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Zigan Wang

2 accepted papers

2026

ViG-RAG: Video-aware Graph Retrieval-Augmented Generation via Temporal and Semantic Hybrid Reasoning

AAAI 2026technical

Retrieval-augmented generation (RAG) has greatly improved Large Language Models (LLMs) by adding external knowledge. However, current RAG-based methods face difficulties with long-context video understanding due to two main challenges. First, Current RAG-based methods for long-context video understa

Cited by 0SourcePDFScholar
2026

VideoTrace-R1: Long Video-based Retrieval-Augmented Generation via Temporal Path Graph Understanding

ICML 2026poster

Long-video temporal reasoning remains challenging for Large Video Language Models (LVLMs). Recent reasoning-enhanced models apply reinforcement learning with outcome supervision to improve temporal understanding. However, outcome-only rewards cannot distinguish whether a model arrived at the correct…

Cited by 0SourceScholar