Papers by Yintao Tai
PIXAR: Auto-Regressive Language Modeling in Pixel Space (2024.findings-acl)
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| Challenge: | Recent work shows the possibility of building open-vocabulary large language models that operate on pixel representations. |
| Approach: | They propose a pixel-based autoregressive LLM that performs generative tasks . they propose an adversarial pretraining stage that improves the readability and accuracy of PIXAR by 8.1 on LAMBADA and 8.5 on bAbI. |
| Outcome: | The proposed model performs free-form generative tasks while keeping the number of parameters on par with previous encoder-decoder models. |
Learning to Simulate Natural Language Feedback for Interactive Semantic Parsing (2023.acl-long)
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| Challenge: | Existing work on interactive semantic parsing relies on human annotations to train a model . prior work relied on human-annotated feedback data, which is prohibitively expensive and not scalable . |
| Approach: | They propose a task of simulating NL feedback for interactive semantic parsing . they propose evaluators to assess the quality of the simulated feedback . |
| Outcome: | The proposed simulator can generate high-quality NL feedback to boost the error correction ability of a specific parser. |