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Junyao Yang

3 accepted papers

2026

RCP-Merging: Merging Long Chain-of-Thought Models with Domain-Specific Models by Considering Reasoning Capability as Prior

AAAI 2026technical

Large Language Models (LLMs) with long chain-of-thought (CoT) capability, termed Reasoning Models, demonstrate superior intricate problem-solving abilities through multi-step long CoT reasoning. To create a dual-capability model with long CoT capability and domain-specific knowledge without substant

Cited by 0SourcePDFScholar
2025

PrivacyRestore: Privacy-Preserving Inference in Large Language Models via Privacy Removal and Restoration

ACL 2025long

The widespread usage of online Large Language Models (LLMs) inference services has raised significant privacy concerns about the potential exposure of private information in user inputs. Existing privacy protection methods for LLMs suffer from either insufficient privacy protection with performance…

Cited by 0SourcePDFScholar
2025

RewardDS: Privacy-Preserving Fine-Tuning for Large Language Models via Reward Driven Data Synthesis

EMNLP 2025

The success of large language models (LLMs) has attracted many individuals to fine-tune them for domain-specific tasks by uploading their data. However, in sensitive areas like healthcare and finance, privacy concerns often arise. One promising solution is to generate synthetic data with Differentia