Large Language Models (LLMs) have shown excellent generalization capabilities that have
led to the development of numerous models. These models propose various new …

In this work, we develop and release Llama 2, a collection of pretrained and fine-tuned large
language models (LLMs) ranging in scale from 7 billion to 70 billion parameters. Our fine …

Abstract Large Language Models (LLMs) can achieve strong performance on many tasks by
producing step-by-step reasoning before giving a final output, often referred to as chain-of …

Recent AI-assistant agents, such as ChatGPT, predominantly rely on supervised fine-tuning
(SFT) with human annotations and reinforcement learning from human feedback (RLHF) to …

Agents capable of carrying out general tasks on a computer can improve efficiency and
productivity by automating repetitive tasks and assisting in complex problem-solving. Ideally …

Optimization is ubiquitous. While derivative-based algorithms have been powerful tools for
various problems, the absence of gradient imposes challenges on many real-world …

Large language models (LLMs) have achieved impressive performance on code generation.
However, for complex programming tasks, generating the correct solution in one go …

Large Language Models (LLMs) have emerged as a groundbreaking technology with their
unparalleled text generation capabilities across various applications. Nevertheless …

Recent developments in large language models (LLMs) have been impressive. However,
these models sometimes show inconsistencies and problematic behavior, such as …

Large language models (LLMs) have exploded a new heatwave of AI for their ability to
engage end-users in human-level conversations with detailed and articulate answers across …