Papers with question encoding
STL-CQA: Structure-based Transformers with Localization and Encoding for Chart Question Answering (2020.emnlp-main)
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| Challenge: | Chart Question Answering (CQA) is a task of answering natural language questions about visualisations in the chart image. |
| Approach: | They propose a method for Chart Question Answering which improves the question/answering through sequential elements localization, question encoding and then, a structural transformer-based learning approach. |
| Outcome: | The proposed method outperforms state-of-the-art methods on various chart Q/A datasets while outperforming even human baseline. |
Understanding LLMs’ Cross-Lingual Context Retrieval: How Good It Is And Where It Comes From (2025.emnlp-main)
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| Challenge: | Cross-lingual context retrieval is a fundamental aspect of cross-lingual alignment, but the performance and mechanism of it for large language models (LLMs) remains unclear. |
| Approach: | They evaluate cross-lingual context retrieval of over 40 large language models . they use cross-linguistic machine reading comprehension as a representative scenario . |
| Outcome: | The results show that open LLMs show strong cross-lingual context retrieval ability . the results also show that their oracle performances improve after training . |