For a long time, researchers have sought artificial intelligence (AI) that matches or exceeds
human intelligence. AI agents, which are artificial entities capable of sensing the …

Autonomous agents have long been a research focus in academic and industry
communities. Previous research often focuses on training agents with limited knowledge …

The emergence of large language models (LLMs) has marked a significant breakthrough in
natural language processing (NLP), fueling a paradigm shift in information acquisition …

Generation of plausible yet incorrect factual information, termed hallucination, is an
unsolved issue in large language models. We study the ability of language models to …

Self-correction is an approach to improving responses from large language models (LLMs)
by refining the responses using LLMs during inference. Prior work has proposed various self …

Large language models (LLMs) are popular for high-quality text generation but can produce
harmful content, even when aligned with human values through reinforcement learning …

This paper introduces a pioneering approach to artificial intelligence research, embodied in
our O1 Replication Journey. In response to the announcement of OpenAI's groundbreaking …

Dialogue-based language models mark a huge milestone in the field of artificial intelligence,
by their impressive ability to interact with users, as well as a series of challenging tasks …

Abstract Compared with Large Language Models (LLMs), Large Vision-Language Models
(LVLMs) can also accept images as input, thus showcasing more interesting emergent …

While large language models (LLMs) have shown remarkable effectiveness in various NLP
tasks, they are still prone to issues such as hallucination, unfaithful reasoning, and toxicity. A …