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20242026
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cs.CL2026

Scaling Data Difficulty: Improving Coding Models via Reinforcement Learning on Fresh and Challenging Problems

Zongqian Li, Tengchao Lv, Shaohan Huang +8

Training next-generation code generation models requires high-quality datasets, yet existing datasets face difficulty imbalance, format inconsistency, and data quality problems. We…

cs.CL2025

Code Aesthetics with Agentic Reward Feedback

Bang Xiao, Lingjie Jiang, Shaohan Huang +5

Large Language Models (LLMs) have become valuable assistants for developers in code-related tasks. While LLMs excel at traditional programming tasks such as code generation and bug…

cs.CL2025

Geometric-Mean Policy Optimization

Yuzhong Zhao, Yue Liu, Junpeng Liu +9

Group Relative Policy Optimization (GRPO) has significantly enhanced the reasoning capability of large language models by optimizing the arithmetic mean of token-level rewards. Unf…

cs.CL2025

VibeVoice Technical Report

Zhiliang Peng, Jianwei Yu, Wenhui Wang +10

This report presents VibeVoice, a novel model designed to synthesize long-form speech with multiple speakers by employing next-token diffusion, which is a unified method for modeli…

cs.CL2025

VisCodex: Unified Multimodal Code Generation via Merging Vision and Coding Models

Lingjie Jiang, Shaohan Huang, Xun Wu +3

Multimodal large language models (MLLMs) have significantly advanced the integration of visual and textual understanding. However, their ability to generate code from multimodal in…

cs.CL2025

Think Only When You Need with Large Hybrid-Reasoning Models

Lingjie Jiang, Xun Wu, Shaohan Huang +7

Recent Large Reasoning Models (LRMs) have shown substantially improved reasoning capabilities over traditional Large Language Models (LLMs) by incorporating extended thinking proce…