2 citations · 2 across the 6 of their papers we have counts for
6 papers
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…
Large-Scale Terminal Agentic Trajectory Generation from Dockerized Environments
Siwei Wu, Yizhi Li, Yuyang Song +8
Training agentic models for terminal-based tasks critically depends on high-quality terminal trajectories that capture realistic long-horizon interactions across diverse domains. H…
AGRO-SQL: Agentic Group-Relative Optimization with High-Fidelity Data Synthesis
Cehua Yang, Dongyu Xiao, Junming Lin +7
The advancement of Text-to-SQL systems is currently hindered by the scarcity of high-quality training data and the limited reasoning capabilities of models in complex scenarios. In…
P-Aligner: Enabling Pre-Alignment of Language Models via Principled Instruction Synthesis
Feifan Song, Bofei Gao, Yifan Song +6
Large Language Models (LLMs) are expected to produce safe, helpful, and honest content during interaction with human users, but they frequently fail to align with such values when…
QUITE: A Query Rewrite System Beyond Rules with LLM Agents
Yuyang Song, Hanxu Yan, Jiale Lao +5
Query rewrite transforms SQL queries into semantically equivalent forms that run more efficiently. Existing approaches mainly rely on predefined rewrite rules, but they handle a li…
Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey
Junqiao Wang, Zeng Zhang, Yangfan He +18
With the rapid evolution of large language models (LLM), reinforcement learning (RL) has emerged as a pivotal technique for code generation and optimization in various domains. Thi…