Introducing Smart Collections - Intelligent Paper Organization

We're excited to announce Smart Collections—a powerful new feature that transforms how you organize research papers in GeminiPaper.

Traditional folders force you to choose: which single category does this paper belong to? But research papers don't fit into neat boxes. A paper might be relevant to your PhD thesis, use an interesting methodology, and relate to your teaching—all at once.

Smart Collections solve this with AI-powered, multi-dimensional organization that adapts to how you actually work.

What Are Smart Collections?

Smart Collections are intelligent, dynamic groups of papers that update automatically based on rules you define.

Traditional Folders vs. Smart Collections

Traditional approach:

• Manual assignment to one folder
• Papers can't belong to multiple folders
• Static—doesn't update as library grows
• Requires constant maintenance

Smart Collections approach:

• Automatic categorization by multiple criteria
• Papers can belong to many collections
• Dynamic—updates as you add papers
• Maintains itself with AI

Real-World Example

Sarah is a PhD student studying machine learning in healthcare. With traditional folders:

Papers/
├── Thesis/
├── Methods/
└── Teaching/

Problem: Where does "Deep Learning for Medical Imaging" go? It's relevant to all three!

With Smart Collections:

Collection 1: "Thesis Papers"

• Auto-includes: Papers tagged "thesis" OR "healthcare-ml"
• Updates: Automatically adds relevant new papers

Collection 2: "Interesting Methods"

• Auto-includes: Papers with "deep learning" OR "neural networks" in title
• Updates: Catches methodology papers automatically

Collection 3: "Teaching Examples"

• Auto-includes: Papers marked 5-stars OR tagged "teach"
• Updates: Grows as Sarah rates papers

One paper can appear in all three collections. No duplicates, no decisions, no maintenance.

Key Features

1. AI-Powered Auto-Categorization

When you upload papers, AI analyzes:

• Content: Main topics and themes
• Methodology: Research approaches used
• Field: Academic discipline
• Type: Review, empirical study, meta-analysis, etc.

Then automatically suggests collections and applies rules.

Example: Upload a paper on "Transformer Models for Clinical Notes"

AI detects:

• Topic: NLP, Healthcare
• Method: Deep Learning, Transformers
• Field: Medical Informatics
• Type: Empirical Study

Automatically adds to:

• "NLP Research" collection
• "Deep Learning Methods" collection
• "Healthcare Applications" collection

2. Smart Rules Engine

Create sophisticated rules without coding:

Simple rules:

• All papers by author "Smith"
• Papers published after 2020
• Papers with status "Reading"

Complex rules:

• (Machine Learning OR AI) AND Healthcare
• Papers with >100 citations AND published in top journals
• Papers tagged "important" AND not yet cited in my work

Dynamic rules:

• Papers similar to [specific paper]
• Papers recommended based on my reading history
• Papers citing or cited by papers in this collection

3. Nested Collections

Organize collections hierarchically:

Machine Learning/
├── Deep Learning/
│   ├── CNNs/
│   ├── Transformers/
│   └── GANs/
├── Traditional ML/
└── Reinforcement Learning/

Papers in "Transformers" automatically appear in parent collections too.

4. Collection Views

Each collection can have custom views:

List view: Compact, sortable Grid view: Visual with previews Timeline view: Chronological Network view: Citation relationships Comparison view: Side-by-side analysis

5. Smart Recommendations

AI suggests:

• New collections based on your library
• Papers to add to existing collections
• Related collections from other users (with permission)
• Optimal collection structures

How to Use Smart Collections

Creating Your First Smart Collection

Step 1: Create collection

1. Click "New Collection"
2. Name it (e.g., "PhD Literature Review")
3. Choose icon and color
4. Add description

Step 2: Define rules

1. Click "Add Rule"
2. Choose criteria:
   • Tags contain "thesis"
   • Status is "Reading" or "Completed"
   • Publication date after 2020
3. Set logic: AND/OR
4. Save rules

Step 3: Let AI populate AI scans your library and adds matching papers automatically.

Step 4: Refine Review suggested papers, adjust rules if needed.

