graph-based

TIGER is an inference-time framework that mitigates hallucinations in multimodal generation by extracting observation and claim graphs and assigning risk scores to repair unsupported facts. It reduces unsupported content across image-to-text, image+text-to-text, audio-to-text, and video-to-text tasks.

PropGuard is a propagation-aware framework for safeguarding LLM-based multi-agent systems (LLM-MAS) from malicious instructions that propagate across agents and rounds. It constructs a dual-view spatio-temporal graph and uses a GE-GRPO trained inspector to detect and remediate suspicious propagation subgraphs.

GraphBit is a graph-based agentic framework that uses deterministic DAG orchestration with a Rust engine to eliminate hallucinations and infinite loops. It achieves 67.6% accuracy on GAIA benchmarks with zero framework-induced errors and low latency.

Researchers from the University of British Columbia propose an unsupervised graph-based system for organizing arguments from online debates by constructing interaction graphs and applying community detection to reveal diverse viewpoint distributions. The approach requires no training data and aims to help users navigate complex argumentative landscapes and combat filter bubbles.