📊 LLM Evaluation¶

🎞️ ECCV2026 · 2 paper notes

SVGEval: A Vision-Grounded Framework for Perceptual-Quality Benchmarking and Evaluation in Text-to-SVG Generation: SVGEval moves the evaluation target of text-to-SVG from the SVG code to the rendered outcome that users actually see: it builds a 500-instance binary-diagnosis plus 500-instance 1–5 scoring benchmark over a four-dimension rubric (Aesthetic, Semantic, Spatial, Structural) with multi-round human annotation and expert adjudication, then distills an explainable scorer that reads both the rendering and the code and outputs dimension-wise scores with evidence-grounded rationales — cutting MAE from 0.71 (best general model) to 0.58 and lifting ±1 adjacent accuracy from 66.6% to 72.0%.
LASER: A Corrective Lens for LVLMs via Visual Attention Preservation and Sink Suppression: To tackle visual forgetting and attention sink collapse during long-horizon reasoning in LVLMs, LASER introduces a GRPO-based post-training framework that pairs a visual grounding reward with a sink suppression reward, simultaneously regulating temporal attention decay and spatial intra-visual allocation to boost multimodal reasoning and perceptual grounding.