3 citations · 3 across the 4 of their papers we have counts for
5 papers
AwarenessBench: Assessing Cognitive Capabilities of Language Models
Xiaojian Li, Rongwu Xu, Tianyun Zhang +9
As language models (LMs) exhibit increasingly consciousness-like behaviors, evaluating their cognitive abilities becomes essential. We introduce AwarenessBench, the first comprehen…
WindFM: An Open-Source Foundation Model for Zero-Shot Wind Power Forecasting
Hang Fan, Yu Shi, Zongliang Fu +4
High-quality wind power forecasting is crucial for the operation of modern power grids. However, prevailing data-driven paradigms either train a site-specific model which cannot ge…
Kronos: A Foundation Model for the Language of Financial Markets
Yu Shi, Zongliang Fu, Shuo Chen +4
The success of large-scale pre-training paradigm, exemplified by Large Language Models (LLMs), has inspired the development of Time Series Foundation Models (TSFMs). However, their…
MegatronApp: Efficient and Comprehensive Management on Distributed LLM Training
Bohan Zhao, Guang Yang, Shuo Chen +4
The rapid escalation in the parameter count of large language models (LLMs) has transformed model training from a single-node endeavor into a highly intricate, cross-node activity.…
Nuclear Deployed: Analyzing Catastrophic Risks in Decision-making of Autonomous LLM Agents
Rongwu Xu, Xiaojian Li, Shuo Chen +1
Large language models (LLMs) are evolving into autonomous decision-makers, raising concerns about catastrophic risks in high-stakes scenarios, particularly in Chemical, Biological,…