CoMPosT: Characterizing and Evaluating Caricature in LLM Simulations

Recent work has aimed to capture nuances of human behavior by using LLMs to simulate responses from particular demographics in settings like social science experiments and public opinion surveys. However, there are currently no established ways to discuss or evaluate the quality of such LLM simulations. Moreover, there is growing concern that these LLM simulations are flattened caricatures of the personas that they aim to simulate, failing to capture the multidimensionality of people and perpetuating stereotypes. To bridge these gaps, we present CoMPosT, a framework to characterize LLM simulations using four dimensions: Context, Model, Persona, and Topic. We use this framework to measure open-ended LLM simulations' susceptibility to caricature, defined via two criteria: individuation and exaggeration. We evaluate the level of caricature in scenarios from existing work on LLM simulations. We find that for GPT-4, simulations of certain demographics (political and marginalized groups) and topics (general, uncontroversial) are highly susceptible to caricature.Comment: To appear at EMNLP 2023 (Main

Signal Denoising Method Based on Adaptive Redundant Second-Generation Wavelet for Rotating Machinery Fault Diagnosis

Vibration signal of rotating machinery is often submerged in a large amount of noise, leading to the decrease of fault diagnosis accuracy. In order to improve the denoising effect of the vibration signal, an adaptive redundant second-generation wavelet (ARSGW) denoising method is proposed. In this method, a new index for denoising result evaluation (IDRE) is constructed first. Then, the maximum value of IDRE and the genetic algorithm are taken as the optimization objective and the optimization algorithm, respectively, to search for the optimal parameters of the ARSGW. The obtained optimal redundant second-generation wavelet (RSGW) is used for vibration signal denoising. After that, features are extracted from the denoised signal and then input into the support vector machine method for fault recognition. The application result indicates that the proposed ARSGW denoising method can effectively improve the accuracy of rotating machinery fault diagnosis

Local structure of glassy lithium phosphorus oxynitride thin films: a combined experimental and ab initio approach

Lithium phosphorus oxynitride (LiPON) is an amorphous solid-state lithium ion conductor displaying exemplary cyclability against lithium metal anodes. There is no definitive explanation for this stability due to the limited understanding of the structure of LiPON. We provide a structural model of RF-sputtered LiPON via experimental and computational spectroscopic methods. Information about the short-range structure results from 1D and 2D solid-state nuclear magnetic resonance experiments investigating chemical shift anisotropy and dipolar interactions. These results are compared with first principles chemical shielding calculations of Li-P-O/N crystals and ab initio molecular dynamics-generated amorphous LiPON models to unequivocally identify the glassy structure as primarily isolated phosphate monomers with N incorporated in both apical and as bridging sites in phosphate dimers. Structural results suggest LiPON's stability is a result of its glassy character. Free-standing LiPON films are produced that exhibit a high degree of flexibility highlighting the unique mechanical properties of glassy materials

Pressure-tailored lithium deposition and dissolution in lithium metal batteries

A porous electrode resulting from unregulated Li growth is the major cause of the low Coulombic efficiency and potential safety hazards of rechargeable Li metal batteries. Strategies aiming to achieve large granular Li deposits have been extensively explored; yet, the ideal Li deposits, which consist of large Li particles that are seamlessly packed on the electrode and can be reversibly deposited and stripped, have never been achieved. Here, by controlling the uniaxial stack pressure during battery operation, a dense Li deposition (99.49% electrode density) with an ideal columnar structure has been achieved. Using multi-scale characterization and simulation, we elucidated the critical role of stack pressure on Li nucleation, growth and dissolution processes, and developed innovative strategies to maintain the ideal Li morphology during extended cycling. The precision manipulation of Li deposition and dissolution is a critical step to enable fast charging and low temperature operation for Li metal batteries

Unveiling the Stable Nature of the Solid Electrolyte Interphase between Lithium Metal and LiPON via Cryogenic Electron Microscopy

The solid electrolyte interphase (SEI) is regarded as the most complex but the least understood constituent in secondary batteries using liquid and solid electrolytes. The nanostructures of SEIs were recently reported to be equally important to the chemistry of SEIs for stabilizing Li metal in liquid electrolyte. However, the dearth of such knowledge in all-solid-state battery (ASSB) has hindered a complete understanding of how certain solid-state electrolytes, such as LiPON, manifest exemplary stability against Li metal. Characterizing such solid-solid interfaces is difficult due to the buried, highly reactive, and beam-sensitive nature of the constituents within. By employing cryogenic electron microscopy (cryo-EM), the interphase between Li metal and LiPON is successfully preserved and probed, revealing a multilayer mosaic SEI structure with concentration gradients of nitrogen and phosphorous, materializing as crystallites within an amorphous matrix. This unique SEI nanostructure is less than 80 nm and is shown stable and free of any organic lithium containing species or lithium fluoride components, in contrast to SEIs often found in state-of-the-art organic liquid electrolytes. Our findings reveal insights on the nanostructures and chemistry of such SEIs as a key component in lithium metal batteries to stabilize Li metal anode