687 citations · 1.7k across the 81 of their papers we have counts for
13 papers · 2 filters
Democratizing Reasoning Ability: Tailored Learning from Large Language Model
Zhaoyang Wang, Shaohan Huang, Yuxuan Liu +8
Large language models (LLMs) exhibit impressive emergent abilities in natural language processing, but their democratization is hindered due to huge computation requirements and cl…
BitNet: Scaling 1-bit Transformers for Large Language Models
Hongyu Wang, Shuming Ma, Li Dong +7
The increasing size of large language models has posed challenges for deployment and raised concerns about environmental impact due to high energy consumption. In this work, we int…
Calibrating LLM-Based Evaluator
Yuxuan Liu, Tianchi Yang, Shaohan Huang +6
Recent advancements in large language models (LLMs) on language modeling and emergent capabilities make them a promising reference-free evaluator of natural language generation qua…
KOSMOS-2.5: A Multimodal Literate Model
Tengchao Lv, Yupan Huang, Jingye Chen +13
The automatic reading of text-intensive images represents a significant advancement toward achieving Artificial General Intelligence (AGI). In this paper we present KOSMOS-2.5, a m…
Adapting Large Language Models to Domains via Reading Comprehension
Daixuan Cheng, Shaohan Huang, Furu Wei
We explore how continued pre-training on domain-specific corpora influences large language models, revealing that training on the raw corpora endows the model with domain knowledge…
Retentive Network: A Successor to Transformer for Large Language Models
Yutao Sun, Li Dong, Shaohan Huang +5
In this work, we propose Retentive Network (RetNet) as a foundation architecture for large language models, simultaneously achieving training parallelism, low-cost inference, and g…