5 papers · 1 filter
MulDimIF: A Multi-Dimensional Constraint Framework for Evaluating and Improving Instruction Following in Large Language Models
Junjie Ye, Caishuang Huang, Zhuohan Chen +12
Instruction following refers to the ability of large language models (LLMs) to generate outputs that satisfy all specified constraints. Existing research has primarily focused on c…
LongCat-Flash Technical Report
Meituan LongCat Team, Bayan, Bei Li +179
We introduce LongCat-Flash, a 560-billion-parameter Mixture-of-Experts (MoE) language model designed for both computational efficiency and advanced agentic capabilities. Stemming f…
Libra: Assessing and Improving Reward Model by Learning to Think
Meng Zhou, Bei Li, Jiahao Liu +5
Reinforcement learning (RL) has significantly improved the reasoning ability of large language models. However, current reward models underperform in challenging reasoning scenario…
Training Agents with Weakly Supervised Feedback from Large Language Models
Dihong Gong, Pu Lu, Zelong Wang +2
Large Language Models (LLMs) offer a promising basis for creating agents that can tackle complex tasks through iterative environmental interaction. Existing methods either require…
Towards Democratizing Multilingual Large Language Models For Medicine Through A Two-Stage Instruction Fine-tuning Approach
Meng Zhou, Surajsinh Parmar, Anubhav Bhatti
Open-source, multilingual medical large language models (LLMs) have the potential to serve linguistically diverse populations across different regions. Adapting generic LLMs for he…