Papers by Richard H.R. Hahnloser
Embedding-based Scientific Literature Discovery in a Text Editor Application (2020.acl-demos)
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| Challenge: | Despite the availability of powerful search engines and text editing software, discovering relevant papers and integrating the knowledge into a manuscript remain complex tasks associated with high cognitive load. |
| Approach: | They propose to combine text editing and literature discovery in an interactive user interface with a search engine that couples Boolean keyword filtering with nearest neighbor search over text embeddings. |
| Outcome: | The proposed application combines text editing and literature discovery in an interactive user interface. |
SciLit: A Platform for Joint Scientific Literature Discovery, Summarization and Citation Generation (2023.acl-demo)
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| Challenge: | Scientific writing involves retrieving, summarizing, and citing relevant papers. |
| Approach: | They propose a pipeline that automatically recommends relevant papers, extracts highlights, and suggests a reference sentence as a citation of a paper. |
| Outcome: | The proposed pipeline recommends relevant papers from large databases of hundreds of millions of papers . it provides extractive summaries and abstractively-generated citation sentences . authors question whether it is possible to partly automate this process to reduce cognitive load . |
Character-Level Translation with Self-attention (2020.acl-main)
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| Challenge: | Existing models for character-level neural machine translation operate on word-level, which makes them memory inefficient because of large vocabulary sizes. |
| Approach: | They propose a transformer-based model and a novel variant that uses convolutions to combine information from nearby characters to facilitate character interactions. |
| Outcome: | The proposed model outperforms the standard transformer model and learns more robust character alignments on bilingual and multilingual translation datasets. |