From the 1 of 6 linked papers with an AI index.
6 papers
SKILL-KD: Contrastive Skill Distillation for LLM Agents
Qiming Shi, Yibo Dou, Jiawen Zhu +5
The paper introduces SKILL-KD, a contrastive skill distillation framework that creates explicit textual skill patches from teacher‑student failures to iteratively improve weaker LL…
SPADER: Step-wise Peer Advantage with Diversity-Aware Exploration Rewards for Multi-Answer Question Answering
Qiming Shi, Zhaolu Kang, Yunfan Zhou +2
Large language models are increasingly deployed as tool-augmented agents to acquire information beyond parametric knowledge. While recent work has improved long-horizon tool-use re…
Cerebra: Aligning Implicit Knowledge in Interactive SQL Authoring
Yunfan Zhou, Qiming Shi, Zhongsu Luo +5
LLM-driven tools have significantly lowered barriers to writing SQL queries. However, user instructions are often underspecified, assuming the model understands implicit knowledge,…
ViseGPT: Towards Better Alignment of LLM-generated Data Wrangling Scripts and User Prompts
Jiajun Zhu, Xinyu Cheng, Zhongsu Luo +4
Large language models (LLMs) enable the rapid generation of data wrangling scripts based on natural language instructions, but these scripts may not fully adhere to user-specified…
Xavier: Toward Better Coding Assistance in Authoring Tabular Data Wrangling Scripts
Yunfan Zhou, Xiwen Cai, Qiming Shi +5
Data analysts frequently employ code completion tools in writing custom scripts to tackle complex tabular data wrangling tasks. However, existing tools do not sufficiently link the…
RCInvestigator: Towards Better Investigation of Anomaly Root Causes in Cloud Computing Systems
Shuhan Liu, Yunfan Zhou, Lu Ying +9
Finding the root causes of anomalies in cloud computing systems quickly is crucial to ensure availability and efficiency since accurate root causes can guide engineers to take appr…