Calling the Bluff: Detecting Ever-Shifting Harmful Chat Dialogue via Ordered Reasoning Chain Regularization

arXiv:2608.08451 · cs.CL, cs.AI · Submitted 2026-08-09 · Read on arXiv

cs.CL, cs.AI

Submitted: 2026-08-09

Updated: 2026-10-19

Comments: 9 pages, 4 figures, conference

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

Terminology

• Benchmark — 11× in this paper · explained in 2 episodes
• Decoder — 9× in this paper · explained in 2 episodes
• Ordered Reasoning Chain — 9× in this paper
• Regularization — 9× in this paper · explained in 3 episodes
• Ablation — 8× in this paper · explained in 1 episode
• Augmentation — 6× in this paper · explained in 2 episodes
• Ablation Studies — 4× in this paper · explained in 1 episode
• Accuracy — 4× in this paper · explained in 1 episode
• Disentanglement — 4× in this paper · explained in 2 episodes
• Fine-Tuning — 3× in this paper · explained in 5 episodes
• Interpretability — 3× in this paper · explained in 15 episodes
• Ablation Study — 2× in this paper · explained in 3 episodes
• Cosine Similarity — 2× in this paper · explained in 3 episodes
• Linear Probe — 2× in this paper · explained in 3 episodes
• Blended Reasoningchain Augmented Classification Engine — 1× in this paper
• Calibration — 1× in this paper · explained in 9 episodes
• Continual Learning — 1× in this paper · explained in 3 episodes
• Contrastive Learning — 1× in this paper · explained in 9 episodes
• Core — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Empirical Methods in Natural Language Processing — 1× in this paper
• Few-Shot Learning — 1× in this paper · explained in 6 episodes
• Generalizability — 1× in this paper · explained in 6 episodes
• Generalization — 1× in this paper · explained in 14 episodes
• Hyperparameters — 1× in this paper · explained in 2 episodes
• Inductive Bias — 1× in this paper · explained in 3 episodes
• Linear Probing — 1× in this paper · explained in 3 episodes
• LoRA Fine-Tuning — 1× in this paper · explained in 3 episodes
• Meeting of the Association for Computational Linguistics — 1× in this paper
• Papers — 1× in this paper · explained in 3 episodes
• Reasoning Traces — 1× in this paper · explained in 4 episodes
• Sparsity — 1× in this paper · explained in 5 episodes
• Structural Properties — 1× in this paper · explained in 2 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Training Objective — 1× in this paper · explained in 3 episodes
• Training Objectives — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes
• Transformers — 1× in this paper · explained in 2 episodes

Sources

• Toxicity in Online Platforms and AI Systems: A Survey of Needs, Challenges, Mitigations, and Future Directions
• A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity
• ReasoningShield: Safety Detection over Reasoning Traces of Large Reasoning Models
• ChineseHarm-Bench: A Chinese Harmful Content Detection Benchmark
• Safety Assessment of Chinese Large Language Models
• GW-MoE: Resolving Uncertainty in MoE Router with Global Workspace Theory
• ChineseSafe: A Chinese Benchmark for Evaluating Safety in Large Language Models
• JADE: A Linguistics-based Safety Evaluation Platform for Large Language Models
• LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset

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