| name | openreview-explorer |
| description | Search papers on OpenReview and retrieve peer reviews and rebuttals from major ML conferences (ICLR, NeurIPS, ICML). Core skill for FrontierPilot's Knowledge Exploration engine. |
| version | 1.0.0 |
OpenReview Explorer
This skill fetches papers, peer reviews, and author rebuttals from OpenReview — treating the review process as structured learning material for newcomers entering a research field.
Why Reviews Matter
Peer reviews reveal what the field actually cares about: common weaknesses, evaluation standards, and how top authors respond to criticism. This is knowledge that takes years to accumulate informally — FrontierPilot surfaces it directly.
Python Interpreter
Always use: python3 (available in the OpenClaw container environment)
Capabilities
1. Search papers by keyword + venue
python3 /home/node/.openclaw/workspace/skills/openreview-explorer/scripts/search_papers.py \
--query "automl" \
--venue "ICLR" \
--year 2024 \
--limit 5
2. Get reviews + rebuttal for a paper
python3 /home/node/.openclaw/workspace/skills/openreview-explorer/scripts/get_reviews.py \
--forum-id <FORUM_ID> \
--venue "ICLR" \
--year 2024
3. Get conference papers (all from a venue/year)
python3 /home/node/.openclaw/workspace/skills/openreview-explorer/scripts/search_papers.py \
--venue "ICLR" \
--year 2024 \
--limit 10
Workflow for Knowledge Exploration
- User provides a topic (e.g., "diffusion models for image generation")
- Run
search_papers.py to find top relevant papers from recent ICLR/NeurIPS/ICML
- For each promising paper, run
get_reviews.py to retrieve:
- Reviewer ratings and summaries
- Detailed strengths/weaknesses
- Author rebuttal (how the authors defended their work)
- Synthesize: What do reviewers consistently praise? What weaknesses appear? What does the rebuttal reveal about the authors' intent?
- Save synthesis to
memory/RESEARCH_LOG.md
Output Format
Papers are returned as JSON. Present them as:
- Title, authors, venue, year
- Abstract excerpt
- Forum ID (needed for get_reviews.py)
Reviews are returned with:
- Rating (e.g., "8: accept, good paper")
- Summary, strengths, weaknesses
- Confidence score
- Rebuttal excerpt
Environment Variables
The scripts read credentials from environment variables. Set them before use:
OPENREVIEW_USERNAME: your OpenReview account emailOPENREVIEW_PASSWORD: your OpenReview account passwordOPENREVIEW_BASE_URL: https://api2.openreview.net (default, usually no need to set)
Supported Venues
| Venue | Invitation Pattern |
|---|
| ICLR 2024 | ICLR.cc/2024/Conference/-/Submission |
| ICLR 2023 | ICLR.cc/2023/Conference/-/Submission |
| NeurIPS 2024 | NeurIPS.cc/2024/Conference/-/Submission |
| ICML 2024 | ICML.cc/2024/Conference/-/Submission |
Error Handling
- If a paper has no reviews yet (e.g., under review), the script returns an empty list — note this to the user
- Rate limit: space out requests for large batches (>20 papers)
- If login fails, fall back to anonymous mode (public papers only, no reviews)
