes
• Gross Merchandise Volume — 1× in this paper
• Group Relative Policy Optimization (GRPO) — 1× in this paper · explained in 5 episodes
• Iterative Refinement — 1× in this paper · explained in 3 episodes
• Modality Gap — 1× in this paper · explained in 4 episodes
• Multimodal Inputs — 1× in this paper · explained in 2 episodes
• Objective Function — 1× in this paper · explained in 2 episodes
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 5 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes
• Reward Hacking — 1× in this paper · explained in 8 episodes
• Structured Reasoning — 1× in this paper · explained in 3 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes

Sources

• InternLM2 Technical Report
• KTO: Model Alignment as Prospect Theoretic Optimization
• MOON Embedding: Multimodal Representation Learning for E-commerce Search Advertising
• ChatGLM: A Family of Large Language Models from GLM-130B to GLM-4 All Tools
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
• Proximal Policy Optimization Algorithms
• CausalTAD: Injecting Causal Knowledge into Large Language Models for Tabular Anomaly Detection
• MOON3.0: Reasoning-aware Multimodal Representation Learning for E-commerce Product Understanding
• Learning to Reason under Off-Policy Guidance
• Qwen3 Technical Report
• SWIFT:A Scalable lightWeight Infrastructure for Fine-Tuning

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