8 papers · 1 filter
From Generalist to Specialist: A Survey of Large Language Models for Chemistry
Yang Han, Ziping Wan, Lu Chen +2
Large Language Models (LLMs) have significantly transformed our daily life and established a new paradigm in natural language processing (NLP). However, the predominant pretraining…
AdaEAGLE: Optimizing Speculative Decoding via Explicit Modeling of Adaptive Draft Structures
Situo Zhang, Hankun Wang, Da Ma +4
Speculative Decoding (SD) is a popular lossless technique for accelerating the inference of Large Language Models (LLMs). We show that the decoding speed of SD frameworks with stat…
SciDFM: A Large Language Model with Mixture-of-Experts for Science
Liangtai Sun, Danyu Luo, Da Ma +7
Recently, there has been a significant upsurge of interest in leveraging large language models (LLMs) to assist scientific discovery. However, most LLMs only focus on general scien…
Rejection Improves Reliability: Training LLMs to Refuse Unknown Questions Using RL from Knowledge Feedback
Hongshen Xu, Zichen Zhu, Situo Zhang +4
Large Language Models (LLMs) often generate erroneous outputs, known as hallucinations, due to their limitations in discerning questions beyond their knowledge scope. While address…
Mobile-Env: Building Qualified Evaluation Benchmarks for LLM-GUI Interaction
Danyang Zhang, Zhennan Shen, Rui Xie +8
The Graphical User Interface (GUI) is pivotal for human interaction with the digital world, enabling efficient device control and the completion of complex tasks. Recent progress i…
Evolving Subnetwork Training for Large Language Models
Hanqi Li, Lu Chen, Da Ma +3
Large language models have ushered in a new era of artificial intelligence research. However, their substantial training costs hinder further development and widespread adoption. I…