Papers with grounding natural language instructions

2 papers
Mapping Natural Language Instructions to Mobile UI Action Sequences (2020.acl-main)

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Challenge: a new problem of grounding natural language instructions to mobile UI actions is emerging . we use a Transformer to extract action phrase tuples from long-range natural language instruction .
Approach: They propose a dataset that pairs English instructions with actions performed by people on a mobile UI emulator.
Outcome: The proposed model achieves 70.59% accuracy on predicting complete ground-truth action sequences in PixelHelp.
StructuThink: Reasoning with Task Transition Knowledge for Autonomous LLM-Based Agents (2025.findings-emnlp)

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Challenge: StructuThink framework enhances LLMs' ability to ground decisions in domain-specific scenarios.
Approach: They propose a knowledge-structured reasoning framework that enhances LLM-based agents with explicit decision constraints.
Outcome: The proposed framework achieves higher task success rates and more efficient action sequences than baseline methods.

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