Results 231 to 240 of about 6,924 (296)

Bias in, symbolic compliance out? GPT's reliance on gender and race in strategic evaluations

open access: yesStrategic Management Journal, EarlyView.
Abstract Research summary Organizations are increasingly using large language models (LLMs) to support strategic evaluations. We examine whether and how these systems rely on gender and race. We asked GPT to evaluate identical startup pitches varying only the founder's name, shaping gender and race perceptions.
Tristan L. Botelho, Qingyang (Iris) Wang
wiley   +1 more source

Large‐Scale Structural Dynamics in the Tail Fiber Modulate the Infective Transition of the T7 Bacteriophage

open access: yesSmall, EarlyView.
During host recognition, the fibers of T7 bacteriophages transition from a capsid bound state to an extended conformation, which requires some level of fiber flexibility. By using high‐speed atomic force microscopy, we show that the fibers have an internal molecular hinge and a torsionally compliant coiled‐coil region.
Luca Elizabet Kosik   +16 more
wiley   +1 more source

Automatic text readability assessment for educational content based on graph representation learning. [PDF]

open access: yesSci Rep
Zhang L   +8 more
europepmc   +1 more source

A Large Language Model‐Based Approach for Fault Detection and Its Application

open access: yesSafety Science and Technology, EarlyView.
This work proposes an interpretable fault detection framework utilizing pre‐trained large language models to overcome small sample sizes and label scarcity in industrial datasets. A stepwise tuple‐based validation mitigates hallucinations, ensuring reliable detection.
Yihua Ye, Yin Zhu, Liming Che, Hua Zhou
wiley   +1 more source

Balancing Accuracy and Cost: Trade‐Offs in Large Language Model Quantization for the Systems Engineering Domain

open access: yesSystems Engineering, EarlyView.
ABSTRACT As Large Language Models (LLMs) are increasingly deployed within the systems engineering domain, optimizing these models to balance performance accuracy and cost for given computational resources becomes essential. One process for finding the right balance is quantization, a process that involves converting model parameters from higher ...
Ryan Bell   +2 more
wiley   +1 more source

Baselining Large Language Model Performance in Systems Engineering Using SysEngBench

open access: yesSystems Engineering, EarlyView.
ABSTRACT In the rapidly evolving field of artificial intelligence (AI), large language model s (LLMs) have demonstrated impressive capabilities in generating natural language. However, their proficiency in specialized domains, particularly in the field of systems engineering (SE), remains less explored and unquantified.
Ryan Bell   +3 more
wiley   +1 more source

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