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ACE-RL: Adaptive Constraint-Enhanced Reward for Long-form Generation Reinforcement Learning
Jianghao Chen, Wei Sun, Qixiang Yin +2
Long-form generation has become a critical and challenging application for Large Language Models (LLMs). Existing studies are limited by their reliance on scarce, high-quality long…
LADM: Long-context Training Data Selection with Attention-based Dependency Measurement for LLMs
Jianghao Chen, Junhong Wu, Yangyifan Xu +1
Long-context modeling has drawn more and more attention in the area of Large Language Models (LLMs). Continual training with long-context data becomes the de-facto method to equip…
LR^2Bench: Evaluating Long-chain Reflective Reasoning Capabilities of Large Language Models via Constraint Satisfaction Problems
Jianghao Chen, Zhenlin Wei, Zhenjiang Ren +2
Recent progress in Large Reasoning Models (LRMs) has significantly enhanced the reasoning abilities of Large Language Models (LLMs), empowering them to tackle increasingly complex…
Hit the Sweet Spot! Span-Level Ensemble for Large Language Models
Yangyifan Xu, Jianghao Chen, Junhong Wu +1
Ensembling various LLMs to unlock their complementary potential and leverage their individual strengths is highly valuable. Previous studies typically focus on two main paradigms:…
ChineseWebText: Large-scale High-quality Chinese Web Text Extracted with Effective Evaluation Model
Jianghao Chen, Pu Jian, Tengxiao Xi +7
During the development of large language models (LLMs), the scale and quality of the pre-training data play a crucial role in shaping LLMs' capabilities. To accelerate the research…