3 papers
cs.SE2026
SysTradeBench: An Iterative Build-Test-Patch Benchmark for Strategy-to-Code Trading Systems with Drift-Aware Diagnostics
Yuchen Cao, Hanlin Zhang, Jacky Wai Keung +2
Large language models (LLMs) are increasingly used as quantitative research copilots to translate natural-language strategy specifications into executable trading code. Yet most ex…
cs.CL2025
CAKE: Cascading and Adaptive KV Cache Eviction with Layer Preferences
Ziran Qin, Yuchen Cao, Mingbao Lin +5
Large language models (LLMs) excel at processing long sequences, boosting demand for key-value (KV) caching. While recent efforts to evict KV cache have alleviated the inference bu…
cs.LG2025
Every Sample Matters: Leveraging Mixture-of-Experts and High-Quality Data for Efficient and Accurate Code LLM
Codefuse, Ling Team, : +30
Recent advancements in code large language models (LLMs) have demonstrated remarkable capabilities in code generation and understanding. It is still challenging to build a code LLM…