Throughline

Trace research lineages through time using LLMs and semantic embeddings. Discover "spiritual successors" and same-lab work that traditional citation networks miss.

What It Does

ResearchRabbit's "related papers" feature misses obvious research lineages when there's no direct citation path. For example, searching from ViNT (2023) might miss NoMaD, LeLaN, and OmniVLA - all obvious successors from the same lab.

Throughline solves this by combining:

• Dual-strategy search: Both citations API (direct descendants) + recommendations API (semantic similarity)
• SPECTRE v2 embeddings (Semantic Scholar) for semantic paper discovery
• LLM-based ranking (Grok 4.1 Fast via OpenRouter) with full abstracts, authors, and citation counts
• Recursive expansion from seed papers → current year
• Sub-thread spawning when papers diverge into new research directions

Analysis runs in background - close the popup anytime and check back later.

Installation

1. Clone/download this repo
2. Chrome → chrome://extensions/ → Enable "Developer mode"
3. Click "Load unpacked" → Select the extension folder
4. Right-click extension icon → Options → Add your OpenRouter API key

Get OpenRouter key: https://openrouter.ai/keys (free tier available)

Usage

Basic Workflow

1. Go to ResearchRabbit → Switch to list view (not canvas)
2. Click "➕ Add to Throughline" on 1-3 seed papers
3. Click extension icon → "🔍 Trace throughlines"
4. Click "Run Analysis" (takes 2-5 minutes)
5. View threads sorted chronologically

During Analysis

• Progress bar shows current operation
• Live thread display shows threads being built in real-time
• Stop button (⏹) stops analysis gracefully and saves debug tree
• Analysis continues in background - safe to close popup

After Analysis

• Click paper titles to open in Semantic Scholar
• Download Debug Tree to see decision-making process
• View all discovered threads and papers

How It Works

For Each Seed Paper:

1. Theme Extraction: LLM identifies 2-3 core research themes
2. Thread Creation: Each theme becomes a separate research thread
3. Paper Discovery (dual strategy):
   • Fetch papers that cite the seed (direct descendants)
   • Fetch semantically similar papers via SPECTRE embeddings
   • Merge and deduplicate (330+ candidates typical)
4. Quality Filtering:
   • Remove papers 3+ years old with <5 citations
   • Keep recent papers (≤2 years) regardless of citations
5. LLM Ranking:
   • Provide full abstracts, authors, citation counts
   • LLM ranks papers by relevance to thread theme
   • Helps identify same-lab work and conceptual connections
6. Thread Expansion:
   • LLM selects papers to add (same authors/lab = strongest signal)
   • Check if paper spawns new sub-threads
   • Recurse until reaching current year or thread exhausted
7. Sub-thread Detection:
   • LLM analyzes each paper for new research directions
   • Spawns sub-threads for significant divergences

Example Thread Evolution:

Thread: Development of ViNT as a Transformer-based foundation...
  ├─ ViNT: A Foundation Model for Visual Navigation (2023)
  ├─ NoMaD: Goal Masked Diffusion Policies... (2023)
  │  └─ Sub-thread: Unified diffusion policy for goal-directed navigation...
  │     ├─ LeLaN: Learning A Language-Conditioned Navigation... (2024)
  │     └─ OmniVLA: An Omni-Modal Vision-Language-Action... (2025)
  └─ ...continues to 2026

Understanding Results

Thread Display

• Theme: LLM-generated description of research direction
• Papers: Chronological list with year, title, authors, citations
• Sub-threads: Indented threads showing research divergence
• Links: Click titles to open in Semantic Scholar

Quality Indicators

• Citation count: Shows paper impact
• Author overlap: Helps identify same-lab work
• Year progression: Shows research evolution over time

Debug Tree

Download the debug tree to see:

• Which papers were considered at each step
• How the LLM ranked candidates
• Why specific papers were selected
• All current threads at any point in time
• Search statistics (citing vs recommended papers)

Example debug tree entry:

[5] SELECT_DECISIONS: LLM selected 2 of 10 candidates
    LLM decisions:
      ✓ ADD: NoMaD: Goal Masked Diffusion Policies...
          Reason: Same authors (Shah), direct follow-up extending ViNT
      ✗ SKIP: Navigation with Large Language Models...
          Reason: Uses LLMs for planning, unrelated architecture

Technical Details

Search Strategy

1. Citations API: Papers that cite the seed (direct descendants)
2. Recommendations API: Semantically similar via SPECTRE v2
3. Merge: Deduplicate papers appearing in both
4. Filter: Quality filter removes old low-impact papers
5. Rank: LLM with full context selects most relevant

Rate Limits

• Semantic Scholar: 1 req/sec (unauthorized API)
• OpenRouter: Depends on your tier
• Built-in retry logic for 429 errors

Limits (Configurable)

• Max 10 threads per analysis
• Max 20 papers per thread
• Prompts ~150-500KB for ranking (large context windows)

Error Handling

• LLM parse errors: Automatic self-correction retry
• Rate limiting: Exponential backoff up to 20s, then hard failure
• Malformed responses: Debug tree captures for analysis
• Stop button: Graceful termination with debug tree save

Storage

• Uses Chrome local storage
• Papers stored with: title, authors, abstract, year, citations, paperId
• Debug tree saved for every analysis
• All data stored locally (no external sync)

Development

File Structure

throughline-extension/
├── manifest.json          # Extension config
├── background.js          # Core analysis logic (ThroughlineAnalyzer)
├── content.js            # ResearchRabbit page injection
├── popup.html/js         # Extension popup UI
├── config.html           # Options page for API key
└── README.md            # This file

Key Classes

• ThroughlineAnalyzer: Main analysis engine
  • analyze(): Entry point
  • processSeedPaper(): Extract themes and start threads
  • expandThread(): Recursive thread expansion
  • findRelatedPapers(): Dual-strategy search
  • rankPapers(): LLM ranking with full context
  • checkForSubThreads(): Detect research divergence

Debug Logging

Set DEBUG_ENABLED = true in background.js for verbose console logs.