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Found 9 papers, 6 papers with code
Methods for Legal Citation Prediction in the Age of LLMs: An Australian Law Case Study
In recent years, Large Language Models (LLMs) have shown great potential across a wide range of legal tasks.
Agent S: An Open Agentic Framework that Uses Computers Like a Human
We present Agent S, an open agentic framework that enables autonomous interaction with computers through a Graphical User Interface (GUI), aimed at transforming human-computer interaction by automating complex, multi-step tasks.
Strategies for Improving NL-to-FOL Translation with LLMs: Data Generation, Incremental Fine-Tuning, and Verification
Research in symbolic logical reasoning explored FOL generation using state-of-the-art LLMs (i. e., GPT-4) to produce FOL translations of natural language (NL) statements, but errors in translation are usually not the focus.
Towards Uncertainty-Aware Language Agent
We present the Uncertainty-Aware Language Agent (UALA), a framework that orchestrates the interaction between the agent and the external world using uncertainty quantification.
POSQA: Probe the World Models of LLMs with Size Comparisons
Embodied language comprehension emphasizes that language understanding is not solely a matter of mental processing in the brain but also involves interactions with the physical and social environment.
Reward Engineering for Generating Semi-structured Explanation
Semi-structured explanation depicts the implicit process of a reasoner with an explicit representation.
PiVe: Prompting with Iterative Verification Improving Graph-based Generative Capability of LLMs
We show how a small language model could be trained to act as a verifier module for the output of an LLM~(i. e., ChatGPT, GPT-4), and to iteratively improve its performance via fine-grained corrective instructions.
Self-supervised Graph Masking Pre-training for Graph-to-Text Generation
Large-scale pre-trained language models (PLMs) have advanced Graph-to-Text (G2T) generation by processing the linearised version of a graph.
