#multimodal large language models
Multimodal Large Language Models: 6 AI articles covering multimodal large language models news, analysis, and research
Articles
SLVR: Structured Latent Visual Reasoning via Human-like⭐9
SLVR structures multimodal latent reasoning into typed stages—planning, grounding, evidence selection, integration—cutting textual chain-of-thought cost while i...
PalmLeaf-VQA: A Multi-Script Visual Question Answering Benchmark⭐8
PalmLeaf-VQA introduces a 7,384-question benchmark across eight South and Southeast Asian scripts, revealing that leading multimodal LLMs reach only 58% accurac...
MechReason: A New Benchmark for Multi-Image, Multi-Hop Reasoning⭐8
MechReason, a 12k-question benchmark from real mechanical engineering papers, tests multi-image, multi-hop reasoning in MLLMs across explanation, prediction, de...
Unified Hallucination Fuzzing for Multimodal Large Language Models⭐10
Unified fuzzing framework reveals severe hallucination risks in MLLMs, exposing hidden performance degradation and alignment trade-offs.
Adversarial Style Optimization: Enhancing VLM Jailbreaks by⭐7
ASO enhances visual jailbreak attacks on multimodal LLMs by optimizing stylistic triggers via GRPO, achieving higher Attack Success Rates and exposing stylistic...
Securing Multimodal AI through Internal Information Decomposition⭐8
FlowGuard detects harmful multimodal inputs by monitoring cross-modal consistency, reducing attack success rates from >90% to <15% with minimal utility loss.