Instruction Following
The ability of an AI model to understand and execute tasks according to instructions provided in user or system prompts. It is a foundational metric for measuring model controllability and alignment, and is typically achieved through Supervised Fine-Tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF).
Timeline (last 90 days)
In the context of large language models, 'intent understanding' generally refers to the model's ability to map a user's natural language instructions or behavioral patterns to the user's actual underlying goals, a topic that academia sometimes places under the research scope of 'instruction following' or 'task alignment'.
This method measures answer quality along three core evaluation axes: Composition, Grounding, and Instruction-Following
All Facts (2)
In the context of large language models, 'intent understanding' generally refers to the model's ability to map a user's natural language instructions or behavioral patterns to the user's actual underlying goals, a topic that academia sometimes places under the research scope of 'instruction following' or 'task alignment'.
50%UnverifiedThis method measures answer quality along three core evaluation axes: Composition, Grounding, and Instruction-Following
50%