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cs.SE2025
U2F: Encouraging SWE-Agent to Seize Novelty without Losing Feasibility
Wencheng Ye, Yan Liu
Large language models (LLMs) have shown strong capabilities in software engineering tasks, yet most existing LLM-based SWE-Agents mainly tackle well-defined problems using conventi…
cs.CV2025
ActDistill: General Action-Guided Self-Derived Distillation for Efficient Vision-Language-Action Models
Wencheng Ye, Tianshi Wang, Lei Zhu +3
Recent Vision-Language-Action (VLA) models have shown impressive flexibility and generalization, yet their deployment in robotic manipulation remains limited by heavy computational…
cs.LG2025
When LLM Meets Time Series: Can LLMs Perform Multi-Step Time Series Reasoning and Inference
Wen Ye, Jinbo Liu, Defu Cao +2
The rapid advancement of Large Language Models (LLMs) has sparked growing interest in their application to time series analysis tasks. However, their ability to perform complex rea…