ConRetroBert achieves 62.4% top-1 accuracy on USPTO-50k by combining contrastive pretraining, hard-negative listwise ranking, and EMA-stabilized dual encoders for template retrieval in retrosynthesis.
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PlantMarkerBench supplies 5,550 literature sentences annotated for plant marker gene evidence validity and type across Arabidopsis, maize, rice and tomato, showing frontier LLMs handle direct expression evidence but struggle with functional, indirect and weak-support cases.
NV-Embed achieves first place on the MTEB leaderboard across 56 tasks by combining a latent attention layer, causal-mask removal, two-stage contrastive training, and data curation for LLM-based embedding models.
citing papers explorer
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ConRetroBert: EMA Stabilized Dual Encoders for Template-Based Single-Step Retrosynthesis
ConRetroBert achieves 62.4% top-1 accuracy on USPTO-50k by combining contrastive pretraining, hard-negative listwise ranking, and EMA-stabilized dual encoders for template retrieval in retrosynthesis.
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PlantMarkerBench: A Multi-Species Benchmark for Evidence-Grounded Plant Marker Reasoning
PlantMarkerBench supplies 5,550 literature sentences annotated for plant marker gene evidence validity and type across Arabidopsis, maize, rice and tomato, showing frontier LLMs handle direct expression evidence but struggle with functional, indirect and weak-support cases.
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NV-Embed: Improved Techniques for Training LLMs as Generalist Embedding Models
NV-Embed achieves first place on the MTEB leaderboard across 56 tasks by combining a latent attention layer, causal-mask removal, two-stage contrastive training, and data curation for LLM-based embedding models.