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-(0.5 B/1.5 …

The advancement of function-calling agent models requires diverse, reliable, and high-
quality datasets. This paper presents APIGen, an automated data generation pipeline …

We introduce Differential Performance Evaluation (DPE), a framework designed to reliably
evaluate Large Language Models (LLMs) for efficient code generation. Traditional coding …

Contemporary evaluation techniques are inadequate for agentic systems. These
approaches either focus exclusively on final outcomes--ignoring the step-by-step nature of …

The increasing development of large language models (LLMs) in code generation has
drawn significant attention among researchers. To enhance LLM-based code generation …

Large language models (LLMs) for code have become indispensable in various domains,
including code generation, reasoning tasks and agent systems. While open-access code …

Code generation models have increasingly become integral to aiding software
development. Although current research has thoroughly examined the correctness of the …

Integrating Large Language Models (LLMs) into autonomous agents marks a significant shift
in the research landscape by offering cognitive abilities that are competitive with human …

Code large language models (codeLLMs) have made significant strides in code generation.
Most previous code-related benchmarks, which consist of various programming exercises …

We introduce self-invoking code generation, a new task designed to evaluate the
progressive reasoning and problem-solving capabilities of LLMs. In this task, models are …