activity
20232026
most citedQwen3 Technical Report

111 citations · 418 across the 44 of their papers we have counts for

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Showing 2024Show all

11 papers · 1 filter

cs.CL2024

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…

cs.CL2024

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…

cs.CL2024★ 15 cited

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…

cs.CL2024

IW-Bench: Evaluating Large Multimodal Models for Converting Image-to-Web

Hongcheng Guo, Wei Zhang, Junhao Chen +9

Recently advancements in large multimodal models have led to significant strides in image comprehension capabilities. Despite these advancements, there is a lack of the robust benc…

cs.CL2024★ 45 cited

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/…

cs.CL2024★ 7 cited

OLMoE: Open Mixture-of-Experts Language Models

Niklas Muennighoff, Luca Soldaini, Dirk Groeneveld +21

We introduce OLMoE, a fully open, state-of-the-art language model leveraging sparse Mixture-of-Experts (MoE). OLMoE-1B-7B has 7 billion (B) parameters but uses only 1B per input to…

cs.SE2024★ 11 cited

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…

cs.SE2024★ 22 cited

BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions

Terry Yue Zhuo, Minh Chien Vu, Jenny Chim +30

Task automation has been greatly empowered by the recent advances in Large Language Models (LLMs) via Python code, where the tasks ranging from software engineering development to…

cs.CV2024

DEEM: Diffusion Models Serve as the Eyes of Large Language Models for Image Perception

Run Luo, Yunshui Li, Longze Chen +9

The development of large language models (LLMs) has significantly advanced the emergence of large multimodal models (LMMs). While LMMs have achieved tremendous success by promoting…

cs.CL2024★ 3 cited

Prompting Large Language Models to Tackle the Full Software Development Lifecycle: A Case Study

Bowen Li, Wenhan Wu, Ziwei Tang +13

Recent advancements in large language models (LLMs) have significantly enhanced their coding capabilities. However, existing benchmarks predominantly focused on simplified or isola…

cs.SE2024★ 67 cited

StarCoder 2 and The Stack v2: The Next Generation

Anton Lozhkov, Raymond Li, Loubna Ben Allal +63

The BigCode project, an open-scientific collaboration focused on the responsible development of Large Language Models for Code (Code LLMs), introduces StarCoder2. In partnership wi…