Papers by Shweti Mahajan

2 papers
Lexi: Self-Supervised Learning of the UI Language (2022.findings-emnlp)

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Challenge: Existing models rely on UI metadata, which is often missing or not accessible.
Approach: They propose a vision and language model that can learn generic visio-linguistic representations of UIs . they use a dataset to train Lexi, which is based on UI metadata .
Outcome: The proposed model can handle unique features of UI screens, including text richness and context sensitivity.
Automatic Pair Construction for Contrastive Post-training (2024.findings-naacl)

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Challenge: Large language models (LLMs) have unprecedented proficiency in a wide array of tasks.
Approach: They propose a way to construct contrastive data using preference pairs from multiple models of varying strengths using SLiC and DPO.
Outcome: The proposed method outperforms existing models like Orca in the comparison of SLiC and DPO with SFT baselines.

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