pith:MTQBGLQE
Beyond Cosine Similarity: Zero-Initialized Residual Complex Projection for Aspect-Based Sentiment Analysis
Projecting ABSA features into complex space via zero-initialized residuals separates opposing polarities by phase.
arxiv:2603.28205 v2 · 2026-03-30 · cs.CL
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Claims
Our framework achieves a state-of-the-art Macro-F1 score of 0.8923 on the ASAP dataset, outperforming robust baselines by projecting textual features into a complex semantic space and using an anti-collision mask to expand the discriminative margin between opposing polarities.
That mapping features to complex space via zero-initialized residual projection plus the masked angle loss will reliably isolate polarities and generalize beyond the ASAP dataset without introducing new representation artifacts or requiring extensive hyperparameter tuning.
Zero-Initialized Residual Complex Projection with anti-collision masked angle loss reaches 0.8923 Macro-F1 on the ASAP dataset for aspect-based sentiment analysis.
References
Receipt and verification
| First computed | 2026-05-17T23:39:15.636083Z |
|---|---|
| Builder | pith-number-builder-2026-05-17-v1 |
| Signature | Pith Ed25519
(pith-v1-2026-05) · public key |
| Schema | pith-number/v1.0 |
Canonical hash
64e0132e041ee025c6eb12f961c4999c7e4d6632e26f5dc7fa6cc99ad19c1f08
Aliases
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Verify this Pith Number yourself
curl -sH 'Accept: application/ld+json' https://pith.science/pith/MTQBGLQED3QCLRXLCL4WDREZTR \
| jq -c '.canonical_record' \
| python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: 64e0132e041ee025c6eb12f961c4999c7e4d6632e26f5dc7fa6cc99ad19c1f08
Canonical record JSON
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