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INSPIRE: An Internalize-Then-Improve Approach for Example-Driven Mathematical Reasoning
Shuai Wang, Jiayi Kuang, Yinghui Li +4
Mathematical reasoning has seen rapid progress in large language models (LLMs), yet existing methods optimize predominantly for final-answer correctness, raising the question wheth…
Youtu-LLM: Unlocking the Native Agentic Potential for Lightweight Large Language Models
Junru Lu, Jiarui Qin, Lingfeng Qiao +35
We introduce Youtu-LLM, a lightweight yet powerful language model that harmonizes high computational efficiency with native agentic intelligence. Unlike typical small models that r…
Atomic Thinking of LLMs: Decoupling and Exploring Mathematical Reasoning Abilities
Jiayi Kuang, Haojing Huang, Yinghui Li +8
Large Language Models (LLMs) have demonstrated outstanding performance in mathematical reasoning capabilities. However, we argue that current large-scale reasoning models primarily…
Refine Knowledge of Large Language Models via Adaptive Contrastive Learning
Yinghui Li, Haojing Huang, Jiayi Kuang +7
How to alleviate the hallucinations of Large Language Models (LLMs) has always been the fundamental goal pursued by the LLMs research community. Looking through numerous hallucinat…
Natural Language Understanding and Inference with MLLM in Visual Question Answering: A Survey
Jiayi Kuang, Jingyou Xie, Haohao Luo +6
Visual Question Answering (VQA) is a challenge task that combines natural language processing and computer vision techniques and gradually becomes a benchmark test task in multimod…
Dynamic Demonstration Retrieval and Cognitive Understanding for Emotional Support Conversation
Zhe Xu, Daoyuan Chen, Jiayi Kuang +3
Emotional Support Conversation (ESC) systems are pivotal in providing empathetic interactions, aiding users through negative emotional states by understanding and addressing their…