Apple Research Proposes Rubric-Based Method for Training Agents Across Multiple Environments
Apple researchers, with National University of Singapore collaborators, published a paper on RISED, a new training framework for LLM agents that must learn across many different interactive environments at once. Instead of relying only on scalar reward signals, RISED uses an LLM judge to tag each training rollout with rubrics describing its behaviour, then uses these rubric tags to select training data and to supply extra supervision. The authors report RISED achieves the highest average success rate across environments compared to existing approaches, ranking first or second in every tested environment.