Paper Database
Our research layer tracks papers from arXiv, NeurIPS, ICML, ICLR, and other sources, analyzing their impact on deployed models.Impact Levels
🔴 Revolutionary
🔴 Revolutionary
Paradigm-shifting work that redefines what’s possible
🟠 Significant
🟠 Significant
Major advancement with measurable improvements
🟡 Incremental
🟡 Incremental
Small but meaningful improvement
🟢 Validation
🟢 Validation
Confirms or reproduces existing work
⚪ Negative
⚪ Negative
Disproves or challenges existing claims
Browse Papers
Chain of Thought at Scale
Achieving human-level mathematical reasoning
Impact: Significant | Models: GPT-4o, Claude 3 Opus
Impact: Significant | Models: GPT-4o, Claude 3 Opus
All Papers
Browse complete paper database
Recent Discoveries
- 3 papers on reasoning improvements
- 2 papers on multimodal architectures
- 1 paper challenging existing benchmarks
Contributing Papers
Found a paper that impacts model performance? We track:- Direct model improvements - Papers that improve specific models
- Benchmark changes - New evaluation methods or datasets
- Architecture innovations - New techniques applicable across models
- Negative results - Papers that challenge existing assumptions
Papers are reviewed by our graduate research layer before publication