Term #2,271
Training objective
Claim Term
Training objective
Origin matter
A method for screening manuscripts
Reference Case 1
BRT_PAT-2-PROV
Date Added
7/15/25
Created
7/15/25, 5:00 PM
Modified
1/7/26, 7:29 PM
Full Desc
"Training objective" refers to a defined goal, criterion, or set of conditions used to guide the learning process of an artificial intelligence model, machine learning system, or neural network during training. Synonyms for “training objective” may include optimization goal, learning criterion, loss function target, model supervision directive, or the like. The training objective may quantify how well the model performs a task and may direct the adjustment of model parameters to minimize or maximize a defined measure of performance. In some embodiments, the training objective may incorporate one or more performance metrics, similarity comparisons, classification accuracy measures, or quality-based evaluations.
In the context of editorial content generation, the training objective may include comparing a machine-generated editorial comment for a manuscript to a human-generated editorial comment for the same manuscript using a similarity metric such as cosine similarity, thereby encouraging the model to produce outputs that align semantically with human-provided output. The training objective may also include additional components such as language fluency, coherence, informativeness, or compliance with editorial guidelines. The training objective may be used in supervised, semi-supervised, or reinforcement learning workflows and may be updated or tuned over time to reflect evolving editorial standards, reviewer preferences, or corpus characteristics.
In certain embodiments, a composite training objective may be employed. A composite training objective refers to a training objective that includes two or more individual objective components that are optimized jointly, such as a combination of classification accuracy, semantic similarity, language quality, or rule-based compliance. The individual components of a composite training objective may be combined through weighting, aggregation, or other optimization strategies, and may be adjusted over time to balance competing editorial goals or performance considerations.
Applications using this term
| Matter | Usage | Notes | Actions |
|---|---|---|---|
| BRT-PAT-2-PROV | Defined | — | App terms |