most citedHelloBench: Evaluating Long Text Generation Capabilities of Large Language Models

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cs.CL2025

ACADREASON: Exploring the Limits of Reasoning Models with Academic Research Problems

Xin Gui, King Zhu, JinCheng Ren +17

In recent years, the research focus of large language models (LLMs) and agents has shifted increasingly from demonstrating novel capabilities to complex reasoning and tackling chal…

cs.CL2025

A Comprehensive Survey on Long Context Language Modeling

Jiaheng Liu, Dawei Zhu, Zhiqi Bai +34

Efficient processing of long contexts has been a persistent pursuit in Natural Language Processing. With the growing number of long documents, dialogues, and other textual data, it…

cs.CL2025

OpenCSG Chinese Corpus: A Series of High-quality Chinese Datasets for LLM Training

Yijiong Yu, Ziyun Dai, Zekun Wang +3

Large language models (LLMs) have demonstrated remarkable capabilities, but their success heavily relies on the quality of pretraining corpora. For Chinese LLMs, the scarcity of hi…

cs.CL2024

Next Token Prediction Towards Multimodal Intelligence: A Comprehensive Survey

Liang Chen, Zekun Wang, Shuhuai Ren +24

Building on the foundations of language modeling in natural language processing, Next Token Prediction (NTP) has evolved into a versatile training objective for machine learning ta…

cs.CL2024

M2rc-Eval: Massively Multilingual Repository-level Code Completion Evaluation

Jiaheng Liu, Ken Deng, Congnan Liu +13

Repository-level code completion has drawn great attention in software engineering, and several benchmark datasets have been introduced. However, existing repository-level code com…

cs.CL2024

PopAlign: Diversifying Contrasting Patterns for a More Comprehensive Alignment

Zekun Moore Wang, Shawn Wang, Kang Zhu +5

Alignment of large language models (LLMs) involves training models on preference-contrastive output pairs to adjust their responses according to human preferences. To obtain such c…