1 citations · 1 across the 5 of their papers we have counts for
5 papers
Tool-Augmented On-Policy Distillation for LLM Domain Adaptation in Sequence-Based Omics Tasks
Jie Ying, Zhefan Wang, Zihong Chen +11
Multi-omics sequences contain complex biological patterns, yet deciphering their mechanisms for automated scientific discovery remains challenging. As large language models (LLMs)…
Knowledge-to-Verification: Exploring RLVR for LLMs in Knowledge-Intensive Domains
Zhonghang Yuan, Zhefan Wang, Fang Hu +7
Reinforcement learning with verifiable rewards (RLVR) has demonstrated promising potential to enhance the reasoning capabilities of large language models (LLMs) in domains such as…
Route-Induced Density and Stability (RIDE): Controlled Intervention and Mechanism Analysis of Routing-Style Meta Prompts on LLM Internal States
Dianxing Zhang, Gang Li, Sheng Li
Routing is widely used to scale large language models, from Mixture-of-Experts gating to multi-model/tool selection. A common belief is that routing to a task ``expert'' activates…
Routine: A Structural Planning Framework for LLM Agent System in Enterprise
Guancheng Zeng, Xueyi Chen, Jiawang Hu +13
The deployment of agent systems in an enterprise environment is often hindered by several challenges: common models lack domain-specific process knowledge, leading to disorganized…
Adaptable and Precise: Enterprise-Scenario LLM Function-Calling Capability Training Pipeline
Guancheng Zeng, Wentao Ding, Beining Xu +8
Enterprises possess a vast array of API assets scattered across various functions, forming the backbone of existing business processes. By leveraging these APIs as functional tools…