12 papers
Adaptive Social Learning via Mode Policy Optimization for Language Agents
Minzheng Wang, Yongbin Li, Haobo Wang +6
Effective social intelligence simulation requires language agents to dynamically adjust reasoning depth, a capability notably absent in current studies. Existing methods either lac…
EvoRoute: Experience-Driven Self-Routing LLM Agent Systems
Guibin Zhang, Haiyang Yu, Kaiming Yang +4
Complex agentic AI systems, powered by a coordinated ensemble of Large Language Models (LLMs), tool and memory modules, have demonstrated remarkable capabilities on intricate, mult…
Selective Weak-to-Strong Generalization
Hao Lang, Fei Huang, Yongbin Li
Future superhuman models will surpass the ability of humans and humans will only be able to \textit{weakly} supervise superhuman models. To alleviate the issue of lacking high-qual…
EIFBENCH: Extremely Complex Instruction Following Benchmark for Large Language Models
Tao Zou, Xinghua Zhang, Haiyang Yu +3
With the development and widespread application of large language models (LLMs), the new paradigm of "Model as Product" is rapidly evolving, and demands higher capabilities to addr…
IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference Optimization
Xinghua Zhang, Haiyang Yu, Cheng Fu +2
In the realm of large language models (LLMs), the ability of models to accurately follow instructions is paramount as more agents and applications leverage LLMs for construction, w…
DEMO: Reframing Dialogue Interaction with Fine-grained Element Modeling
Minzheng Wang, Xinghua Zhang, Kun Chen +5
Large language models (LLMs) enabled dialogue systems have become one of the central modes in human-machine interaction, which bring about vast amounts of conversation logs and inc…