3 papers
cs.CL2024
ChatQA 2: Bridging the Gap to Proprietary LLMs in Long Context and RAG Capabilities
Peng Xu, Wei Ping, Xianchao Wu +4
In this work, we introduce ChatQA 2, an Llama 3.0-based model with a 128K context window, designed to bridge the gap between open-source LLMs and leading proprietary models (e.g.,…
cs.CL2023★ 3 cited
SteerLM: Attribute Conditioned SFT as an (User-Steerable) Alternative to RLHF
Yi Dong, Zhilin Wang, Makesh Narsimhan Sreedhar +2
Model alignment with human preferences is an essential step in making Large Language Models (LLMs) helpful and consistent with human values. It typically consists of supervised fin…
cs.CL2023
Retrieval meets Long Context Large Language Models
Peng Xu, Wei Ping, Xianchao Wu +7
Extending the context window of large language models (LLMs) is getting popular recently, while the solution of augmenting LLMs with retrieval has existed for years. The natural qu…