6 papers
To Diff or Not to Diff? Structure-Aware and Adaptive Output Formats for Efficient LLM-based Code Editing
Wei Cheng, Yongchang Cao, Chen Shen +4
Large Language Models (LLMs) are increasingly used for code editing, yet the prevalent full-code generation paradigm suffers from severe efficiency bottlenecks, posing challenges f…
On the Step Length Confounding in LLM Reasoning Data Selection
Bing Wang, Rui Miao, Chen Shen +7
Large reasoning models have recently demonstrated strong performance on complex tasks that require long chain-of-thought reasoning, through supervised fine-tuning on large-scale an…
ART: Attention Replacement Technique to Improve Factuality in LLMs
Ziqin Luo, Yihao Quan, Xiaofeng Zhang +2
Hallucination in large language models (LLMs) continues to be a significant issue, particularly in tasks like question answering, where models often generate plausible yet incorrec…
Composer 2 Technical Report
Cursor Research, :, Aaron Chan +53
Composer 2 is a specialized model designed for agentic software engineering. The model demonstrates strong long-term planning and coding intelligence while maintaining the ability…
Efficient Reasoning Through Suppression of Self-Affirmation Reflections in Large Reasoning Models
Kaiyuan Liu, Chen Shen, Zhanwei Zhang +3
While recent advances in large reasoning models have demonstrated remarkable performance, efficient reasoning remains critical due to the rapid growth of output length. Existing op…
GeoCAD: Local Geometry-Controllable CAD Generation with Large Language Models
Zhanwei Zhang, Kaiyuan Liu, Junjie Liu +5
Local geometry-controllable computer-aided design (CAD) generation aims to modify local parts of CAD models automatically, enhancing design efficiency. It also ensures that the sha…