Comparative study: FISER vs. CEMIR for pragmatic intent recognition
This arXiv study benchmarks FISER (structured social/embodied reasoning) against CEMIR (context-enriched multimodal intent recognition that synthesizes narratives and photorealistic images) across four LLM backbones, from Qwen2.5-Omni-3B to GPT-5, on the HandMeThat v2 benchmark. Using multiple-comparison-corrected statistics and ablations isolating narrative and visual components, the authors find no statistically significant performance difference between the two approaches; performance correlates mainly with backbone capability and problem difficulty.