Papers2

#Hallucination Mitigation

From Blind Spots to Gains: Diagnostic-Driven Iterative Training for Large Multimodal Models

Hongrui Jia, Chaoya Jiang et al.Feb 26arXiv

Large multimodal models (LMMs) can look at pictures and read text, but they still miss tricky cases, like tiny chart labels or multi-step math.

#Large Multimodal Models#Diagnostic-driven Progressive Evolution#Reinforcement Learning

QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation

Intermediate

Dehai Min, Kailin Zhang et al.Dec 22arXiv

QuCo-RAG is a new way to decide when an AI should look things up while it writes, using facts from its training data instead of its own shaky confidence.

#Dynamic RAG#Retrieval-Augmented Generation#Uncertainty Quantification