Papers with SURF
Answering Unanswered Questions through Semantic Reformulations in Spoken QA (2023.acl-industry)
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| Challenge: | Question Answering (QA) is a longstanding NLP task, and voice assistants like Alexa have made Spoken QA ubiquitous. |
| Approach: | They propose a model that uses linguistically-grounded operations to rewrite questions to facilitate answering. |
| Outcome: | The proposed model improves answer rates on 1M unanswered questions from a leading voice assistant. |
SURF: Semantic-level Unsupervised Reward Function for Machine Translation (2022.naacl-main)
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| Challenge: | Reinforcement Learning (RL) is dependent on the reward formulation due to the intrinsic difficulty of the task in the high-dimensional discrete action space and the sparseness of the standard reward functions. |
| Approach: | They propose a maximally dense semantic-level unsupervised reward function which mimics human evaluation by considering both sentence fluency and semantic similarity. |
| Outcome: | The proposed reward outperforms the standard sparse reward by 2% on average for in- and out-of-domain settings. |
The Effects of Unimodal Representation Choices on Multimodal Learning (L18-1)
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| Challenge: | In the real world, multiple modes of information are gathered to create knowledge in a way humans can understand. |
| Approach: | They propose to combine unimodal representations to map multiple modes of information to a single space . they argue that the way they are combined can affect performance and classification metrics . |
| Outcome: | The proposed model can be used to correlate words in a textual description of an object with multimodal representations. |