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Use this FREE tool to identify hallucinated & fake references. This tool is used by many scientific journals. 1. Go to and log in 2. Upload the paper or list of references 3. Reviewer3 will check each reference 4. It will display a YES or NO for each reference... show more

Faheem Ullah

22,463 subscribers

10,192 Aufrufe • vor 8 Monaten •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

4 Kommentare

Profilbild von Juzly

Juzlyvor 8 Monaten

@reviewer3com I used ChatGPT, but the references were fake.

Profilbild von Faheem Ullah

Faheem Ullahvor 8 Monaten

@reviewer3com This happens a lot. @reviewer3com can help to identify these fake references.

Profilbild von WriteForm

WriteFormvor 8 Monaten

@reviewer3com Amazing. This solves so many problems with people claiming so many fake citations from the hallucinations

Profilbild von Faheem Ullah

Faheem Ullahvor 8 Monaten

@reviewer3com Exactly. Glad you found it useful

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3. Click on the "+" in the chat bar and select Connectors and you will see the Scite Connector enabled. Now if you ask a question, Claude will answer it with reference to papers in the Scite database. No hallucinations, no fake references.

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82,922 Aufrufe • vor 11 Monaten

What started as building a personal taste.md skill for myself, turned into building a pipeline to create any taste as a skill. The most important piece is references. This is where you should spend time. If the references suck, so does the skill. I find that references cropped tightly on details in high resolution work the best. Each image gets analyzed by both Opus 4.7 and GPT 5.5. The analysis is based on why the reference is successful as a piece of design - not what it does functionally. Using two models helps rule out biases and gaps from each. The models focus on layout, spacing, typography, rhythm, composition, hierarchy, etc. At the end, each image has: reference-01/ - opus-4-7-analysis.md - gpt-5-5-analysis.md Then we fuse them together using GPT 5.5 - but the md files are anonymized so 5.5 doesn't prefer itself. reference-01/ - fused-analysis.md reference-02/ - fused-analysis.md etc. After fusion, we have one synthesized analysis per reference. Now the goal is to combine all of those into a single rule set. This is where chunking matters. If you ask one model to combine 100 image analyses at once, the result becomes too broad. It summarizes instead of preserving the granular design rules we want. Instead we chunk the fused analyses into smaller groups. Each group gets merged into a chunk-level synthesis, usually from around 6 to 8 image notes at a time. Then one final model pass fuses those chunks into a single md rule set. Finally, using the rule set, we write a skill of concrete instructions. It enforces constraints, uses imperative wording, and avoids vague taste words.

What started as building a personal taste.md skill for myself, turned into building a pipeline to create any taste as a skill. The most important piece is references. This is where you should spend time. If the references suck, so does the skill. I find that references cropped tightly on details in high resolution work the best. Each image gets analyzed by both Opus 4.7 and GPT 5.5. The analysis is based on why the reference is successful as a piece of design - not what it does functionally. Using two models helps rule out biases and gaps from each. The models focus on layout, spacing, typography, rhythm, composition, hierarchy, etc. At the end, each image has: reference-01/ - opus-4-7-analysis.md - gpt-5-5-analysis.md Then we fuse them together using GPT 5.5 - but the md files are anonymized so 5.5 doesn't prefer itself. reference-01/ - fused-analysis.md reference-02/ - fused-analysis.md etc. After fusion, we have one synthesized analysis per reference. Now the goal is to combine all of those into a single rule set. This is where chunking matters. If you ask one model to combine 100 image analyses at once, the result becomes too broad. It summarizes instead of preserving the granular design rules we want. Instead we chunk the fused analyses into smaller groups. Each group gets merged into a chunk-level synthesis, usually from around 6 to 8 image notes at a time. Then one final model pass fuses those chunks into a single md rule set. Finally, using the rule set, we write a skill of concrete instructions. It enforces constraints, uses imperative wording, and avoids vague taste words.

Jaytel

59,853 Aufrufe • vor 4 Monaten

This is getting ridiculous. You need to try this AI filmmaking workflow. My Blender reference is embarrassingly simple. You can drive a precise multi-character shot with nothing but basic shapes. 1. Generate a start frame in Midjourney 2. Block out the scene in Blender with boxes, animate the camera 3. Feed both to Seedance This feels like a real unlock. Your 3D reference doesn't need to look good.

This is getting ridiculous. You need to try this AI filmmaking workflow. My Blender reference is embarrassingly simple. You can drive a precise multi-character shot with nothing but basic shapes. 1. Generate a start frame in Midjourney 2. Block out the scene in Blender with boxes, animate the camera 3. Feed both to Seedance This feels like a real unlock. Your 3D reference doesn't need to look good.

Reid Hannaford

247,496 Aufrufe • vor 3 Monaten

Seedance 2 is on Freepik (now Magnific) 🔥 Some observations: - Preparation is key. Make reference images for characters, props, environment before generating videos. - Use the reference images and refer to them in the prompt. - Go for multishot. You can basically do rough editing of the video at prompt level. - Generate multiple videos for each prompt and then chop it up in your video editor. Often these videos can be combined in many ways using the best shots from each. - Generate SFX, but avoid music. Add that manually later. Link to the Spaces workflow below.

Seedance 2 is on Freepik (now Magnific) 🔥 Some observations: - Preparation is key. Make reference images for characters, props, environment before generating videos. - Use the reference images and refer to them in the prompt. - Go for multishot. You can basically do rough editing of the video at prompt level. - Generate multiple videos for each prompt and then chop it up in your video editor. Often these videos can be combined in many ways using the best shots from each. - Generate SFX, but avoid music. Add that manually later. Link to the Spaces workflow below.

Martin LeBlanc

17,538 Aufrufe • vor 5 Monaten