Local Ai
Localize, Then Reason: Visual Latent Structural Reasoning for Molecular Properties and Edits
arXiv:2608.13244v1 Announce Type: new Abstract: Local chemical perception and property reasoning are both essential for understanding how molecular structure determines properties. Current LLM-based c
arXiv:2608.13244v1 Announce Type: new Abstract: Local chemical perception and property reasoning are both essential for understanding how molecular structure determines properties. Current LLM-based chemical reasoning methods either receive SMILES/molecular images together with descriptions of local motifs, or reason directly from molecular images. Neither approach enables the model to focus on chemically meaningful regions before reasoning. To address this gap, we propose Visual Latent Structural Reasoning (VLSR), an end-to-end framework that jointly learns localization and reasoning from molecular images. Central to our approach is a localize-then-reason strategy. VLSR first learns to locate chemically meaningful regions in a molecular image. It then reasons about their property effects in a compact latent workspace before producing the final answer. Under the same inference setup, this design achieves 9.6X higher throughput than a comparable textual-reasoning baseline.
Related
- Perception Before Reasoning: Dynamic Latent Reasoning for Video Understanding and Question Answering
- Forest Before Trees: Latent Superposition for Efficient Visual Reasoning
- Energy-Based Constraint Networks: Learning Structural Coherence Across Modalities
Source: arXiv cs.CL | 2026-08-14