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20242026
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cs.CL2026

OPT-Engine: Benchmarking the Limits of LLMs in Optimization Modeling via Complexity Scaling

Yitian Chen, Cheng Cheng, Yinan Sun +2

We investigate the capabilities and scalability of Large Language Models (LLMs) in optimization modeling, a domain requiring structured reasoning and precise formulation. To this e…

cs.CL2025

AD-AGENT: A Multi-agent Framework for End-to-end Anomaly Detection

Tiankai Yang, Junjun Liu, Wingchun Siu +6

Anomaly detection (AD) is essential in areas such as fraud detection, network monitoring, and scientific research. However, the diversity of data modalities and the increasing numb…

cs.CL2025

A Comparative Study of Large Language Models and Human Personality Traits

Wang Jiaqi, Wang bo, Guo fa +2

Large Language Models (LLMs) have demonstrated human-like capabilities in language comprehension and generation, becoming active participants in social and cognitive domains. This…

cs.CL2024

Skywork-MoE: A Deep Dive into Training Techniques for Mixture-of-Experts Language Models

Tianwen Wei, Bo Zhu, Liang Zhao +13

In this technical report, we introduce the training methodologies implemented in the development of Skywork-MoE, a high-performance mixture-of-experts (MoE) large language model (L…

cs.CL2024

LongSkywork: A Training Recipe for Efficiently Extending Context Length in Large Language Models

Liang Zhao, Tianwen Wei, Liang Zeng +12

We introduce LongSkywork, a long-context Large Language Model (LLM) capable of processing up to 200,000 tokens. We provide a training recipe for efficiently extending context lengt…