84 citations · 172 across the 43 of their papers we have counts for
5 papers · 1 filter
More Than One Teacher: Adaptive Multi-Guidance Policy Optimization for Diverse Exploration
Xiaoyang Yuan, Yujuan Ding, Yi Bin +5
Reinforcement Learning with Verifiable Rewards (RLVR) is a promising paradigm for enhancing the reasoning ability in Large Language Models (LLMs). However, prevailing methods prima…
Explore Briefly, Then Decide: Mitigating LLM Overthinking via Cumulative Entropy Regulation
Yi Bin, Tianyi Jiang, Yujuan Ding +5
Large Language Models (LLMs) have demonstrated remarkable reasoning abilities on complex problems using long Chain-of-Thought (CoT) reasoning. However, they often suffer from overt…
MMEvol: Empowering Multimodal Large Language Models with Evol-Instruct
Run Luo, Haonan Zhang, Longze Chen +13
The development of Multimodal Large Language Models (MLLMs) has seen significant advancements with increasing demands in various fields (e.g., multimodal agents, embodied intellige…
T-SciQ: Teaching Multimodal Chain-of-Thought Reasoning via Mixed Large Language Model Signals for Science Question Answering
Lei Wang, Yi Hu, Jiabang He +4
Large Language Models (LLMs) have recently demonstrated exceptional performance in various Natural Language Processing (NLP) tasks. They have also shown the ability to perform chai…
ICL-D3IE: In-Context Learning with Diverse Demonstrations Updating for Document Information Extraction
Jiabang He, Lei Wang, Yi Hu +4
Large language models (LLMs), such as GPT-3 and ChatGPT, have demonstrated remarkable results in various natural language processing (NLP) tasks with in-context learning, which inv…