Papers by Honghao Fu

3 papers
VistaWise: Building Cost-Effective Agent with Cross-Modal Knowledge Graph for Minecraft (2025.emnlp-main)

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Challenge: Large language models (LLMs) have shown significant promise in embodied decision-making tasks within virtual open-world environments, but lack domain-specific knowledge.
Approach: They propose a cost-effective agent framework that integrates cross-modal domain knowledge and finetunes a dedicated object detection model for visual analysis.
Outcome: The proposed framework reduces the requirement for domain-specific training data from millions of samples to a few hundred.
Signer Diversity-driven Data Augmentation for Signer-Independent Sign Language Translation (2024.findings-naacl)

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Challenge: Existing methods for sign language translation (SLT) rely on signer identity labels, which is often impractical and costly in real-world applications.
Approach: They propose a signer diversity-driven data augmentation method that can generalize to signers not encountered during training.
Outcome: The proposed method achieves state-of-the-art results without relying on signer identity labels.
VideoStir: Understanding Long Videos via Spatio-Temporally Structured and Intent-Aware RAG (2026.acl-long)

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Challenge: Existing methods for retrieval-augmented generation (RAG) to long videos are limited by limited context windows and flatten videos into independent segments.
Approach: They propose a structured and intent-aware long-video RAG framework that structures a video as a spatio-temporal graph and then performs multi-hop retrieval to aggregate evidence across distant yet contextually related events.
Outcome: The proposed framework is competitive with state-of-the-art baselines without auxiliary information.

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