84 citations · 161 across the 27 of their papers we have counts for
11 papers · 1 filter
Confidence v.s. Critique: A Decomposition of Self-Correction Capability for LLMs
Zhe Yang, Yichang Zhang, Yudong Wang +3
Large Language Models (LLMs) can correct their self-generated responses, but a decline in accuracy after self-correction is also witnessed. To have a deeper understanding of self-c…
ExecRepoBench: Multi-level Executable Code Completion Evaluation
Jian Yang, Jiajun Zhang, Jiaxi Yang +9
Code completion has become an essential tool for daily software development. Existing evaluation benchmarks often employ static methods that do not fully capture the dynamic nature…
Evaluating and Aligning CodeLLMs on Human Preference
Jian Yang, Jiaxi Yang, Ke Jin +7
Code large language models (codeLLMs) have made significant strides in code generation. Most previous code-related benchmarks, which consist of various programming exercises along…
Aligning CodeLLMs with Direct Preference Optimization
Yibo Miao, Bofei Gao, Shanghaoran Quan +6
The last year has witnessed the rapid progress of large language models (LLMs) across diverse domains. Among them, CodeLLMs have garnered particular attention because they can not…
Qwen2-VL: Enhancing Vision-Language Model's Perception of the World at Any Resolution
Peng Wang, Shuai Bai, Sinan Tan +16
We present the Qwen2-VL Series, an advanced upgrade of the previous Qwen-VL models that redefines the conventional predetermined-resolution approach in visual processing. Qwen2-VL…
A Spark of Vision-Language Intelligence: 2-Dimensional Autoregressive Transformer for Efficient Finegrained Image Generation
Liang Chen, Sinan Tan, Zefan Cai +7
This work tackles the information loss bottleneck of vector-quantization (VQ) autoregressive image generation by introducing a novel model architecture called the 2-Dimensional Aut…
Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
An Yang, Beichen Zhang, Binyuan Hui +13
In this report, we present a series of math-specific large language models: Qwen2.5-Math and Qwen2.5-Math-Instruct-1.5B/7B/72B. The core innovation of the Qwen2.5 series lies in in…
Rotated Runtime Smooth: Training-Free Activation Smoother for accurate INT4 inference
Ke Yi, Zengke Liu, Jianwei Zhang +4
Large language models have demonstrated promising capabilities upon scaling up parameters. However, serving large language models incurs substantial computation and memory movement…
Qwen2.5-Coder Technical Report
Binyuan Hui, Jian Yang, Zeyu Cui +21
In this report, we introduce the Qwen2.5-Coder series, a significant upgrade from its predecessor, CodeQwen1.5. This series includes six models: Qwen2.5-Coder-(0.5B/1.5B/3B/7B/14B/…
Synthesizing Text-to-SQL Data from Weak and Strong LLMs
Jiaxi Yang, Binyuan Hui, Min Yang +3
The capability gap between open-source and closed-source large language models (LLMs) remains a challenge in text-to-SQL tasks. In this paper, we introduce a synthetic data approac…
OpenHands: An Open Platform for AI Software Developers as Generalist Agents
Xingyao Wang, Boxuan Li, Yufan Song +21
Software is one of the most powerful tools that we humans have at our disposal; it allows a skilled programmer to interact with the world in complex and profound ways. At the same…