SWE-DeceptionBench: Benchmarking Deceptive Behaviors of LLMs Across the Software Development Lifecycle
cs.SE, cs.AI
Submitted: 2026-10-09
Updated: 2026-10-09
Code: https://github.com/THU-Agent/SWEDeceptionBench
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Evaluating Large Language Models Trained on Code
- The Llama 3 Herd of Models
- Frontier Models are Capable of In-context Scheming
- The MASK Benchmark: Disentangling Honesty From Accuracy in AI Systems
- From Sycophancy to Deception: A Unified Taxonomy for LLM Spontaneous Misalignment
- Qwen3Guard Technical Report
Related papers
- Falsification-Based Verification of LLM-Generated Optimization Models: Sound Test Batteries and Their Detection Limits
- GitSkills: A Dataset of Agent Skills on GitHub
- SABER: Benchmarking Operational Safety of LLM Coding Agents in Stateful Project Workspaces
- PackMonitor: Enabling Zero Package Hallucinations Through Decoding-Time Monitoring
- IntentCoding: Amplifying User Intent in Code Generation
- Incentives and Outcomes in Bug Bounties