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20242026
most citedExploring Prompt Engineering Practices in the Enterprise

8 citations · 16 across the 8 of their papers we have counts for

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7 papers · 1 filter

cs.CL2024

Granite Guardian

Inkit Padhi, Manish Nagireddy, Giandomenico Cornacchia +20

We introduce the Granite Guardian models, a suite of safeguards designed to provide risk detection for prompts and responses, enabling safe and responsible use in combination with…

cs.CL2024★ 3 cited

Evaluating the Prompt Steerability of Large Language Models

Erik Miehling, Michael Desmond, Karthikeyan Natesan Ramamurthy +5

Building pluralistic AI requires designing models that are able to be shaped to represent a wide range of value systems and cultures. Achieving this requires first being able to ev…

cs.LG2024★ 1 cited

Black-box Uncertainty Quantification Method for LLM-as-a-Judge

Nico Wagner, Michael Desmond, Rahul Nair +6

LLM-as-a-Judge is a widely used method for evaluating the performance of Large Language Models (LLMs) across various tasks. We address the challenge of quantifying the uncertainty…

cs.HC2024★ 2 cited

Aligning Human and LLM Judgments: Insights from EvalAssist on Task-Specific Evaluations and AI-assisted Assessment Strategy Preferences

Zahra Ashktorab, Michael Desmond, Qian Pan +7

Evaluation of large language model (LLM) outputs requires users to make critical judgments about the best outputs across various configurations. This process is costly and takes ti…

cs.HC2024

Emerging Reliance Behaviors in Human-AI Content Grounded Data Generation: The Role of Cognitive Forcing Functions and Hallucinations

Zahra Ashktorab, Qian Pan, Werner Geyer +5

We investigate the impact of hallucinations and Cognitive Forcing Functions in human-AI collaborative content-grounded data generation, focusing on the use of Large Language Models…

cs.HC2024★ 1 cited

Human-Centered Design Recommendations for LLM-as-a-Judge

Qian Pan, Zahra Ashktorab, Michael Desmond +5

Traditional reference-based metrics, such as BLEU and ROUGE, are less effective for assessing outputs from Large Language Models (LLMs) that produce highly creative or superior-qua…

cs.HC2024★ 8 cited

Exploring Prompt Engineering Practices in the Enterprise

Michael Desmond, Michelle Brachman

Interaction with Large Language Models (LLMs) is primarily carried out via prompting. A prompt is a natural language instruction designed to elicit certain behaviour or output from…