37 citations · 54 across the 9 of their papers we have counts for
9 papers
TrasMuon: Trust-Region Adaptive Scaling for Orthogonalized Momentum Optimizers
Peng Cheng, Jiucheng Zang, Qingnan Li +6
Muon-style optimizers leverage Newton-Schulz (NS) iterations to orthogonalize updates, yielding update geometries that often outperform Adam-series methods. However, this orthogona…
AstroMMBench: A Benchmark for Evaluating Multimodal Large Language Models Capabilities in Astronomy
Jinghang Shi, Xiaoyu Tang, Yang Huang +4
Astronomical image interpretation presents a significant challenge for applying multimodal large language models (MLLMs) to specialized scientific tasks. Existing benchmarks focus…
Reasoning on a Budget: A Survey of Adaptive and Controllable Test-Time Compute in LLMs
Mohammad Ali Alomrani, Yingxue Zhang, Derek Li +14
Large language models (LLMs) have rapidly progressed into general-purpose agents capable of solving a broad spectrum of tasks. However, current models remain inefficient at reasoni…
Skywork Open Reasoner 1 Technical Report
Jujie He, Jiacai Liu, Chris Yuhao Liu +14
The success of DeepSeek-R1 underscores the significant role of reinforcement learning (RL) in enhancing the reasoning capabilities of large language models (LLMs). In this work, we…
Echo: Simulating Distributed Training At Scale
Yicheng Feng, Yuetao Chen, Kaiwen Chen +7
Simulation offers unique values for both enumeration and extrapolation purposes, and is becoming increasingly important for managing the massive machine learning (ML) clusters and…
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…
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…
Exploring the Frontiers of LLMs in Psychological Applications: A Comprehensive Review
Luoma Ke, Song Tong, Peng Cheng +1
This paper explores the frontiers of large language models (LLMs) in psychology applications. Psychology has undergone several theoretical changes, and the current use of Artificia…
Skywork: A More Open Bilingual Foundation Model
Tianwen Wei, Liang Zhao, Lichang Zhang +27
In this technical report, we present Skywork-13B, a family of large language models (LLMs) trained on a corpus of over 3.2 trillion tokens drawn from both English and Chinese texts…