Language agents have achieved considerable performance on various complex tasks.
Despite the incessant exploration in this field, existing language agent systems still struggle …

LLM-as-a-Judge and reward models are widely used alternatives of multiple-choice
questions or human annotators for large language model (LLM) evaluation. Their efficacy …

Large Language Models (LLMs) have become integral components in various autonomous
agent systems. In this study, we present an exploration-based trajectory optimization …

Large language models (LLMs) have significantly advanced in various fields and intelligent
agent applications. However, current LLMs that learn from human or external model …

Existing LLM agent systems typically select actions from a fixed and predefined set at every
step. While this approach is effective in closed, narrowly-scoped environments, we argue …

Scientific innovation is pivotal for humanity, and harnessing large language models (LLMs)
to generate research ideas could transform discovery. However, existing LLMs often …

Abstract Large Language Models (LLMs) have taken the field of AI by storm, but their
adoption in the field of Artificial Life (ALife) has been, so far, relatively reserved. In this work …

Existing ML benchmarks lack the depth and diversity of annotations needed for evaluating
models on business process management (BPM) tasks. BPM is the practice of documenting …

The reasoning abilities of Large Language Models (LLMs) remain a topic of debate. Some
methods such as ReAct-based prompting, have gained popularity for claiming to enhance …

Language agents have demonstrated autonomous decision-making abilities by reasoning
with foundation models. Recently, efforts have been made to train language agents for …