THPL: Vision-to-language framework for rainbow trout feeding decisions in RAS
This arXiv preprint (arXiv:2610.02378v1) introduces THPL, a vision-to-language decision-support framework for precision feeding of rainbow trout in Recirculating Aquaculture Systems. The method extracts trajectories with Fishsort to compute an Activity Coefficient (AC), encodes temporal and group dynamics with a Hierarchical Behavior Encoder using Temporal and Set Transformers to produce dual 'physical' and 'soft' tokens, and fine-tunes an LLM with LoRA plus counterfactual multimodal Direct Preference Optimization (mDPO); reported results show strong correlation of AC with expert feeding intensity (Spearman ρ = 0.925, p < 0.001) and decision accuracy improvements from 33.33% (text-only) to 93.33% (with dual-evidence tokens) and to 96.67% after mDPO, along with gains in METEOR and diversity metrics.