Papers by Kavya Srinet

2 papers
CraftAssist Instruction Parsing: Semantic Parsing for a Voxel-World Assistant (2020.acl-main)

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Challenge: Existing datasets for semantic parsing are limited due to the wide variety of robot setups and proprietary nature of personal assistants.
Approach: They propose a semantic parsing dataset for Minecraft's voxel-based crafting game . they propose to use 7K human utterances and their corresponding parses to execute them in game if proper world state is provided .
Outcome: The proposed dataset can be used to analyze human-bot interactions in the game Minecraft.
AnyMAL: An Efficient and Scalable Any-Modality Augmented Language Model (2024.emnlp-industry)

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Challenge: Prior work on LLMs focused on models that combine text and one other modality, such as image encoders or proprietary models that are not open sourced.
Approach: They propose a unified model that reasons over diverse input modality signals and generates textual responses.
Outcome: The proposed model performs better on multimodal tasks than industry-leading models .

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