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Found 9 papers, 6 papers with code
Rediscovering the Latent Dimensions of Personality with Large Language Models as Trait Descriptors
Assessing personality traits using large language models (LLMs) has emerged as an interesting and challenging area of research.
Efficient and Scalable Estimation of Tool Representations in Vector Space
To address those challenges, we present a novel framework for generating synthetic data for tool retrieval applications and an efficient data-driven tool retrieval strategy using small encoder models.
TinyAgent: Function Calling at the Edge
Recent large language models (LLMs) have enabled the development of advanced agentic systems that can integrate various tools and APIs to fulfill user queries through function calling.
Virtual Personas for Language Models via an Anthology of Backstories
Large language models (LLMs) are trained from vast repositories of text authored by millions of distinct authors, reflecting an enormous diversity of human traits.
An LLM Compiler for Parallel Function Calling
To address this, we introduce LLMCompiler, which executes functions in parallel to efficiently orchestrate multiple function calls.
Ensuring Visual Commonsense Morality for Text-to-Image Generation
Text-to-image generation methods produce high-resolution and high-quality images, but these methods should not produce immoral images that may contain inappropriate content from the perspective of commonsense morality.
Zero-shot Visual Commonsense Immorality Prediction
Here, we propose a model that predicts visual commonsense immorality in a zero-shot manner.
An Embedding-Dynamic Approach to Self-supervised Learning
It also uses a purely-dynamic local dispersive force (Brownian motion) that shows improved performance over other methods and does not require knowledge of other particle coordinates.
