papers

Publications (8)

cs.LG2026

FrontierSmith: Synthesizing Open-Ended Coding Problems at Scale

Runyuan He, Qiuyang Mang, Shang Zhou +14

Many real-world coding challenges are open-ended and admit no known optimal solution. Yet, recent progress in LLM coding has focused on well-defined tasks such as feature implement…

cs.OS2026

Continuum: Efficient and Robust Multi-Turn LLM Agent Scheduling with KV Cache Time-to-Live

Hanchen Li, Runyuan He, Qiuyang Mang +7

KV cache management is essential for efficient LLM inference. To maximize utilization, existing inference engines evict finished requests' KV cache if new requests are waiting. Thi…

cs.AI2026

Playing Psychic: Using Thought Trees to Predict Reasoning Models Accuracy on Coding Tasks

Jiaxin Fang, Runyuan He, Sahil Bhatia +2

Recent advances in large language models (LLMs) have shown that test-time scaling can substantially improve model performance on complex tasks, particularly in the coding domain. U…

cs.DB2026

PLOP: Cost-Based Placement of Semantic Operators in Hybrid Query Plans

Qiuyang Mang, Yufan Xiang, Hangrui Zhou +5

Recent database systems have introduced semantic operators that leverage large language models (LLMs) to filter, join, and project over structured data using natural language predi…

cs.AI2026

Combee: Scaling Prompt Learning for Self-Improving Language Model Agents

Hanchen Li, Runyuan He, Qizheng Zhang +11

Recent advances in prompt learning allow large language model agents to acquire task-relevant knowledge from inference-time context without parameter changes. For example, existing…

cs.IR2026

In-depth Analysis of Graph-based RAG in a Unified Framework

Yingli Zhou, Yaodong Su, Youran Sun +8

Graph-based Retrieval-Augmented Generation (RAG) has proven effective in integrating external knowledge into large language models (LLMs), improving their factual accuracy, adaptab…

cs.DB2026

Automated Discovery of Test Oracles for Database Management Systems Using LLMs

Qiuyang Mang, Runyuan He, Suyang Zhong +3

Since 2020, automated testing for Database Management Systems (DBMSs) has flourished, uncovering hundreds of bugs in widely-used systems. A cornerstone of these techniques is test…

cs.LG2025

FrontierCS: Evolving Challenges for Evolving Intelligence

Qiuyang Mang, Wenhao Chai, Zhifei Li +48

We introduce FrontierCS, a benchmark of 156 open-ended problems across diverse areas of computer science, designed and reviewed by experts, including CS PhDs and top-tier competiti…