Large language models (LLMs) often exhibit deficient reasoning or generate hallucinations.
To address these, studies prefixed with" Self-" such as Self-Consistency, Self-Improve, and …

Analyzing unstructured data has been a persistent challenge in data processing. Large
Language Models (LLMs) have shown promise in this regard, leading to recent proposals …

Language-based agentic systems have shown great promise in recent years, transitioning
from solving small-scale research problems to being deployed in challenging real-world …

Solving complex real-world tasks requires cycles of actions and observations. This is
particularly true in science, where tasks require many cycles of analysis, tool use, and …

Augmented Large Language Models (LLMs) enhance the capabilities of standalone LLMs
by integrating external data sources through API calls. In interactive LLM applications …

Large Language Models (LLMs) are increasingly embedded into software products across
diverse industries, enhancing user experiences, but at the same time introducing numerous …

Text-based AI system optimization typically involves a feedback loop scheme where a single
LLM generates an evaluation in natural language of the current output to improve the next …

Given a task in the form of a basic description and its training examples, prompt optimization
is the problem of synthesizing the given information into a text prompt for a large language …