Most RAG systems don’t understand sophisticated documents — they shred them

Standard RAG pipelines treat documents as flat strings of text. They use "fixed-size chunking" (cutting a document every 500 ...
GitHub

OCR-Reasoning Benchmark: Unveiling the True Capabilities of MLLMs in Complex Text-Rich ...

Recent advancements in multimodal slow-thinking systems have demonstrated remarkable performance across diverse visual reasoning tasks. However, their capabilities in text-rich image reasoning tasks ...
IEEE

LogiCode: An LLM-Driven Framework for Logical Anomaly Detection

Abstract: This paper presents LogiCode, a novel framework that leverages Large Language Models (LLMs) for identifying logical anomalies in industrial settings, moving beyond the traditional focus on ...
Frontiers

Fostering effective hybrid human-LLM reasoning and decision making

The impressive performance of modern Large Language Models (LLMs) across a wide range of tasks, along with their often non-trivial errors, has garnered unprecedented attention regarding the potential ...
IEEE

Logical Rules Enhanced Multimodal Reasoning Based on Biomedical Knowledge Graph

Abstract: Biomedical knowledge graph reasoning is capable of discovering hidden new knowledge based on existing biomedical data, providing ideas and references for new drug discovery, disease research ...