arXiv subjects

Dan Brown

Publications and source records attributed to Dan Brown.

8 recordsLinked to original sources

arXiv2025

Mind the Gap: Conformative Decoding to Improve Output Diversity of Instruction-Tuned Large Language Models

Instruction-tuning large language models (LLMs) reduces the diversity of their outputs, which has implications for many tasks, particularly for creative tasks. This paper investigates the ``diversity gap'' for a writing prompt narrative generation task. This gap emerges as measured by current diversity metrics for various open-weight and open-source LLMs. The results show significant decreases in diversity due to instruction-tuning. We explore the diversity loss at each fine-tuning stage for the OLMo and OLMo 2 models to further understand how output diversity is affected. The results indicate that DPO has the most substantial impact on diversity. Motivated by these findings, we present a new decoding strategy, conformative decoding, which guides an instruct model using its more diverse base model to reintroduce output diversity. We show that conformative decoding typically increases diversity and even maintains or improves quality.

cs.CL↗

arXiv2025

Can Large Language Models Outperform Non-Experts in Poetry Evaluation? A Comparative Study Using the Consensual Assessment Technique

This study adapts the Consensual Assessment Technique (CAT) for Large Language Models (LLMs), introducing a novel methodology for poetry evaluation. Using a 90-poem dataset with a ground truth based on publication venue, we demonstrate that this approach allows LLMs to significantly surpass the performance of non-expert human judges. Our method, which leverages forced-choice ranking within small, randomized batches, enabled Claude-3-Opus to achieve a Spearman's Rank Correlation of 0.87 with the ground truth, dramatically outperforming the best human non-expert evaluation (SRC = 0.38). The LLM assessments also exhibited high inter-rater reliability, underscoring the methodology's robustness. These findings establish that LLMs, when guided by a comparative framework, can be effective and reliable tools for assessing poetry, paving the way for their broader application in other creative domains.

cs.CL↗

arXiv2024

Is Temperature the Creativity Parameter of Large Language Models?

Large language models (LLMs) are applied to all sorts of creative tasks, and their outputs vary from beautiful, to peculiar, to pastiche, into plain plagiarism. The temperature parameter of an LLM regulates the amount of randomness, leading to more diverse outputs; therefore, it is often claimed to be the creativity parameter. Here, we investigate this claim using a narrative generation task with a predetermined fixed context, model and prompt. Specifically, we present an empirical analysis of the LLM output for different temperature values using four necessary conditions for creativity in narrative generation: novelty, typicality, cohesion, and coherence. We find that temperature is weakly correlated with novelty, and unsurprisingly, moderately correlated with incoherence, but there is no relationship with either cohesion or typicality. However, the influence of temperature on creativity is far more nuanced and weak than suggested by the "creativity parameter" claim; overall results suggest that the LLM generates slightly more novel outputs as temperatures get higher. Finally, we discuss ideas to allow more controlled LLM creativity, rather than relying on chance via changing the temperature parameter.

cs.CL↗

arXiv2023

Bits of Grass: Does GPT already know how to write like Whitman?

This study examines the ability of GPT-3.5, GPT-3.5-turbo (ChatGPT) and GPT-4 models to generate poems in the style of specific authors using zero-shot and many-shot prompts (which use the maximum context length of 8192 tokens). We assess the performance of models that are not fine-tuned for generating poetry in the style of specific authors, via automated evaluation. Our findings indicate that without fine-tuning, even when provided with the maximum number of 17 poem examples (8192 tokens) in the prompt, these models do not generate poetry in the desired style.

cs.CL↗

arXiv2023

Automated Time-frequency Domain Audio Crossfades using Graph Cuts

The problem of transitioning smoothly from one audio clip to another arises in many music consumption scenarios, especially as music consumption has moved from professionally curated and live-streamed radios to personal playback devices and services. we present the first steps toward a new method of automatically transitioning from one audio clip to another by discretizing the frequency spectrum into bins and then finding transition times for each bin. We phrase the problem as one of graph flow optimization; specifically min-cut/max-flow.

cs.SD↗

arXiv2023

Large Music Recommendation Studies for Small Teams

Running live music recommendation studies without direct industry partnerships can be a prohibitively daunting task, especially for small teams. In order to help future researchers interested in such evaluations, we present a number of struggles we faced in the process of generating our own such evaluation system alongside potential solutions. These problems span the topics of users, data, computation, and application architecture.

cs.HC↗

arXiv2022

Hybrid normal mode and energy flux model for an ideal oceanic wedge environment with radial sound speed front

Energy flux is an acoustic propagation model that calculates the locally-averaged intensity without computing explicit eigenvalues or tracing rays. The energy flux method has so far only been used for two-dimensional problems that have collapsed the third dimension by rotational or translational symmetry. This report outlines the derivation and implementation of a three-dimensional ocean acoustic propagation model using a combination of normal modes and the energy flux method. This model is specifically derived for a wedge environment with a radial sound speed front at some distance from the shoreline. The hybrid energy flux model's output is compared to that of another propagation model for this environment that is built on normal modes alone. General agreement in the shape, location, and amplitude of caustic features is observed with some discrepancies that may be attributable to inherent differences in the model derivations. This work serves as a stepping-stone toward developing a more generalized three-dimensional energy flux model.

physics.comp-ph↗

arXiv2019

Shallow Art: Art Extension Through Simple Machine Learning

Shallow Art presents, implements, and tests the use of simple single-output classification and regression models for the purpose of art generation. Various machine learning algorithms are trained on collections of computer generated images, artworks from Vincent van Gogh, and artworks from Rembrandt van Rijn. These models are then provided half of an image and asked to complete the missing side. The resulting images are displayed, and we explore implications for computational creativity.

cs.CV↗