An Explicit Logic Channel of LLM, VFM and probabilistic inference validates and improves zero-shot MLLMs via Consistency Rate without ground-truth labels.
In: Proceedings of the IEEE conference on computer vision and pattern recognition
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
years
2026 3representative citing papers
EGM enables 8B VLMs to reach 91.4 IoU on RefCOCO at 737 ms latency, outperforming a 235B model at 4320 ms, by substituting volume of mid-quality tokens for model scale.
citing papers explorer
-
Explicit Logic Channel for Validation and Enhancement of MLLMs on Zero-Shot Tasks
An Explicit Logic Channel of LLM, VFM and probabilistic inference validates and improves zero-shot MLLMs via Consistency Rate without ground-truth labels.
-
EGM: Efficient Visual Grounding Language Models
EGM enables 8B VLMs to reach 91.4 IoU on RefCOCO at 737 ms latency, outperforming a 235B model at 4320 ms, by substituting volume of mid-quality tokens for model scale.
- Tarot-SAM3: Training-free SAM3 for Any Referring Expression Segmentation