2 citations · 2 across the 10 of their papers we have counts for
4 papers · 1 filter
RAVR: Reference-Answer-guided Variational Reasoning for Large Language Models
Tianqianjin Lin, Xi Zhao, Xingyao Zhang +5
Reinforcement learning (RL) can refine the reasoning abilities of large language models (LLMs), but critically depends on a key prerequisite: the LLM can already generate high-util…
Structuring GUI Elements through Vision Language Models: Towards Action Space Generation
Yi Xu, Yesheng Zhang, Jiajia Liu +1
Multimodal large language models (MLLMs) have emerged as pivotal tools in enhancing human-computer interaction. In this paper we focus on the application of MLLMs in the field of g…
Many-Turn Jailbreaking
Xianjun Yang, Liqiang Xiao, Shiyang Li +5
Current jailbreaking work on large language models (LLMs) aims to elicit unsafe outputs from given prompts. However, it only focuses on single-turn jailbreaking targeting one speci…
AutoMixAlign: Adaptive Data Mixing for Multi-Task Preference Optimization in LLMs
Nicholas E. Corrado, Julian Katz-Samuels, Adithya Devraj +6
When aligning large language models (LLMs), their performance on various tasks (such as being helpful, harmless, and honest) depends heavily on the composition of their training da…