1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.AI2026
IQuest-Coder-V1 Technical Report
Jian Yang, Wei Zhang, Shawn Guo +35
In this report, we introduce the IQuest-Coder-V1 series-(7B/14B/40B/40B-Loop), a new family of code large language models (LLMs). Moving beyond static code representations, we prop…
cs.CV2025★ 1 cited
CogDoc: Towards Unified thinking in Documents
Qixin Xu, Haozhe Wang, Che Liu +2
Current document reasoning paradigms are constrained by a fundamental trade-off between scalability (processing long-context documents) and fidelity (capturing fine-grained, multim…
cs.AI2025
Emergent Hierarchical Reasoning in LLMs through Reinforcement Learning
Haozhe Wang, Qixin Xu, Che Liu +3
Reinforcement Learning (RL) has proven highly effective at enhancing the complex reasoning abilities of Large Language Models (LLMs), yet underlying mechanisms driving this success…