GoodPoint: LLM Constructive Paper Feedback
💡SOTA LLM for paper feedback: 83.7% gain, beats Gemini-3-flash (arXiv new)
⚡ 30-Second TL;DR
What Changed
Curated GoodPoint-ICLR dataset: 19K papers with dual-axis feedback annotations from author responses.
Why It Matters
Advances AI-assisted peer review, enabling better simulated feedback to accelerate research iteration and paper quality. Empowers researchers with actionable LLM tools without full automation.
What To Do Next
Download GoodPoint-ICLR dataset from arXiv and fine-tune your LLM for feedback generation.
Key Points
- •Curated GoodPoint-ICLR dataset: 19K papers with dual-axis feedback annotations from author responses.
- •GoodPoint training: fine-tuning on valid/actionable feedback + real/synthetic preference pairs.
- •Qwen3-8B gains 83.7% predicted success rate over base, tops Gemini-3-flash in precision.
- •New SOTA on 1.2K ICLR feedback benchmark, validated by expert human study.
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Original source: ArXiv AI ↗
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