Papers with information transfer
In Neural Machine Translation, What Does Transfer Learning Transfer? (2020.acl-main)
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| Challenge: | a recent study found that word embeddings are not necessary for transfer learning. |
| Approach: | They perform several ablation studies that limit information transfer and measure the quality impact across three language pairs to gain a black-box understanding of transfer learning. |
| Outcome: | The proposed method can eliminate the need for a warm-up phase when training transformer models in high resource language pairs. |
INT: Establishing Information Transfer for Multilingual Intent Detection and Slot Filling (2025.findings-acl)
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Di Wu, Liting Jiang, Bohui Mao, Hongyan Xie, Haoxiang Su, Zhongjiang He, Ruiyu Fang, Shuangyong Song, Hao Huang, Xuelong Li
| Challenge: | Existing studies struggle to achieve performance comparable to that on high-resource languages due to inherent linguistic diversity of multilingual SLU tasks. |
| Approach: | They propose a multilingual information transfer network to solve these challenges . they propose to reformulate SF as a span prediction problem and introduce a slot-matching attention mechanism to achieve slot alignment across languages. |
| Outcome: | The proposed model outperforms baseline models on the MASSIVE and MASSIV-UG datasets in overall accuracy across all languages. |
mPresenter: An Agentic Framework for Generating Multilingual Presentation Videos from Scientific Papers (2026.findings-acl)
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| Challenge: | Existing Paper2Video systems are monolingual and often rely on single-pass pipelines. |
| Approach: | They propose a multilingual agentic Paper2Video system that decomposes the task into planning, audience-oriented critique, layout-aware slide generation, and multilingual figure interpretation. |
| Outcome: | The proposed system improves question-answering accuracy relative to previous systems while maintaining affordable cost and latency. |
Leveraging Social Context for Humor Recognition and Sense of Humor Evaluation in Social Media with a New Chinese Humor Corpus - HumorWB (2024.lrec-main)
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| Challenge: | Existing humor computing research focuses on content while neglecting interaction relationships in social media. |
| Approach: | They propose a dataset which introduces social context information from social media . they propose 'humor recognition' task and 'horror evaluation task' |
| Outcome: | The proposed model incorporates social context information from social media . it shows that it is efficient and can be used to evaluate humor in real life . |
All for One: LLMs Solve Mental Math at the Last Token With Information Transferred From Other Tokens (2025.emnlp-main)
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| Challenge: | Large language models (LLMs) perform well on a multitude of computational tasks, yet their inner workings remain unclear. |
| Approach: | They propose two techniques to inhibit input-specific token computations in initial layers . they propose a transformer that allows for any token to immediately access all preceding tokens . |
| Outcome: | The proposed algorithms can perform on a variety of mental math tasks with high accuracy and transfer across models. |