Papers by Wook-Shin Han
TRIAL: Token Relations and Importance Aware Late-interaction for Accurate Text Retrieval (2025.emnlp-main)
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| Challenge: | Late-interaction based multi-vector retrieval systems rely on a naive summation of token-level similarity scores . this leads to inaccurate relevance estimation due to tokenization of semantic units and the influence of low-content words. |
| Approach: | They propose a late-interaction-based multi-vector retrieval system that uses token relations and token importance in relevance scoring. |
| Outcome: | Extensive tests show that TRIAL achieves state-of-the-art accuracy compared to existing methods. |
HELIOS: Harmonizing Early Fusion, Late Fusion, and LLM Reasoning for Multi-Granular Table-Text Retrieval (2025.acl-long)
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| Challenge: | Existing methods for table-text retrieval are limited due to the need to bridge structured tables and unstructured passages. |
| Approach: | They propose a table-text retrieval system that combines the strengths of both approaches . they propose bipartite subgraph retrieval and query-relevant node expansion . |
| Outcome: | The proposed method outperforms state-of-the-art models with a 42.6% and 39.9% improvement on the OTT-QA benchmark. |
LILaC: Late Interacting in Layered Component Graph for Open-domain Multimodal Multihop Retrieval (2025.emnlp-main)
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| Challenge: | Existing multimodal document retrieval frameworks focus on textual, tabular, and visual elements, but there is a shift toward open-domain multimodal retrieval. |
| Approach: | They propose a multimodal retrieval framework that uses a component graph and a late-interaction-based subgraph retrieval method to capture semantic relationships between components. |
| Outcome: | The proposed framework achieves state-of-the-art retrieval performance on all five benchmarks . it is based on a layered component graph representing multimodal information at two layers . |
SAFE: Schema-Driven Approximate Distance Join for Efficient Knowledge Graph Querying (2025.emnlp-main)
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| Challenge: | Existing methods map an LLM-generated query graph onto the KG or let the LLM traverse the entire graph. |
| Approach: | They propose a framework that leverages schema graphs for robust query graph generation and efficient KG retrieval. |
| Outcome: | Extensive experiments on WebQSP, CWQ and GrailQA show that the proposed framework outperforms state-of-the-art methods in accuracy and efficiency. |