Papers by Hongshuai Wang

2 papers
NOSE: Neural Olfactory-Semantic Embedding with Tri-Modal Orthogonal Contrastive Learning (2026.acl-long)

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Challenge: Existing representation methods fail to fully capture olfactory pathway . current approaches focus on isolated segments of the olefactory pathways .
Approach: They propose a representation learning framework that aligns molecular structure, receptor sequence, and natural language description.
Outcome: The proposed framework achieves state-of-the-art and excellent zero-shot generalization . it decouples contributions of molecular structure, receptor sequence, and natural language description .
SciAssess: Benchmarking LLM Proficiency in Scientific Literature Analysis (2025.findings-naacl)

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Challenge: Existing benchmarks fail to adequately evaluate the proficiency of Large Language Models (LLMs) Existing standards do not cover the skills needed to evaluate LLMs in scientific literature analysis.
Approach: They propose a benchmark to evaluate the proficiency of large language models in scientific literature analysis.
Outcome: SciAssess evaluates 11 LLMs on multiple tasks across scientific fields.

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