Use large language model to enhance reasoning of another large language model through reward updated GRPO [PDF]
Scientific ReportsRecent advancements in deep learning have significantly transformed natural language processing (NLP), enabling sophisticated reasoning and text generation.
Yiqiao Yin
doaj +2 more sources
Efficient Memory Management for Large Language Model Serving with PagedAttention [PDF]
Symposium on Operating Systems Principles, 2023 High throughput serving of large language models (LLMs) requires batching sufficiently many requests at a time. However, existing systems struggle because the key-value cache (KV cache) memory for each request is huge and grows and shrinks dynamically ...
Woosuk Kwon +8 more
semanticscholar +1 more source
A survey on large language model based autonomous agents [PDF]
Frontiers of Computer Science, 2023 Autonomous agents have long been a research focus in academic and industry communities. Previous research often focuses on training agents with limited knowledge within isolated environments, which diverges significantly from human learning processes ...
Lei Wang +12 more
semanticscholar +1 more source
The Rise and Potential of Large Language Model Based Agents: A Survey [PDF]
arXiv.org, 2023 For a long time, humanity has pursued artificial intelligence (AI) equivalent to or surpassing the human level, with AI agents considered a promising vehicle for this pursuit. AI agents are artificial entities that sense their environment, make decisions,
Zhiheng Xi +29 more
semanticscholar +1 more source
LISA: Reasoning Segmentation via Large Language Model [PDF]
Computer Vision and Pattern Recognition, 2023 Although perception systems have made remarkable ad-vancements in recent years, they still rely on explicit human instruction or pre-defined categories to identify the target objects before executing visual recognition tasks. Such systems cannot actively
Xin Lai +6 more
semanticscholar +1 more source
Accelerating Large Language Model Decoding with Speculative Sampling [PDF]
arXiv.org, 2023 We present speculative sampling, an algorithm for accelerating transformer decoding by enabling the generation of multiple tokens from each transformer call.
Charlie Chen +5 more
semanticscholar +1 more source
TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation [PDF]
ACM Conference on Recommender Systems, 2023 Large Language Models (LLMs) have demonstrated remarkable performance across diverse domains, thereby prompting researchers to explore their potential for use in recommendation systems. Initial attempts have leveraged the exceptional capabilities of LLMs,
Keqin Bao +5 more
semanticscholar +1 more source
OpenAssistant Conversations - Democratizing Large Language Model Alignment [PDF]
Neural Information Processing Systems, 2023 Aligning large language models (LLMs) with human preferences has proven to drastically improve usability and has driven rapid adoption as demonstrated by ChatGPT.
Andreas Kopf +17 more
semanticscholar +1 more source
A Survey on Large Language Model (LLM) Security and Privacy: The Good, the Bad, and the Ugly [PDF]
High Confid. Comput., 2023 Large Language Models (LLMs), such as ChatGPT and Bard, have revolutionized natural language understanding and generation. They possess deep language comprehension, human-like text generation capabilities, contextual awareness, and robust problem-solving
Yifan Yao +5 more
semanticscholar +1 more source
ChatDoctor: A Medical Chat Model Fine-Tuned on a Large Language Model Meta-AI (LLaMA) Using Medical Domain Knowledge [PDF]
Cureus, 2023 Objective The primary aim of this research was to address the limitations observed in the medical knowledge of prevalent large language models (LLMs) such as ChatGPT, by creating a specialized language model with enhanced accuracy in medical advice ...
Yunxiang Li +5 more
semanticscholar +1 more source