Papers by Mingyuan Ma

2 papers
Octopus: On-device language model for function calling of software APIs (2025.naacl-industry)

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Challenge: Large Language Models (LLMs) are pivotal for advanced text processing and generation.
Approach: They propose a framework to train on-device Large Language Models optimized for invoking software APIs.
Outcome: The proposed model outperforms GPT-4 in API calling tasks while maintaining inference speed.
ContextCheck: Sentence-Level Faithfulness Verification with Context-Aware Disambiguation (2026.findings-acl)

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Challenge: Large language models often hallucinate, producing content that is factually incorrect or not grounded in the sources.
Approach: They propose a framework for sentence-level faithfulness verification with context-aware disambiguation.
Outcome: The proposed framework improves Macro F1 by over 10 points compared to baselines on three context-dependent datasets.

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