24 citations · 27 across the 17 of their papers we have counts for
13 papers · 1 filter
SiriusDeliver: Automating Data Warehouse Delivery at Tencent
Haining Xie, Xiaokai Zhou, Jiaming Yang +12
Enterprise data warehouses (DWs) support business-critical analytics, but warehouse task delivery remains a complicated production process involving context retrieval, workflow con…
Kimi K3: Open Frontier Intelligence
Kimi Team, Tongtong Bai, Yifan Bai +398
We introduce Kimi K3, a 2.8T parameter Mixture-of-Experts model with 104 billion activated parameters, native vision capabilities, and a 1-million-token context window. Kimi K3 is…
DataClawEval: A Benchmark for Data Engineering Agents in Real Industrial Harness
Debin Meng, Jiaming Yang, Zefang Zong +4
Large language models (LLMs) and LLM-based agents are increasingly being deployed to automate complex workflows, promising to revolutionize data management and processing. However,…
PATS: Policy-Aware Training Scaffolding for Agentic Reinforcement Learning
Yipeng Shi, Zhipeng Ma, Yue Wang +4
In long-horizon LLM agent reinforcement learning, weak policies often repeat similar failures, producing uninformative rollout trajectories and limiting effective policy optimizati…
NOVA: A Verification-Aware Agent Harness for Architecture Evolution in Industrial Recommender Systems
Shaohua Liu, Liang Fang, Yilong Sun +16
Industrial advertising recommender systems are continually improved through architecture modifications, yet production iteration remains expert-intensive because coordinated change…
ProSPy: A Profiling-Driven SQL-Python Agentic Framework for Enterprise Text-to-SQL
Zhaorui Yang, Huawei Zheng, Sen Yang +14
Large language models have substantially advanced Text-to-SQL systems, yet applying them to enterprise-scale databases remains challenging. Real-world databases often contain large…
ATOD: Annealed Turn-Aware On-Policy Distillation for Multi-Turn Agentic Tasks
Qitai Tan, Zefang Zong, Mo Li +3
Training small language-model agents for long-horizon interactive tasks requires both fast imitation and reward-driven improvement. On-policy distillation (OPD) provides dense teac…
SIRIUS-SQL: Anchoring Multi-Candidate Text-to-SQL in Execution Feedback
Leo Luo, Haining Xie, Siqi Shen +8
Text-to-SQL on complex schemas is unreliable on a single pass, so recent systems generate multiple SQL candidates and let voting filter out errors. Yet voting alone is not enough,…
EviLink: Multi-Path Schema Linking with Uncertainty-Guided Evidence Acquisition for Large-Scale Text-to-SQL
Huawei Zheng, Sen Yang, Zhaorui Yang +12
Schema linking is a difficult and important step in large-scale Text-to-SQL, where systems must identify a compact yet sufficient schema context from large and ambiguous databases.…
Efficient Agentic Reinforcement Learning with On-Policy Intrinsic Knowledge Boundary Enhancement
Dingwei Chen, Zefang Zong, Zhipeng Ma +5
Agentic reinforcement learning (RL) has proven effective for training LLM-based agents with external tool-use capabilities. However, we identify that agentic RL training induces in…
Time to REFLECT: Can We Trust LLM Judges for Evidence-based Research Agents?
Leyao Wang, Yanan He, Peng Chen +5
Deep research agents increasingly automate complex information-seeking tasks, producing evidence-grounded reports via multi-step reasoning, tool use, and synthesis. Their growing r…
ATGPO: Agentic Turn-Group Policy Optimization with Adaptive Turn-level Clipping
Dingwei Chen, Zefang Zong, Zhipeng Ma +5
Reinforcement learning for agentic large language models (LLMs) typically relies on a sparse, trajectory-level outcome reward, making it difficult to evaluate the contribution of i…
SiriusHelper: An LLM Agent-Based Operations Assistant for Big Data Platforms
Yu Shen, Shiyang Liu, Qihang He +14
Big data platforms are widely used in modern enterprises, and an in-production intelligent assistant is increasingly important to help users quickly find actionable guidance and re…