Papers by Dehai Min
UniHGKR: Unified Instruction-aware Heterogeneous Knowledge Retrievers (2025.naacl-long)
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| Challenge: | Existing information retrieval models assume a homogeneous structure for knowledge sources and user queries, limiting their applicability in real-world settings. |
| Approach: | They propose a unified instruction-aware heterogeneous knowledge retriever that builds a heterogenous retrieval space for heterogenized knowledge and follows diverse user instructions to retrieve knowledge in specified types. |
| Outcome: | The proposed framework outperforms state-of-the-art methods on CompMix-IR . it achieves 6.36% relative improvements and 54.23% relative improvements . |
Three Stream Based Multi-level Event Contrastive Learning for Text-Video Event Extraction (2023.emnlp-main)
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| Challenge: | Existing methods for event extraction ignore motion representations in videos and are misguided by background noise. |
| Approach: | They propose a text-video based multimodal event extraction framework that integrates video appearance features and motion representations with video appearance. |
| Outcome: | The proposed framework outperforms the state-of-the-art methods in the event extraction field. |
QuCo-RAG: Quantifying Uncertainty from the Pre-training Corpus for Dynamic Retrieval-Augmented Generation (2026.findings-acl)
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| Challenge: | Existing methods for reducing LLM hallucinations rely on model-internal signals . Existing approaches rely only on model internal signals, resulting in unreliability . |
| Approach: | They propose a method that shifts from subjective confidence to objective statistics . they leverage Infini-gram for millisecond-latency queries over 4 trillion tokens . |
| Outcome: | The proposed method reduces hallucinations in large language models by reducing uncertainty in the model. |