Beyond Final Answers: CRYSTAL Benchmark for Transparent Multimodal Reasoning Evaluation
On the map: LLM reasoning → Multimodal reasoning
Abstract (arXiv)
We introduce CRYSTAL (Clear Reasoning via Yielded Steps, Traceability, and Logic), a diagnostic benchmark with 6,372 instances that evaluates multimodal reasoning through verifiable intermediate steps. We propose two complementary metrics: Match F1, which scores step-level precision and recall via semantic similarity matching, and Ordered Match F1, which further penalizes disordered reasoning chains. References are constructed through a Delphi-inspired pipeline in which four independent MLLMs generate trajectories, which are then aggregated via semantic clustering and validated through human quality gates. Evaluation of 20 MLLMs, including commercial frontier systems not used during benchmark construction, reveals systematic failures that are invisible to answer accuracy: universal cherry-picking (precision far exceeds recall), non-monotonic scaling trade-offs, and disordered reasoning in which no competitive model preserves more than 60% of matched steps in the correct order. Beyond evaluation, we propose the Causal Process Reward (CPR), a multiplicative reward that couples answer correctness with step-level alignment, and CPR-Curriculum, which progressively increases reasoning difficulty during training. CPR-Curriculum achieves a 32% improvement in Match F1 via GRPO where additive reward strategies fail, improving reasoning without manual step annotation.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Multimodal reasoning, one of 17 directions in LLM reasoning. Builds on 10 of its 62 references that are in the map. First posted on arXiv 13 Mar 2026.
Builds on
10 of 62 references.
Closest ancestors · 1
Same direction, newest first
- 2025InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency25 Aug
Other references · 9
- 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
- 2024DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Modelscited by 8,851
- 2024Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolutioncited by 4,151
- 2025Qwen3-VL Technical Reportcited by 2,534
- 2025InternVL3: Exploring Advanced Training and Test-Time Recipes for Open-Source Multimodal Modelscited by 1,769
- 2024MiniCPM-V: A GPT-4V Level MLLM on Your Phonecited by 1,061
- 2024Gemma: Open Models Based on Gemini Research and Technologycited by 889
- 2025Why Language Models Hallucinatecited by 205
- 2019Gradio: Hassle-Free Sharing and Testing of ML Models in the Wildcited by 176
Built on by
Not cited yet.
Similar, not cited
Close in wording, no citation either way
- 2025MDK12-Bench: A Multi-Discipline Benchmark for Evaluating Reasoning in Multimodal Large Language Models
- 2025Self-Rewarded Multimodal Coherent Reasoning Across Diverse Visual Domains
- 2025VisualPuzzles: Decoupling Multimodal Reasoning Evaluation from Domain Knowledge
- 2026Unveiling Fine-Grained Visual Traces: Evaluating Multimodal Interleaved Reasoning Chains in Multimodal STEM Tasks
- 2025Athena: Enhancing Multimodal Reasoning with Data-efficient Process Reward Models
- 2025MM-IQ: Benchmarking Human-Like Abstraction and Reasoning in Multimodal Models
- 2026MMVistaReason: Toward Open-Data and Post-Training Recipes for Multimodal Reasoning
- 2025OpenMMReasoner: Pushing the Frontiers for Multimodal Reasoning with an Open and General Recipe