There is no better exercise in clear communication than writing data annotation guidelines
PROMPT ENGINEERING
-
ChatGPT Generated Content and Rule Compliance Issues
By
–
He didn't roll his own. Chatgpt rolled it for him. So the rule isn't broken!
-
Flux AI Model: Weekly Lab Overview and Testing Guide
By
–
Quien quiera saber un poco más de Flux y probarlo, en el vídeo de esta semana del lab os hablé de él.
-
Using ‘please’ in system instructions as a prompt engineering technique
By
–
A simple trick – just add “please” to all your system instructions
-
LLM Evaluation Prompts Still Challenging Current Models
By
–
¿Qué prompts soléis utilizar para evaluar a los LLMs y que todavía a día de hoy veáis que cuestan ser superados por los modelos actuales? Estoy recopilando y testeando. Por cierto, el Anonymous GPT por ahora pinta bien.
-
Using Claude as an Editor: Improving AI-Generated Content Quality
By
–
I’ve been using Claude as an editor for the past few months. It’s great, but it gives me an A- on practically any first draft I send it.
— Packy McCormick (@packyM) 7 août 2024
Dan and I try to fix that. He’s a master. https://t.co/q1YEySkWPNI’ve been using Claude as an editor for the past few months. It’s great, but it gives me an A- on practically any first draft I send it. Dan and I try to fix that. He’s a master.
-
IPAdapter-Instruct: Resolving Ambiguity in Image-based Conditioning
By
–
Unity presents IPAdapter-Instruct Resolving Ambiguity in Image-based Conditioning using Instruct Prompts discuss: https://
huggingface.co/papers/2408.03
209
… Diffusion models continuously push the boundary of state-of-the-art image generation, but the process is hard to control with any nuance: -
GPT-4o blurts wrong answer, then self-corrects; structured output tangential
By
–
It helps, but in this case GPT-4o often blurts out the wrong answer at the start but then realizes and fixes the mistake as it talks. If you grade liberally in that case, most naive prompts asking for reasoning will work fine. Structured Output is slightly tangential here.
-
OpenAI docs include ‘9.11 > 9.9’ solved by JSON output
By
–
"9.11 > 9.9" is now in the OpenAI docs, as a problem solved by requesting JSON structured output to separate final answers from supporting reasoning:
-
Function Calls vs JSON Output: Usage Differences Explored
By
–
Curious how different this is from function calls as I know a lot of people were using them for just the JSON output