ToolDF: Tool-Integrated Reasoning for Mixed-Authenticity Audio Deepfake Detection

arXiv:2609.03620 · eess.AS, cs.AI, cs.SD · Submitted 2026-09-03 · Read on arXiv

eess.AS, cs.AI, cs.SD

Submitted: 2026-09-03

Updated: 2026-09-07

Code: https://github.com/rlataewoo/tooldf

Terminology

• Benchmark — 18× in this paper · explained in 2 episodes
• Aggregation — 6× in this paper · explained in 1 episode
• Ablation — 5× in this paper · explained in 1 episode
• F1 Score — 5× in this paper · explained in 3 episodes
• Fine-Tuning — 4× in this paper · explained in 5 episodes
• Generalization — 3× in this paper · explained in 13 episodes
• Interpretability — 2× in this paper · explained in 15 episodes
• Structured Reasoning — 2× in this paper · explained in 3 episodes
• Verification — 2× in this paper · explained in 2 episodes
• Ablation study — 1× in this paper · explained in 1 episode
• Adam — 1× in this paper · explained in 2 episodes
• Adaptation — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Low-Rank Adaptation (LoRA) — 1× in this paper · explained in 9 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Supervised Fine-Tuning (SFT) — 1× in this paper · explained in 8 episodes
• Trace — 1× in this paper · explained in 2 episodes
• Transformer — 1× in this paper · explained in 2 episodes

Sources

• MusicLM: Generating Music From Text
• Towards Explicit Acoustic Evidence Perception in Audio LLMs for Speech Deepfake Detection
• Interpretable All-Type Audio Deepfake Detection with Audio LLMs via Frequency-Time Reinforcement Learning
• ToolRL: Reward is All Tool Learning Needs
• Omni-R1: Do You Really Need Audio to Fine-Tune Your Audio LLM?
• Qwen2.5-Omni Technical Report

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