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cs.CL2025
CARFT: Boosting LLM Reasoning via Contrastive Learning with Annotated Chain-of-Thought-based Reinforced Fine-Tuning
Wenqiao Zhu, Ji Liu, Rongjuncheng Zhang +2
Reasoning capability plays a significantly critical role in the the broad applications of Large Language Models (LLMs). To enhance the reasoning performance of LLMs, diverse Reinfo…
cs.AI2025
PuzzleClone: A DSL-Powered Framework for Synthesizing Verifiable Data
Kai Xiong, Yanwei Huang, Rongjunchen Zhang +3
High-quality mathematical and logical datasets with verifiable answers are essential for strengthening the reasoning capabilities of large language models (LLMs). While recent data…
cs.MM2025
Nexus: An Omni-Perceptive And -Interactive Model for Language, Audio, And Vision
Che Liu, Yingji Zhang, Dong Zhang +13
This work proposes an industry-level omni-modal large language model (LLM) pipeline that integrates auditory, visual, and linguistic modalities to overcome challenges such as limit…