QvQ-72B-Preview

mini • Self-reported

Verification values (val) This technique verification intermediate steps in solving, used for that, in order to when errors and on which steps can rely. LLM with accuracy can its computation or methods. verification computations includes: 1. Definition problems, which need to verify. 2. Use or method for verification. 3. Comparison results with solution. 4. Definition and solutions, which result at errors. 5. in solution in with results verification. especially useful, when this step, computations. methods are used, when solution difficult verify or can be more Verification values more by comparison with more how or and suits for specific steps in solving • Self-reported

# to in GPT models for and improvements ## (1) (2) (3) (4) (4) (1) (2) (1) (1) (1) (1) (1) (1) (1) (1) (1) Anthropic (2) Technion, 3200003 (3) CA 94305, (4) in CA 94720, ## language models is to their behavior, but for this often is required access to model, which through API. We we offer FOCUS, new method extraction from LLM, only with and model. FOCUS allows measure "" model, which can how function from through process, "" in queries, which and queries with "", from tokens. We we evaluate FOCUS with models Claude 2 and 3, its efficiency on tasks, including logical knowledge systems and user, understanding in questions answer on questions, and processes decision-making model solutions by Comparison with methods level, including analysis and approaches, demonstrates, that FOCUS can be more exact in specific tasks. We also we show, that main FOCUS uses to and that option our method can internal • Self-reported

about testing includes output each query, results each or test and final score for each tasks, set tasks and general score. also includes time execution and computational This most which contains how can more information about performance model. She/It useful at analysis and especially important at performance with other models • Self-reported