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Maosongcao Maosongcao

2 accepted papers

2025

Condor: Enhance LLM Alignment with Knowledge-Driven Data Synthesis and Refinement

ACL 2025long

The quality of Supervised Fine-Tuning (SFT) data plays a critical role in enhancing the conversational capabilities of Large Language Models (LLMs). However, the availability of high-quality human-annotated SFT data has become a significant bottleneck for LLMs, necessitating a greater reliance on sy…

2025

OmniAlign-V: Towards Enhanced Alignment of MLLMs with Human Preference

ACL 2025long

Recent advancements in open-source multi-modal large language models (MLLMs) have primarily focused on enhancing foundational capabilities, leaving a significant gap in human preference alignment. This paper introduces OmniAlign-V, a comprehensive dataset of 200K high-quality training samples featur…