Papers by Chun Hei Lo
MATCH: Modulating Attention via In-Context Retrieval for Long-Context Transformers (2026.acl-long)
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Linrui Ma, Chun Hei Lo, Xinyu Wang, Peng Lu, Xihao Yuan, Hanting Chen, Kai Han, Xinghao Chen, Chengjun Zhan, Hanlin xu, Yichun Yin, Lifeng Shang, Feng Wen, Boxing Chen, Yufei Cui
| Challenge: | Existing approaches to improve efficiency often enforce rigid structural constraints such as local attention windows. |
| Approach: | They propose a framework that augments sparse-attention mechanisms with dynamically integrated in-context information through an efficient retrieval system. |
| Outcome: | Empirical results show that MATCH significantly improves the performance of sparse-attention models on synthetic and real-world natural-language tasks. |
Semantic Composition with PSHRG for Derivation Tree Reconstruction from Graph-Based Meaning Representations (2022.acl-long)
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| Challenge: | General graph-based meaning representations (MRs) that model sentence-level semantics aim to provide interpretable intermediate representations that are application-and domain-independent. |
| Approach: | They propose a probabilistic synchronous hyperedge replacement grammar for generating derivation trees from meaning representation graphs with a data-driven approach. |
| Outcome: | The proposed formalism approximates the semantic composition of DMRS graphs and recovers derivations that license them. |
Functional Distributional Semantics at Scale (2023.starsem-1)
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| Challenge: | Functional Distributional Semantics is a linguistically motivated framework for modelling lexical and sentence-level semantics with truth-conditional functions using distributional information. |
| Approach: | They propose a more expressive lexical model that works over a continuous semantic space. |
| Outcome: | The proposed model improves performance and flexibility and is compatible with present-day machine learning frameworks. |