Best Practices

Start broad, then narrow:

1. Create high-level collections first (e.g., "All ML Papers")
2. Add subcollections for specifics (e.g., "NLP", "Computer Vision")
3. Use AI suggestions to discover patterns

Use multiple criteria: Don't rely on single rules. Combine:

• Tags + Status
• Authors + Keywords
• Date range + Citation count
• Your ratings + AI confidence

Regular review:

• Weekly: Check new papers added automatically
• Monthly: Refine rules based on usage
• Quarterly: Reorganize collection structure

Descriptive names:

• "PhD Thesis - Methods Section" ✅
• "Important" ❌
• "Papers for Grant Proposal 2024" ✅
• "Misc" ❌

Advanced Techniques

Time-based collections: Create collections for:

• "This Week's Reading"
• "Papers to Cite This Month"
• "New Papers in My Field"

Project lifecycle collections:

• "Project X - Planning"
• "Project X - Active"
• "Project X - Writing"
• "Project X - Archived"

Quality-based collections:

• "Highly Cited (>500)"
• "Top Journals Only"
• "Seminal Works"
• "Recent Breakthroughs"

Use Cases

For PhD Students

Sarah's Thesis Collections:

• "Core Literature" - 40 essential papers
• "Methodology References" - Methods to cite
• "Results Comparison" - Papers to compare with
• "Discussion Points" - Papers addressing similar questions
• "Supplementary" - Background and context

All update automatically as she adds papers.

For Academic Researchers

Dr. Chen's Research Program:

• "Current Project Papers" - Active research
• "Grant Proposal References" - For funding applications
• "Collaboration Papers" - Shared with team
• "Future Directions" - Ideas for next projects
• "Teaching Examples" - Papers for courses

Smart rules ensure papers flow to right collections.

For Research Teams

Lab Collections:

• "Lab Publications" - All team outputs
• "New Team Members Reading List" - Onboarding papers
• "Methods We Use" - Methodological papers
• "Competing Labs" - Papers from competitors
• "Industry Collaborations" - Applied research

Shared collections keep team aligned.

Migration from Folders

Already have folder-based organization? Easy migration:

Step 1: Map Folders to Collections

For each folder, create equivalent collection:

• Folder: "Machine Learning"
• Collection: "Machine Learning Research"

Step 2: Import Papers

Drag papers from folder into collection, or:

• Bulk import all papers from folder
• Let AI tag them
• AI creates Smart Collection rules automatically

Step 3: Add Smart Rules

Enhance manual collections with rules:

• Original: Manual folder assignment
• Enhanced: Auto-includes papers with specific tags
• Result: Collection maintains itself

Step 4: Archive Folders

Once Smart Collections work well:

• Keep folders as backup (temporarily)
• Switch primary workflow to collections
• Eventually delete old folder structure

Integration with Other Features

Smart Collections work seamlessly with:

Search:

• Search within specific collection
• Find papers across collections
• Save searches as new collections

AI Understanding:

• Bulk summarize all papers in collection
• Compare papers within collection
• Find themes across collection

Projects:

• Link collections to projects
• Auto-add collection papers to project
• Export collection as project bibliography

Tags:

• Use tags in collection rules
• Auto-tag papers in collections
• Sync tags across collections

Tips for Power Users

Automated Workflows

Reading workflow:

1. New papers → "Inbox" collection
2. AI suggests relevant collections
3. After reading → Auto-moves to "Read" collection
4. High-rated papers → "Favorites" collection

Writing workflow:

1. Working on paper → Create "Paper Draft" collection
2. AI suggests relevant papers to cite
3. Cited papers → Auto-tagged
4. After publication → Move to "My Publications"

Collection Templates

Save collection structures as templates:

Literature Review Template:

• Foundational Papers
• Methodology Papers
• Recent Advances
• Critiques and Limitations
• Future Directions

Apply to new projects instantly.

Bulk Operations

Perform actions on entire collections:

• Bulk export citations
• Batch summarize with AI
• Mass tag or retag
• Export all PDFs

Smart Notifications

Get notified when:

• New papers match collection rules
• Collection reaches milestone (e.g., 100 papers)
• Highly-cited paper added
• Collaborator adds papers

Pricing and Availability

Smart Collections are available now on all plans:

Free Plan:

• 5 Smart Collections
• Basic rules
• Manual updates

Pro Plan ($12/month):

• Unlimited Smart Collections
• Advanced rules with AI
• Automatic updates
• Collection templates

Team Plan ($29/month/user):

• Everything in Pro
• Shared collections
• Team templates
• Priority AI processing

What Users Are Saying

Getting Started

Ready to try Smart Collections?

1. Update GeminiPaper - Feature available in latest version
2. Watch tutorial - 5-minute video walkthrough
3. Import papers - Upload your first papers
4. Create collection - Start with one simple collection
5. Let AI help - Accept AI suggestions for rules

Visit GeminiPaper Smart Collections Guide for detailed documentation.

What's Next

We're constantly improving Smart Collections. Coming soon:

• Visual rule builder - Drag-and-drop rule creation
• AI-suggested structures - Optimal collection organization
• Cross-library search - Find papers across multiple users
• Collection analytics - Insights into your research patterns
• Mobile app - Manage collections on the go

Learn More

• Smart Collections Documentation

Transform your research organization today with Smart Collections. Try GeminiPaper free.