Researchers introduced HANIA, a planner-guided multimodal graph framework for evidence-grounded question answering, which uses a frozen vision-language model and a two-group finite-state planner to se…
Researchers introduced GraphLoom, a reliability-calibrated multimodal knowledge-graph retrieval-augmented generation framework that improves answer quality and evidence faithfulness by routing compact…
Researchers propose Visual Saliency Steering Distillation (VSSD) to improve multimodal chain-of-thought reasoning in small models by using attention maps from multimodal large language models to gener…
A new conformal prediction framework called Scientific Feasibility Control (SFC) achieves 50.1% accuracy on the PhyX physics reasoning benchmark, outperforming DeepSeek-R1 (49.8%) and GPT-4 (45.8%), w…
Researchers introduced CaVe-VLM-CoT, a modular reflection-based agentic-RAG framework that enforces evidence-grounded reasoning in vision-language models through a five-stage closed-loop pipeline. The…