github / Research & data
jev-dimabsa
AI-assisted summaries and translations. Check original sources for context and performance claims.
This project demonstrates a classification-only approach to dimensional aspect-based sentiment analysis using Jev primitives. It achieves state-of-the-art results on the SemEval-2026 Task 1 micro-aggregate without text generation, fine-tuning, or GPU acceleration, relying instead on stratified few-shot examples and joint calibration.
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This is a linked resource, not an independent verification of performance, cost or results. Check the original for current details.
- Collected
- 2026-09-24
- Discovered via
- awesomejev.com
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