PRISM-VLM: A Multi-Axis Discriminative Benchmark for Compact Vision-Language Models

arXiv:2609.27395 · cs.CL · Submitted 2026-09-23 · Read on arXiv

cs.CL

Submitted: 2026-09-23

Updated: 2026-09-23

Comments: Accepted to EMNLP 2026 Findings. 29 pages, 22 figures, 21 tables

Code: https://github.com/naver-ai/prism-vlm

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 86× in this paper · explained in 2 episodes
• Core — 81× in this paper · explained in 2 episodes
• Sycophancy — 36× in this paper · explained in 4 episodes
• Accuracy — 18× in this paper · explained in 1 episode
• Hallucination — 16× in this paper · explained in 3 episodes
• Robustness — 12× in this paper · explained in 5 episodes
• Failure Modes — 6× in this paper · explained in 3 episodes
• Grounding — 6× in this paper · explained in 3 episodes
• Conference on Computer Vision and Pattern Recognition — 3× in this paper
• LLM judge — 3× in this paper · explained in 2 episodes
• Aggregation — 2× in this paper · explained in 1 episode
• Empirical Methods in Natural Language Processing — 2× in this paper
• Meeting of the Association for Computational Linguistics — 2× in this paper
• Vision-Language Models (VLMs) — 2× in this paper · explained in 6 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Benchmarking — 1× in this paper · explained in 3 episodes
• Calibration — 1× in this paper · explained in 7 episodes
• Foundation Model — 1× in this paper · explained in 3 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• In European Conference on Computer Vision — 1× in this paper
• Instruction Tuning — 1× in this paper · explained in 2 episodes
• International Conference on Learning Representations — 1× in this paper
• LLM-as-a-Judge — 1× in this paper · explained in 3 episodes
• Multimodal Reasoning — 1× in this paper · explained in 5 episodes
• Trace — 1× in this paper · explained in 2 episodes

Sources

• Qwen3-VL Technical Report
• Molmo2: Open Weights and Data for Vision-Language Models with Video Understanding and Grounding
• Gemma 3 Technical Report
• A Survey on Benchmarks of Multimodal Large Language Models
• A Survey on Hallucination in Large Vision-Language Models
• InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency
• DeepSeek-VL2: Mixture-of-Experts Vision-Language Models for Advanced Multimodal Understanding
• MiniCPM-V: A GPT-4V Level MLLM on Your Phone
• EchoBench: Benchmarking Sycophancy in Medical Large Vision-Language Models
• Instruction-Following Evaluation for Large Language Models

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